The customs statistics of the Russian Federation, like most other countries, consists of statistics on foreign economic activity (goods) and customs statistics.

Customs statistics is a part of economic statistics and at the same time a part of customs, studying the quantitative side, mass phenomena and processes occurring in foreign trade, as well as in the operational and supporting activities of the customs department itself

The subject of foreign trade statistics is the study of the quantitative side of phenomena and processes in connection with their qualitative content in the field of foreign economic activity.

The object in foreign trade statistics is the country's foreign trade turnover, i.e. exports and imports, and data on international trade are formed after processing the primary statistical data on foreign trade of individual countries.

International trade is the exchange of goods and services between states - the main form of international economic relations.

Customs statistics method

The method is a method of studying the subject of the TS, which is based on three successive stages:

Mass statistical observation;

Statistical summary and grouping of data;

Calculation of generalizing indicators and their economic and statistical analysis.

All stages pursue the same goal: to identify patterns in the subject of foreign trade statistics.

Question 2. Statistical observation in the vehicle

Observation is the collection of primary digital data about the object of study.

The purpose of monitoring in foreign trade is to determine the value of exports and imports, their quantitative and qualitative indicators, their geographical distribution.

Object stat. Observations in foreign trade is the totality of all imports and exports.

Statistical observation is carried out by registering the movement of individual goods (consignments of goods) during export or import. Each separately registered item is called an observation unit. There is also a reporting unit category - a legal or natural person providing data on the phenomenon under study.

In the Russian Federation, the reporting unit is firms and individual individuals- participants in foreign economic activity.

A place where the processes and phenomena of foreign trade are recorded, where stats take place. Observations are the customs institutions of the Russian Federation.

The period to which the received TS data relate is called the observation time. Specifically, these are calendar: month, quarter, year.

Since 01/01/1991, the main document of primary statistical information in the Customs Union is a declaration for goods, drawn up on the basis of the form of a single administrative document (SAD) used in the EU.

According to the degree of coverage of the object, the observation is divided into continuous and non-continuous. Non-continuous is used more often than continuous.

Part 1. Customs statistics of foreign trade

Topic 1. The role and place of customs statistics

AT scientific use of the term "statistics" 1 was introduced by the German scientist Gottfried Achenwal in 1746, proposing to replace the name of the course "State Studies", taught at German universities, with "Statistics", thereby laying the foundation for the development of statistics as a science and academic discipline.

AT Currently, this term is used in 4 meanings:

1) science, which studies the quantitative side of mass phenomena and processes in close connection with their qualitative content - a subject in higher and secondary specialized educational institutions;

2) collection of digital information characterizing the state of mass phenomena and processes of social life; statistical data, presented in the reports of enterprises, organizations, sectors of the economy, as well as published in collections, reference books, periodicals and on the Internet, which are the result of statistical work;

3) field of practice("statistical accounting") for the collection,

processing, analysis and publication of massive digital data on a wide variety of phenomena and processes in public life2;

4) a certain parameter of a series of random variables obtained by a certain algorithm from the results of observations, for example, statistical criteria (critical statistics) used to test various hypotheses (presumable

statements) regarding the nature or values ​​of individual indicators of the data under study, the features of their distribution, etc.3

how scientific direction customs statistics is characterized by the subject,

object, purpose, objectives and methods of research. Customs statistics has a common subject and methods for all statistical disciplines.

The subject of customs statistics is mass phenomena (statistical aggregates), as well as the numerical expression of the regularities manifested in them, and its methods are based on the law of large numbers, which makes it possible to use statistical theory tools in the analysis of customs statistics data, and to assess the reliability of statistical estimates and conclusions - apparatus of mathematical statistics. Customs statistics, like other sectoral statistical disciplines, stands out as an independent discipline due to a separate object of study, goals and objectives.

1 From lat.status - state, state of affairs; originally the term was used in the meaning of "political condition"2 This activity on professional level carries out government statistics–

The Federal State Statistics Service (FSGS) and the system of its institutions organized on an administrative-territorial basis, as well as departmental statistics(at enterprises, departments, ministries, etc.)

3 The term "statistics" as a parameter, as a statistical criterion, is used mainly in mathematical statistics, some of them (χ2, t, etc.) are discussed in the relevant topics of this manual

The object of study of customs statistics is the foreign trade of the Russian Federation and the activities of customs authorities.

The purpose of customs statistics is to provide the leadership of the Federal Customs Service (FCS), legislative and executive authorities with information on the state and development of foreign trade Russian Federation(RF) and on the activities of customs authorities. Accordingly, 2 sections of customs statistics are defined: customs statistics of foreign trade and special customs statistics(see fig. 1).

Customs statistics

Customs statistics of foreign trade

Statistical quantities and their observation

System of indicators and signs

Distribution ranks

Series of dynamics

Relationships

indicators

Index method

Features of cost accounting for goods

Special customs statistics

Statistics

declarations

Statistics of customs payments

Currency control statistics

Statistics of customs offenses

Movement statistics Vehicle and individuals

Other types of special customs statistics

Rice. 1. Sections and subsections of customs statistics

Maintaining and organizing customs statistics is one of the functions of the customs authorities. Legal basis customs statistics is

Customs Code (TC) [ Mistake! Reference source not found. ], the new version of which was put into effect on January 1, 2004. The data of special customs statistics are used by the customs authorities exclusively for customs purposes.

The tasks of customs statistics of foreign trade are:

– promotion of development foreign economic activity(Foreign economic activity), expansion of foreign trade relations, development of the foreign trade policy of the Russian Federation;

– development of methodological principles of analysis and a system of indicators characterizing the size, dynamics and structure of foreign trade;

– ensuring complete and reliable accounting of data on exports and imports of the Russian Federation;

– analysis of the main trends, structure and dynamics of foreign trade commodity flows of the Russian Federation in conjunction with the analysis of its macroeconomic situation and the conjuncture of world markets;

– information support of the executive and legislative authorities with the data of customs statistics of foreign trade for their decision-making in the field of the customs policy of the Russian Federation and state regulation foreign trade of the Russian Federation;

– presentation of data of customs statistics of foreign trade to international organizations;

– submission of data on customs statistics of foreign trade in order to control the receipt of customs payments to the federal budget, currency control, development of the balance of payments of the Russian Federation;

– calculation of various kinds of index indicators (for example, indices of prices and physical volume of foreign trade, etc.);

– preparation of initial data for forecasting macroeconomic indicators within the framework of the system of national accounts and the balance of payments of the Russian Federation;

– ensuring comparability of data on mutual trade between the Russian Federation and its foreign trade partners;

– presentation of data of customs statistics of foreign trade of the Russian Federation for the analysis of the effectiveness of measures in the field of tariff and non-tariff measures of state regulation of foreign economic activity;

– solution of other tasks due to the customs policy of the Russian Federation.

AT in accordance with the Constitution of the Russian Federation general management customs business carried out by the Government of the Russian Federation. Direct management is carried out by the Federal Customs Service (FTS) of Russia, which is the central body of the federal executive power. To implement the entire complex of customs measures, special customs authorities are created, which constitute single system shown in the figuresMistake! Link source is not

test questions

1. Meanings of the term "statistics"

2. Features of customs statistics, its sections and tasks

3. The structure of the customs authorities of Russia.

Topic 2. Statistical observation in customs statistics

The statistical study of certain phenomena in statistics suggests how required condition availability of information about these phenomena. Therefore, the beginning of any statistical research comes down to collecting the necessary information. The final results of the work and the conclusions of the researchers largely depend on how complete and high-quality the collected primary data will be.

The features of the object of study and the tasks set determine the specifics of the system of indicators and attributive features, as well as the forms, types and methods of statistical observation. In the customs statistics of foreign trade, these issues are regulated by the Methodology of customs statistics of foreign trade of the Russian Federation [ Mistake! Reference source not found.] (hereinafter referred to as the Methodology).

The methodology, in its statistical essence, is a program of statistical observation of Russia's foreign trade. It defines the object of statistical observation, a system of indicators and features characterizing the object of observation and representing its units of observation, sets the rules for collecting statistical information on foreign trade and determines the possibilities for its further processing and analysis. The methodology has been developed in accordance with international standards in the field of statistics, which makes the information obtained on its basis suitable for international comparisons.

The terms and definitions contained in the Methodology and used in the formation of customs statistics of foreign trade are brought into line with the terms and definitions of the Labor Code of the Russian Federation of 2003.

According to the Methodology, customs statistics of foreign trade takes into account trade in goods and does not affect trade in services. That is, the object of study of customs statistics of foreign trade is foreign trade in goods. Moreover, all goods that are added to the stocks of the country's material resources or deducted from them as a result of their import or export to the territory of the Russian Federation are taken into account. Accordingly, transit commodity flows and temporarily (up to 1 year) imported and exported goods are not taken into account. The new version of the Methodology does not define the threshold for statistical observation, although it was set in the previous version.

In the practice of international trade statistics, two systems of trade accounting are traditionally used: general and special. In accordance with the general system, the accounting of goods is carried out when they cross the state border of the country, and according to the special accounting system - when crossing its customs border. These boundaries are different if there are free customs zones and free warehouses on the territory of the state that are outside the customs territory and, therefore, the customs legislation does not apply.

The recommendations of the UN Statistical Commission give priority to the common trade accounting system. The Methodology establishes that in the customs statistics of foreign trade of the Russian Federation, common trade accounting system which contributes to data comparability.

Units of observation in the customs statistics of foreign trade of the Russian Federation are consignments of goods declared at customs clearance(Table 1).

Table 1. Units of observation in customs foreign trade statistics

As can be seen from Table. 1, not all types of customs regimes established by law4 participate in the formation of the country's foreign trade turnover.

Not taken into account in the customs statistics of foreign trade with the total

4 A list of all customs regimes for the movement of goods across the customs border of Russia is given in Appendix 3.

1) goods in transit through the territory of the state;

2) goods temporarily imported (exported) for a period of less than one year;

3) goods placed in a customs warehouse, free warehouse, free zone and intended for export outside the customs territory of the state;

4) foreign goods destroyed on the territory of the state;

5) exported goods, which the person refused in favor of the state;

6) moving supplies;

7) goods exported from the customs territory of the state and intended to ensure the functioning of embassies, consulates, representative offices at international organizations and other official representative offices of the state abroad;

8) goods transported across the customs border between the military units of the state stationed in the customs territory of the state and outside this territory;

9) goods exported to the CIS member states and intended to support the activities of medical, sports and health-improving and other institutions of the social sphere, the property of which is owned by a given state or subjects of the state, as well as for conducting research work in the territories of these states by domestic organizations in the interests of the state on a non-commercial basis;

10) domestic goods moved between customs authorities through the territory of a foreign state.

The procedure for moving goods across the customs border, which provides for the establishment of customs regimes, is not absolute. There are categories of goods to which it does not apply. Such goods are also not included in the customs statistics of foreign trade of the Russian Federation. These include:

1. Monetary gold, domestic and foreign currency, securities released into circulation.

2. Goods that are not the subject of commercial transactions:

─ moved across the border by individuals for their own use, in quantitative or value terms not exceeding the norms established by national legislation;

─ periodicals (newspapers, magazines) sent by direct subscription to individuals;

─ goods purchased by diplomatic or other missions of foreign states, armed forces, scientific organizations on the territory of the state for their own needs.

3. Goods temporarily imported (exported) for a period of less than one year.

4. Goods lost or destroyed after leaving the economic territory of the exporting country but before entering the economic territory of the destined importing country are not to be included in the import statistics of the destined importing country. importing country (but included in the export statistics of the exporting country).

5. Goods to support the activities of domestic organizations abroad.

6. Goods transported by pipeline transport, necessary for its commissioning.

7. Goods (supplies) to ensure normal operation and Maintenance vehicles engaged in international transportation, intended for consumption by passengers and crew members, as well as intended for sale to passengers and crew members of ships and aircraft.

8. Items of material and technical supply and equipment, fuel, food and other property necessary for the normal operation of vehicles engaged in international transportation.

9. Marine products imported by domestic or leased (chartered) domestic ships.

10. Fuel and lubricants exported for bunkering of domestic vehicles or vessels leased (chartered) by domestic persons located outside the customs territory of the state.

11. Aircraft moving across the state border for maintenance purposes.

12. Goods moved across the border of the state for the purpose of repair.

13. Exhibition exhibits.

14. Goods moved for entertainment and sporting events.

15. Goods supplied against a deposit.

16. Goods samples.

17. "Transportation" container moved across the border.

18. Goods previously imported and placed under a different customs regime in the customs territory of the state, which were taken into account in the import of the state, when the customs regime is changed, are not re-recorded in the customs statistics of the state's foreign trade (without changing the direction of movement of goods).

The documentary basis for maintaining customs statistics is the information contained in the primary document - in Cargo customs declaration(GTE).

Moreover, for the purposes of customs statistics, only that information from the CCD is used that is not confidential, that is, it does not contain information about specific foreign trade operations and specific participants in foreign economic activity.

GTD appears to be a participant in foreign economic relations customs authority and includes officially declared data on goods transported across the customs border of the country, which makes it possible to take into account the entire set of foreign trade operations, each of which, from the point of view of customs control has its own final result: export of goods outside the customs territory of the country (when exporting) or importing them into the customs territory of the country (when importing).

The customs declaration is filled in for each consignment of goods. If there are several trade names in the lot, additional sheets are used, each of which makes it possible to declare goods of three more names.

There are three types of declarations: export, import and transit.

However, filling in all columns of the CCD (about 50) is carried out for the "Export" and "Import" modes, since all economic policy measures are applied to them and the most complete information is required for customs control in these cases.

AT declarations contain such information as the reporting period, the direction of the flow of goods (import or export), the country of origin (when importing), the country

destination (when exported), statistical value, code and name of goods according to TN VED5, net weight, code and name of additional units of measure, quantity by additional units of measure, type of customs regime, etc. Based on this information, information on external trade of the country, therefore, when filling out the CCD, uniform accounting methods are used, as well as generally accepted international or local classifiers and nomenclatures. Based on the data contained in the GTD, it is possible to analyze the geographical and nomenclature distribution of the country's foreign trade.

AT the corresponding columns of the customs declaration contain the characteristics of the goods: description of the goods, weight, cost, etc. In particular, the name of the goods and their specifications, including model numbers, types, sizes, technical specifications etc., which makes it possible to unambiguously classify the declared goods into a certain 9-digit subheading of the TN VED. Correct coding of goods is an important condition for improving the reliability of the data of the customs statistics of the country's foreign trade.

Topic 3. Statistical quantities

As already mentioned, the subject of statistics is aggregates(mass phenomena). Units of the population have certain properties, which are usually called signs.

5 Commodity nomenclature of foreign economic activity - see topic 4 for more details

Signs differ in the way they are measured and in other features, which gives rise to their classification 2.

Table 2. Main classification of features in statistics

To characterize mass phenomena, statistics uses

statistical values ​​(indicators), which characterize groups of units or an aggregate (phenomenon) as a whole. Statistical quantities (indicators)

subdivided into absolute, relative and average.

The results of observations of customs statistics of foreign trade, that is, information obtained from the CCD, are absolute values, reflecting the level of development of a phenomenon (for example, the value of exports/imports of the i-th product to the j-th country). Absolute values ​​are denoted X , and their total number in the statistical population N .

Absolute values ​​are momentary (reflect the level of development of the phenomenon on a certain date, for example, the export price of oil) and interval (reflect the level of development of the phenomenon for a certain period of time, for example, the value of exports per month, quarter, year, etc.). Unlike instantaneous interval absolute values, they allow subsequent summation (for example, summing up the value of exports of goods for January, February and March, we obtain the value of exports for the first quarter).

Absolute values ​​always have their own unit of measurement (dimension) inherent in the phenomenon under study (in customs statistics - a product). The following are widely used in customs statistics. types of units:

1) natural, subdivided into simple (for example, pieces, tons, meters) and complex (composite), which are a combination of two opposite quantities (for example, kilowatt-hour);

2) conditionally natural(for example, alcoholic beverages are counted in the dcl of 100% alcohol, and different kinds fuel is measured by standard fuel with calorific value 7000 kcal/kg or 29.3 MJ/kg);

3) value, allowing to measure in monetary terms goods that cannot be measured in kind (US dollars, rubles, etc.).

The number of units with the same feature value is denoted by f and is called the frequency 6 . Obviously, summing up the number of all values ​​with the same values ​​of the attribute7, we get N , that is, (1):

Analyzing absolute values, for example, statistical data on the foreign trade of the Russian Federation, it is necessary to compare these data in time and space, investigate the patterns of their change and development, and study the structure of aggregates. With the help of absolute values, these tasks are not feasible, in this case it is necessary to use relative values.

Relative value is the result of dividing (comparing) two absolute values. The numerator of the fraction is the value being compared, and the denominator is the value being compared with (the base of comparison). For example, if we compare the exports of the United States and Russia, which in 2005 amounted to 904.383 and 243.569 billion dollars, respectively, then the relative value will show that the value of US exports is 3.71 times (904.383 / 243.569) more than Russian exports, while the base comparison is the value of Russia's exports. The resulting relative value is expressed as a video coefficient, which shows how many times the compared absolute value is greater than the base value. In this example, the comparison base is taken as one. If the base is taken as 100, the relative value is expressed as a percentage (%), if as 1000 - per mille (‰). The choice of one form or another of the relative value depends on its absolute value:

– if the compared value is more than the base of comparison by 2 times or more, then choose the form of the coefficient (as in the above example);

– if the relative value is close to one, then, as a rule, it is expressed as a percentage (for example, comparing the values ​​of Russia's exports in 2006 and 2005, which amounted to 304.5 and 2006 is 125% of 2005);

– if the relative value is significantly less than one (close to zero), it is expressed in ppm (for example, in 2004 Russia exported a total of 4142 thousand tons of oil products to the CIS countries, including 10.7 thousand tons to Georgia, which is 0.0026 , or 2.6‰ of all exports of petroleum products to the CIS countries).

There are relative values ​​of dynamics, structure, coordination, comparison and intensity, for brevity, hereinafter referred to as indices.

The index of dynamics 8 characterizes the change of any phenomenon in time. It is the ratio of the values ​​of the same absolute value in different periods of time. This index is determined by formula (2):

6 f is the initial letter of the English. wordsfrequency - frequency

7 In statistics, unlike mathematics, summation limits are not set, but implied, since the absolute values ​​here are not abstract, but semantic (all values ​​of the population are summed up - from the first to the last)

1. The subject of statistics.

statistics call systematic and systematic accounting carried out nationwide by state statistics bodies headed by state committee RF according to statistics.

Statistics - digital data published in special reference books and mass media.

Statistics - a special scientific discipline.

The subject and content of statistical science.

The subject and content of statistical science have been debatable for a long time. In order to resolve these issues in 1954 and 1968. special meetings were held with the involvement of a wide range of scientists and practitioners, not only statisticians, but also specialists related to science. In addition, until the mid-1970s there was a discussion about the subject of statistics in the specialized literature. During the discussions, it emerged 3 main points of view on the subject of statistics:

1. Statistics - a universal science that studies the mass phenomenon of nature and society.

2. Statistics - a methodological science that does not have its own subject of knowledge, but is a doctrine of the method used by the social sciences.

3. Statistics - social science, which has its own subject, methodology and explores the quantitative patterns of social development.

As a result of the meetings and discussions held in statistical science, the first two points of view were rejected by the majority of scientists and practitioners, and the third one was basically accepted, supplemented and clarified.

The subject of statistics is the quantitative side of mass socio-economic phenomena, inextricable links with their qualitative side, specific conditions, place and time. From this definition it follows main features of the subject of statistical science:

1. Statistics - social science.

2. Unlike other social sciences statistics studies the quantitative side of social phenomena.

3. Statistics studies a mass phenomenon.

4. Statistics studies the quantitative side of phenomena in inseparable connection with the quantitative side, and this is embodied in the existence of a system of statistical indicators.

5. Statistics studies the quantitative side of phenomena in specific conditions of place and time.

2. Features of statistical methodology. statistics method.

Statistical methodology is understood as a system of principles and methods for their implementation aimed at studying quantitative patterns that manifest themselves in the structure of relationships and the dynamics of socio-economic phenomena. The most important constituent elements methods of statistics and statistical methodology are mass statistical observation, summary and grouping, as well as the use of generalizing statistical indicators and their analysis.

Essence of the first element of statistical methodology is the collection of primary data about the object under study. For example: in the course of the country's population census, data is collected on each person living in its territory, which is entered in a special form.

Second element: summary and grouping represents the division of the data set obtained at the observation stage into homogeneous groups one or more signs. for example as a result of the grouping of census materials, the population is divided into groups (by sex, age, population, education, etc.).

The essence of the third element of statistical methodology lies in the calculation and socio-economic interpretation of generalizing statistical indicators:

1. Absolute

2. Relative

3. Medium

4. Indicators of variation

5. Speakers

The three main elements of statistical methodology also constitute the three stages of any statistical study.

3. Theoretical basis statistics.

The theoretical basis of statistics is formed by concepts and categories, in the aggregate of which the basic principles of this science are expressed. In statistics, the most important categories and concepts include: totality, variation, sign, regularity.

Population - this is a set (mass) of the same quality (homogeneous) at least one of any sign of phenomena, the existence of which is limited in space and time. The statistical totality can be considered, for example, the population of Russia as of January 1, 1997, the population farms Rostov region in 1997. However, the statistical population (set) does not necessarily represent a large number of units, in principle it can be very small; for example, the population size of a small sample may sometimes be 8-10 units.

The most important property of the statistical population is her indecomposability. This means that further fragmentation of individual phenomena does not cause the loss of their qualitative basis. The disappearance or elimination of one or a number of phenomena does not destroy the qualitative basis of the statistical population as a whole. Thus, the population of a country or a city will remain a population, despite the ongoing processes of mechanical and natural population movement.

Quantitative changes in the value of a feature in the transition from one unit of the population to another are called variation. Variation occurs under the influence of random, primarily external causes.

Statistical populations have certain properties, the carriers of which are units (individual elements) of the population (phenomena) that have certain characteristics. According to the form of external expression, signs are divided into:

Attributive (descriptive)

quantitative

Attributive (qualitative) signs are not amenable to direct quantitative (numerical) expression.

quantitative signs are divided into discrete (discontinuous) and continuous.

The most important category of statistics is a statistical regularity. Under pattern in general, it is customary to call the repetition, sequence and order of changes in phenomena.

Statistical same regularity in statistics it is considered as a quantitative pattern of changes in space and time of mass phenomena and processes of social life, consisting of many elements (units of the totality). It is characteristic not of individual units of the population, but of their entire mass, or of the population as a whole.

statistical regularity is a form of expression causation, expressed in the sequence, regularity, recurrence of events with a sufficiently high degree of probability, if the causes (conditions) that generate the events. Do not change or change slightly. Statistical patterns are established based on the analysis of mass data.

4. Basic concepts and categories of statistical science in general.

6. General theory statistics as a branch of statistical science.

Population - a set of elements of the same type similar to each other in some respects and differing in others. For example: this is a set of sectors of the economy, a set of universities, a set of cooperation between design bureaus, etc.

Individual elements of a statistical population are called its units. In the examples discussed above, the units of the population are, respectively, the industry, the university (one) and the employee.

Units of the population usually have many features.

sign - property of units of the population, expressing their essence and having the ability to vary, i.e. change. Signs that take a single value in individual units of the population are called varying, and the values ​​themselves are options.

Variable signs are subdivided into attributive or qualitative ones. An attribute is called attributive or qualitative if its separate value (variants) are expressed as a state or properties inherent in the phenomenon. Variants of attributive features are expressed in verbal form. Examples of such signs can serve - economic.

An attribute is called quantitative if its individual value is expressed in the form of numbers. For example: wage, scholarship, age, size of OF.

According to the nature of variation, quantitative signs are divided into discrete and continuous.

Discrete - such quantitative signs that can only take on a well-defined, as a rule, integer value.

continuous - are such signs that, within certain limits, can take on the value of both integer and fractional. For example: GNP of the country, etc.

There are also primary and secondary features.

Main signs characterize the main content and essence of the phenomenon or process being studied.

Minor signs give Additional information and are directly related to the inner content of the phenomenon.

Depending on the goals of a particular study, the same signs in the same cases may be primary, and in others secondary.

statistic - This is a category that reflects the dimensions and quantitative ratios of the signs of socio-economic phenomena and their qualitative certainty in specific conditions of place and time. It is necessary to distinguish between the content of a statistical indicator and its specific numerical expression. Content, i.e. qualitative certainty lies in the fact that the indicators always characterize the social economic categories(population, economy, financial institutions, etc.). Quantitative dimensions of statistical indicators, i.e. their numerical values ​​depend primarily on the time and place of the object that is subjected to statistical research.

Socio-economic phenomena, as a rule, cannot be characterized by any one indicator, For example: the standard of living of the population. A scientifically substantiated system of statistical indicators is necessary for a comprehensive comprehensive characterization of the phenomena under study. Such a system is not permanent. It is constantly being improved based on the needs of social development.

5. Branches of statistical science.

In the process of historical development, as part of statistics as a single science, the following branches emerged and gained a certain independence:

1. The general theory of statistics, which develops the concept of categories and methods for measuring the quantitative patterns of social life.

2. Economic statistics studying the quantitative patterns of reproduction processes at various levels.

3. social statistics, which studies the quantitative side of the development of the social infrastructure of society (statistics of health care, education, culture, moral, judicial, etc.).

4. Industry statistics (statistics of industry, agro-industrial complex, transport, communications, etc.).

All branches of statistics, developing and improving their methodology, contribute to the development of statistical science as a whole.

7. Main tasks and principles of organization of state statistics in Russia.

The main tasks of statistics in the context of the development of market relations in Russia are the following:

1. Improving accounting and reporting and reducing the document flow on this basis.

2. Strengthening work to control the reliability of statistical information provided to enterprises, institutions and organizations of all sectors of the economy and forms of ownership.

3. Improving the timeliness of statistical information both to the incoming statistical agency and the structures provided by them state power and management.

4. Deepening the analytical functions, developing statistical data, forming the topics of statistical data being carried out in accordance with the current tasks of the socio-economic development of the country.

5. Further development and improvement of statistical methodology based on the increasingly widespread introduction of PC practice and ... statistical analysis was not predicted.

8. The concept of statistical observation, the stages of its implementation.

9. Basic forms and types of statistical observation.

Statistical observation - this is a mass, systematic, scientifically organized observation of the phenomena of social and economic life, which consists in registering selected features for each unit of the population.

An example of statistical observation is public opinion polls, which have become especially popular in Russia in recent years. Such observation is taken for the purpose of revealing people's attitudes towards some issue of interest or controversial events. The study of public opinion forms the basis of the general system of market research and is an important part of it. Such observation requires interviewing a number of individuals according to a predetermined program.

Statistical observation can be carried out by state statistics bodies, research institutes, economic services of banks, stock exchanges, firms.

The process of statistical observation includes the following stages:

Observation preparation

Conducting mass data collection

Preparing data for automated processing

Development of proposals for improving statistical observation

Any statistical observation requires careful, thoughtful preparation. The reliability and reliability of information, the timeliness of its receipt will largely depend on it.

The preparation of a statistical observation is a process that includes different types works. First, it is necessary to solve methodological issues, the most important of which are the definition of the purpose and object of observation, the composition of features to be registered; development of documents for data collection; the choice of the reporting unit and the unit to be observed, as well as the methods and means of obtaining data.

In addition to methodological problems, it is necessary to solve organizational problems, for example, to determine the composition of the monitoring bodies; select personnel for observation; compose calendar plan work on the preparation, conduct and processing of observation materials; replicate documents for data collection.

Carrying out mass data collection includes work directly related to filling in statistical forms. It begins with the distribution of census questionnaires, questionnaires, forms, forms statistical reporting and ends with their delivery after filling in the bodies conducting monitoring.

The collected data at the stage of their preparation for automated processing are subject to arithmetic and logical control. Both of these controls are based on knowledge of the relationship between indicators and qualitative features.

At the final stage of the observation, the reasons that led to the incorrect completion of statistical forms are analyzed, and proposals are developed to improve the observation. This is very important for organizing future surveys.

Obtaining information in the course of statistical observation requires considerable financial and labor resources, as well as time.

10. Program and methodological issues of statistical observation.

Purpose of observation. Statistical observations most often pursue a practical goal - obtaining reliable information to identify patterns in the development of phenomena and processes. for example, the purpose of the micro-census of the population of Russia in 1994. There was a receipt of data on the size, composition of the population, living conditions.

Observation task predetermines its program and forms of organization. An unclear goal can lead to the fact that during the observation process unnecessary data will be collected or, conversely, the information necessary for analysis will not be obtained.

Object and unit of observation. Reporting unit. When preparing an observation, in addition to the goal, it is necessary to determine exactly what exactly is to be examined, i.e. set the object of observation.

Under object of observation refers to a certain statistical totality in which the studied socio-economic phenomena and processes take place. For example, a set of individuals, individuals, legal entities.

Unit of observation called constituent element an object that is a carrier of features subject to registration.

reporting unit is the object from which the data about the unit of observation are received.

Statistical Surveillance Program. Every phenomenon has many different features. Collecting information on all grounds is impractical, and often impossible. Therefore, it is necessary to select those features that are essential for characterizing the object based on the purpose of the study. To determine the composition of the registered features, an observation program is developed.

Observation program- this is a list of signs (or questions) to be recorded in the process of observation. The quality of the collected information largely depends on how well the program of statistical observation is developed.

Place and time of observation. The choice of the survey site depends mainly on the purpose of the survey.

11. Organizational matters statistical observation.

The success of any statistical observation depends not only on the thoroughness of methodological preparation, but also on the correct and timely solution of a wide range of organizational issues.

The most important place in organizational work is occupied by personnel training, during which various kinds of briefings are held with employees of statistical bodies, with organizations that provide data on filling in statistical documents, preparing observation materials for automated processing, etc.

If the observation is associated with large labor costs, then persons from among the unemployed (including the unemployed) and certain categories of students are involved in registering information during the period of the survey. When conducting a census, such persons are called enumerators. Training of temporary staff is usually organized. It is carried out to develop skills for the correct filling of statistical forms by enumerators.

Reproduction of the documentation of the survey itself, documentation for briefings and their distribution to the republican, regional, regional committees and departments of statistics also relate to organizational issues.

During the preparation period, a large role is given to mass explanatory work: conducting lectures, conversations, organizing speeches in the press, on radio and television about the meaning, goals and objectives of the upcoming survey.

To harmonize the activities of all services involved in the preparation and conduct of the observation, it is advisable to draw up a calendar plan, which is a list (name) of work and the timing of their execution separately for each organization involved in the survey.

12. Types of non-continuous statistical observation.

discontinuous observation is deliberately oriented towards taking into account some, as a rule, quite a mass part of the units of observation, which, nevertheless, makes it possible to obtain stable generalizing characteristics of the entire statistical population. In statistical practice, different types of non-continuous observation: selective, the method of the main array, questionnaire and monographic. The quality of non-continuous observation is inferior to the results of continuous observation, however, some advantages of the first one are quite obvious: gain in time for making an operational decision, as well as compliance with the resource saving mode. In a number of cases, statistical observation generally turns out to be possible only as a non-continuous one.

For is used to obtain a representative characteristic of the entire population for some part of its units, selective observation is used. In industry, selective observation is used in the statistical control of product quality, the study of the use of production equipment, the workplace of machine operators, etc.

According to the method of the main array, the largest, most significant units of the population are selected, which prevail in their total mass according to the trait under study. According to the principle of the main array in Russia, the statistics of urban market trade is carried out. The number of cities covered by it is less than 5% of all cities, but they are home to more than half of the total urban population of the country.

A monographic description is a detailed examination of a separate, but very typical object, which also determines interest from the point of view of studying the entire population. A monographic study can be aimed at studying best practices or, on the contrary, shortcomings in the work of enterprises. The object of a monographic description can also be a family, a production team, a school, a higher educational institution, medical institution, city, region and other objects.

13. Accuracy of statistical observation. Control of statistical observation materials.

Statistical Observation Accuracy- the degree of conformity of the value of any indicator (the value of some attribute), determined by the materials of statistical observation, to its actual value.

The discrepancy between the calculated and actual values ​​of the studied quantities is called the observation error.

Data Accuracy This is the main requirement for statistical observation. To avoid observation errors, to prevent, identify and correct them, it is necessary to:

Ensure quality training of personnel who will conduct surveillance

Organize special partial or complete control checks on the correctness of filling in statistical forms

Carry out logical and arithmetic control of the received data of the end of information collection

Depending on the causes of occurrence, registration errors and representativeness errors are distinguished.

Registration errors- these are deviations between the value of the indicator obtained in the course of statistical observation and its actual, actual value. This type of error can occur in both continuous and non-continuous observations.

Random bugs- this is the result of the action of various random factors (for example, numbers are rearranged, adjacent lines or columns are mixed up when filling out a statistical form). Such errors have different directions: they can both increase and decrease the values ​​of indicators. With a sufficiently large surveyed population, as a result of the law of large numbers, these errors cancel each other out.

Systematic registration errors always have the same tendency to either increase or decrease the value of indicators for each unit of observation, and therefore the value of the indicator for the population as a whole will include the accumulated error. For example, when conducting sociological surveys of the population, rounding off the age of the population, as a rule, on numbers ending in 5 and 0, can serve.

14. The essence and significance of statistical groupings, their types.

Groupings are still a method of researching socio-economic phenomena, in which the statistical population is divided into homogeneous groups that reveal the state and development of the entire population.

Grouping is the most important stage of statistical research, combining the collection of primary information about the scope of the study and the analysis of this information on the basis of generalizing statistical indicators.

Grouping methods are varied. This diversity is due, on the one hand, to a huge variety of features subjected to statistical research, and, on the other hand, to a variety of tasks that are solved on the basis of groupings.

Depending on the tasks solved with the help of groupings, the following types are distinguished:

typological groups.

For example:

structural groupings.

A grouping is called structural, in which a homogeneous population is divided into groups that characterize its structure according to some varying feature. For example: composition of the population by sex, age, place of residence; the composition of enterprises by the number of employees, the cost of fixed assets; the structure of deposits by the term of their attraction, etc.

analytical groupings.

The phenomena of social life and the features that reflect them are closely interrelated. Analytical- grouping, revealing the relationship between the studied phenomena and their features. Analytical groupings allow you to study the variety of relationships and dependencies between varying features.

The whole set of signs can be divided into two groups: factorial and effective. Factor signs are called signs, under the influence of which other signs change - they form a group of effective signs. The relationship is manifested in the fact that with an increase in the value of the factor attribute, the average value of the indicator of the effective one systematically increases or decreases. For example: labor productivity depends on the technical level of the enterprise: the higher it is, the other equal conditions higher productivity of employees in the enterprise.

A grouping in which groups are formed on the same basis is called simple. To characterize a phenomenon, it is not enough to divide the population into groups according to some homogeneous feature. In this case, complex groupings are built.

complex called grouping, in which the division of the population into groups is carried out according to two or more features taken in combination (combination).

15. The main problems arising in the construction of groups.

The most important problem in building a grouping is the choice of a grouped feature or the basis of the grouping.

Grouping sign - a variable sign by which the units of the population are combined into groups.

According to the nature of variation, signs are divided, as is known, into: attributive and quantitative. This division determines the features of solving the second problem of groupings, namely, the determination of the number of allocated groups. When choosing some attributive features as grouping features, only a strictly defined number of groups can be distinguished. In particular, when grouping the population by sex, it can be distinguished ...

When grouping enterprises by profit, 3 groups can be distinguished.

For many attributive features, stable groupings are developed, called classifications. For example: classification of sectors of the economy, classification of occupations of the population, etc.

When grouping on a quantitative basis, the question of the number of group boundaries should be decided based on the essence of the socio-economic phenomenon under study. In this case, one should take into account such an indicator as the range of variations. The greater the range of variation, the more groups are formed and vice versa. It is also necessary to take into account the number of units of the population on which the grouping is built. With a small volume of the population, it is not advisable to form a large number of groups, because in this case, the groups will not have a sufficient number of units to identify statistical patterns.

An essential issue in grouping by quantitative characteristics is the definition of intervals. The indicators of the number of groups and the size of the intervals are inversely related. The larger the intervals, the fewer groups are required and vice versa.

An interval is the difference between its upper and lower bounds.

According to the size of the grouping attribute, the intervals are divided into equal and unequal. Equal intervals are used in cases where the change in the grouping attribute within the population occurs evenly. The calculation of the value of an equal interval is carried out according to the formula:

k - number of groups

Xmax, Xmin - respectively, the largest and smallest value of the attribute to the quality of the groups.

If the distribution of the grouping attribute within the population is uneven, then unequal intervals are used. Unequal intervals can be progressively increasing and progressively decreasing. often when grouping, so-called specialized intervals are used, i.e. those that are determined based on the purpose of the study and the essence of the phenomenon. For example: when grouping with the aim of characterizing the able-bodied population of the country, five-year intervals of the age of people are used.

The third problem of constructing groupings is the designation of interval boundaries. When selecting intervals according to discrete quantitative characteristics, their boundaries should be designated so that the lower limit of the next interval differs from the upper limit of the previous one by one.

When grouping on a continuous quantitative basis, the boundaries are marked so that the groups are clearly separated from one another. This is achieved by adding to the numerical boundaries of the intervals indications of where to refer the unit that has a grouping feature in sizes that exactly coincide with the boundaries of the intervals. Usually, additional explanations for the numerical boundaries of intervals formed according to continuous quantitative principles are expressed in the words: “more”, “less”, “over”, etc.

16. Typological groupings.

17. Structural groupings.

18. Analytical groupings.

typological groups.

The main task of the typological one is to classify socio-economic phenomena by identifying groups that are homogeneous in terms of qualitative relations. For example: grouping enterprises of economic sectors.

Typological groupings are widely used in the study of socio-economic phenomena and processes. They allow us to trace the origin, development and death of various types of phenomena.

When conducting a typological grouping, the main attention should be paid to identifying the types of socio-economic phenomena. It is based on a deep theoretical analysis of the phenomenon under study.

structural groupings.

A grouping is called structural, in which a homogeneous population is divided into groups that characterize its structure according to some varying feature. For example: composition of the population by sex, age, place of residence; the composition of enterprises by the number of employees, the cost of fixed assets; the structure of deposits by the term of their attraction, etc.

Changes in the structure of social phenomena reflect the most important patterns of their development.

analytical groupings.

The phenomena of social life and the features that reflect them are closely interrelated. Analytical - a grouping that reveals the relationship between the studied phenomena and their features. Analytical groupings allow you to study the variety of relationships and dependencies between varying features.

The whole set of signs can be divided into two groups: factorial and effective. Factor signs are called signs, under the influence of which other signs change - they form a group of effective signs. The relationship is manifested in the fact that with an increase in the value of the factor attribute, the average value of the resultant attribute systematically increases or decreases. For example: labor productivity depends on the technical level of the enterprise: the higher it is, the higher, other things being equal, the labor productivity of those employed in the enterprise.

A grouping in which groups are formed according to one attribute is called simple. To characterize a phenomenon, it is not enough to divide the population into groups according to some homogeneous feature. In this case, complex groupings are built.

A grouping is called complex, in which the population is divided into groups according to two or more features taken in combination (combination).

19. Building groupings on a quantitative basis.

The question of the number of groups, and, consequently, of the grouping intervals, is solved differently in typological groupings and in the selection of groups within types. Studying the quantitative side of mass social phenomena, statistics, relying on specific provisions economic theory, must, in the process of grouping, outline the points of transition from quantity to a new quality; based on the analysis of quantitative changes in grouping characteristics, identify points of transition from one quality to another. In typological grouping, the intervals should be marked in such a way that they delimit the socio-economic types established on the basis of economic theory.

The theoretical and economic analysis of the phenomenon under study should be a prerequisite for scientific statistical grouping, but at the same time, the use of the apparatus of modern statistical methods makes it possible to assess the degree of homogeneity of the selected groups, to select essential grouping features, and to improve the methodology for determining the size of the grouping intervals. The number of selected groups may also depend on the nature of the variation of the indicator under study. If a discrete feature is used as a grouping feature, i.e. a feature that can take only some specific values ​​(for example, integers), then the number of distinguished groups corresponds to the number of options for the value of the feature, if their number is not very large. for example, the distribution of workers of the enterprise according to tariff categories, grouping families by size, etc.

20. Secondary grouping.

When analyzing heterogeneous data, for example, when analyzing material collected in different periods of time related to various industries national economy, there is a need to use a secondary grouping. In addition, the secondary grouping method is also used to show the intensity of processes and phenomena under various conditions, for example, when it is necessary to show the degree of enlargement of collective farms in different regions, and the initial data are presented by different groupings.

As grouping characteristics, the size of the sown area, the number of livestock, the number of horses, etc. can be used.

21. Rows of distribution. Their graphic representation.

Statistical distribution series - this is an ordered distribution of population units into groups according to a certain varying attribute.

Depending on the signs underlying the formation of a distribution series, attributive and variation distribution series are distinguished.

Attributive called distribution series, built on qualitative grounds. It is customary to arrange the distribution series in the form of tables. For example, an attribute series of the distribution of assistance to citizens by lawyers. Lawyers can be distributed, for example, according to types and forms of legal assistance.

Attribute distribution series characterize the composition of the population according to one or another essential feature. Taken over several periods, these data will allow us to study the change in the structure.

Variational distribution series are called, built on a quantitative basis. Any variational series consists of elements: variants and frequencies.

Variants are individual values ​​of a feature that it takes in a variation series, i.e. specific value of the variable attribute.

Frequencies are the numbers of individual variants or each group of the variation series, i.e. these are numbers showing how often certain options occur in a distribution series. The sum of all frequencies determines the size of the entire population, its volume.

22. Absolute and relative values.

24. Types of statistical relative values.

An absolute value is an indicator that expresses the dimensions of a socio-economic phenomenon.

A relative value in statistics is an indicator that expresses the quantitative relationship between phenomena. It is obtained by dividing one absolute value by another absolute value. The value with which we compare is called basis or base of comparison .

Absolute values are always named values.

Relative values ​​are expressed in coefficients, percentages, ppm, etc.

Relative value shows how many times, or how many percent the compared value is more or less than the comparison base.

In statistics, there are 8 types of relative values:

1. The relative value of the implementation of the plan (OVVP) shows how many times or by how many percent this task has been completed.

OVDP = actual data of the reporting period

planned data of the reporting period

2. The relative value of the planned target (OVPZ) shows how many times or how many percent the planned target of the reporting period is more or less than the level of the base period.

OVPV = planned number of the reporting period

3. The relative value of the dynamics (AR) shows how many times or how many percent the level of the reporting period is more or less than the level of the base period.

ATS = actual reporting period data

actual base period data

4. The relative value of comparison (RBC) shows how many times or how many percent the phenomenon in territory A is greater or less than the phenomenon in territory B.

EVav.= actual the level of the phenomenon in territory A for a certain period of time

actual the level of the same phenomenon for the same period of time in territory B

5. Relative intensity value (RVI). Fertility rate, etc., the number of people born in a certain area in a certain period of time.

JVI = actual the level of the phenomenon for opred. time period

the size of the environment in which this phenomenon developed

6. Relative Coordination Value (RVR) is calculated only for grouped data and shows the relationship between parts of the population.

HVAC = number of units of a particular group

the number of units of the group taken as the base of comparison

7. Relative value of the structure (RBC).

OVst.= part of the population

the totality

8. Relative level value economic development(OVUER)

OVWER= annual output

average annual population population

23. Units of measurement of absolute and relative indicators.

Absolute indicators.

AT international practice such natural units of measurement like tons, kilograms, ounces, square, cubic and simple meters, miles, kilometers, gallons, liters, pieces, etc.

In conditions market economy of greatest importance and application are value units, giving a monetary assessment of socio-economic phenomena and processes, such as GNP.

To labor units, allowing to take into account both the total labor costs at the enterprise, and the labor intensity of individual operations technological process, include man-days and man-hours.

Relative indicators.

Relative indicators can be expressed in coefficients, percentages, ppm, decimilles, or named numbers. If the comparison base is taken as 100, 1000 or 10,000, then the relative indicator is expressed as a percentage (%), ppm (‰) and decimille (‰).

26. Statistical tables. Their types.

In the practice of economic and statistical analysis, various types of statistical tables are used, which differ in the number and nature of the aggregates, in the different structure of the subject and predicate, in the structure and ratio of the features that form them.

Depending on the structure of the subject and the grouping of units in it, simple and complex statistical tables are distinguished, and the latter, in turn, are divided into group and combination tables.

In a simple table, the subject gives a simple list of any objects or territorial units, i.e. there is no grouping of aggregate units in the subject. Simple tables are monographic and list. Monographic tables do not characterize the entire set of units of the object under study, but only one group from it, singled out according to a certain, pre-formed feature.

Thus, simple list tables are called tables, the subject of which contains a list of units of the object under study.

Group tables are called statistical tables, the subject of which contains a grouping of population units according to one quantitative or attributive attribute. The predicate in group tables consists of the number of indicators necessary to characterize the subject.

The simplest type of group tables are attribute and variation distribution series. The group table can be more complex if the predicate contains not only the number of units in each group, but also a number of other important indicators that quantitatively and qualitatively characterize the subject groups. Such tables are often used to summarize indicators for groups, which allows us to draw certain practical conclusions.

Thus, group tables make it possible to identify and characterize the socio-economic types of phenomena, their structure, depending on only one attribute.

Combination tables are called statistical tables, the subject of which contains a grouping of population units simultaneously according to two or more characteristics: each of the groups, built on one basis, is divided, in turn, into subgroups according to some other attribute, etc.

Combination tables make it possible to characterize typical groups identified according to several characteristics, and the relationship between the latter. The sequence of splitting units of the population into homogeneous groups according to features is determined either by the importance of one of them in their combination, or by the order of their emission.

28. Development of a predicate statistical table.

In the predicate of the statistical table, indicators are given that are a characteristic of the object under study.

According to the structural structure of the predicate, statistical tables are distinguished with a simple and complex development.

With a simple development of the predicate, the indicator that defines it is not divided into subgroups, and the final values ​​are obtained by simply summing the values ​​for each feature separately, independently of each other.

After filling in this fragment of the table, a detailed description of the privatized enterprises is obtained according to the structure of their owners. For each company, you can get information on the number and price conditions for the sale of shares.

Complex predicate development involves the division of the feature that forms it into subgroups.

With a complex development of the predicate, a more complete and detailed description of the object is obtained.

The combined development of indicators on the conditions for the sale of shares and their types makes it possible to deepen the economic and statistical analysis of the share market and its structure by privatized enterprises.

Here, both predicates (price and species) are closely related to each other. It is possible to analyze not only the number of purchased shares by types and conditions, but also to determine the number of preferred and ordinary shares purchased under different price conditions. So, with a complex development of the predicate, each group of enterprises or each enterprise individually can be characterized by a different combination of features that form the predicate.

30. Tables of contingency.

A contingency table is a table that contains a summary numerical characteristic of the studied population for two or more attributive (qualitative) features or a combination of quantitative and attributive features.

Contingency tables are most widely used in the study of social phenomena and processes: public opinion, the level and way of life, the socio-political system, etc.

Most simple view The contingency table is a 2x2 frequency table.

The construction of this table is based on the assumption that the answers of the respondents or the analyzed attributes will take only two values ​​A1 and A2, B1 and B2. The internal digital content of the table is represented by frequencies (fij) that simultaneously have the i-th (i=1.2) value of one (Ai) and the j-th (j=1.2) value (Bj) of another quality attribute.

The final column and line contain information about the quantitative distribution of the population, respectively, according to A and B attributes.

For a more complete description and analysis of phenomena and processes characterized by attributive features, contingency tables of a higher dimension are used: ixj, where i=1,2,...,k is the number of value options (for example, answers of respondents, etc.) of one feature (for example, feature A); j=1,2,...,n - the number of options for the values ​​of another attribute (B).

The principle of mutual contingency is most effective in identifying and evaluating the relationships and interdependencies between social phenomena and processes.

31. Reading and analysis of the statistical table.

The analysis of statistical tables is preceded by the stage of familiarization - their reading.

Reading and analysis of the table should not be carried out randomly, but in a certain sequence.

Reading assumes that the researcher, having read the words and numbers of the table, assimilated its content, formulated the first judgments about the object, understood the purpose of the table, understood its content as a whole, and assessed the phenomenon or process described in the table.

Table analysis as a method of scientific research by dividing the subject of study into parts is divided into structural and meaningful.

Structural analysis involves the analysis of the structure of the table, the characteristics presented in the table:

The totality and units of observation that form it

Signs and their combinations that form the subject and predicate of the table

Signs: quantitative and attributive

Correlations of the signs of the subject with the indicators of the predicate

Table type: simple or complex, and the latter - group or combination

Solved problems - analysis of the structure, types of phenomena or their relationships

Content analysis involves the study of the internal content of the table: analysis of individual groups of the subject according to the corresponding features of the predicate; identification of correlations and proportions between groups of phenomena according to one and different characteristics; comparative analysis and formulation of conclusions for individual groups and for the entire population as a whole; establishing patterns and determining the reserves for the development of the object under study.

A logical check consists in the possibility of determining specific features by one or another numerical value (for example, it is absurd if the number of employees in the company was 106.7 people).

A counting check involves the selective calculation of individual characteristic values ​​for a group, or the total values ​​of rows or columns, etc.

Analysis of group and combination tables to characterize the types of socio-economic phenomena, the structure of the population, relationships and proportions between individual groups and units of observation.

32. Statistical chart. Its elements and rules of construction.

Statistical Graph - this is a drawing in which statistical aggregates characterized by certain indicators are described using conditional geometric images or signs. The presentation of table data in the form of a graph makes a stronger impression than numbers, allows you to better understand the results of statistical observation, interpret them correctly, greatly facilitates the understanding of statistical material, makes it visual and accessible. This, however, does not at all mean that the graphs have only an illustrative meaning. They provide new knowledge about the subject of research, being a method of generalizing the initial information.

When constructing a graphic image, a number of requirements must be observed. First of all, the graph should be quite visual, since the whole point of the graphic image is to visually depict statistical indicators. In addition, the schedule should be expressive, intelligible and understandable. To fulfill the above requirements, each graph must include a number of basic elements: a graphic image; graph field; spatial landmarks; scale landmarks; chart explication.

Graphic image are geometric signs, i.e. a set of points, lines, figures, with the help of which statistical indicators are depicted.

Chart field - this is the part of the plane where the graphic images are located. The graph field has certain dimensions, which depend on its purpose.

Spatial landmarks of the graph are set in the form of a system of coordinate grids. The coordinate system is necessary for placing geometric symbols in the graph field.

Scale landmarks of the statistical graph are determined by the scale and scale system. Statistical Graph Scale is a measure of converting a numerical value into a graphic one.

Scale bar a line is called, the individual points of which can be read as certain numbers. The scale is of great importance in graphics and includes three elements: a line (or scale carrier), a certain number of dots marked with dashes, which are located on the scale carrier in a certain order, a digital designation of numbers corresponding to individual marked points.

33. Classification of types of charts.

There are many types of graphics. Their classification is based on a number of features: a) a method of constructing a graphic image; b) geometric signs depicting statistical indicators; c) tasks solved with the help of a graphic image.

According to the method of construction, statistical graphs are divided into diagrams and statistical maps.

Diagrams - the most common way of graphic images. These are graphs of quantitative relations. The types and methods of their construction are varied. Diagrams are used for visual comparison in various aspects (spatial, temporal, etc.) of independent quantities: territories, population, etc. In this case, the comparison of the aggregates is carried out according to some significant varying attribute.

Statistical maps - plots of quantitative distribution over the surface. In their main purpose, they closely adjoin diagrams and are specific only in the sense that they are conditional representations of statistical data on a contour map, i.e. show the spatial distribution or spatial distribution of the statistical data. Geometric signs are either points, or lines or planes, or geometric bodies.

Averages are one of the most common summary statistics. They aim to characterize by one number a statistical population consisting of a minority of units. Averages are closely related to the law of large numbers. The essence of this dependence lies in the fact that, with a large number of observations, random deviations from the general statistics cancel each other out and, on average, a statistical regularity is more clearly manifested.

Using the method of averages, the following main tasks are solved:

1. Characteristics of the level of development of phenomena.

2. Comparison of two or more levels.

3. The study of the relationship of socio-economic phenomena.

1. 4. Analysis of the distribution of socio-economic phenomena in space.

To solve these problems, statistical methodology has developed various types of averages.

37. Types of averages.

The harmonic mean is the primitive form of the arithmetic mean. It is calculated in those cases when the weights fi are not given directly, but are included as a factor in one of the available indicators. As well as the arithmetic mean, the harmonic mean can be simple and weighted.

Average harmonic simple:

Average harmonic mixed:

Wi - product of variants by frequencies

When calculating average values, it must be remembered that any intermediate calculations should result both in the numerator and in the denominator and have economic sense indicators.

38. Arithmetic mean and its properties.

To clarify the methodology for calculating the arithmetic mean, we use the following notation:

X - arithmetic sign

X (X1, X2, ... X3) - variants of a certain feature

n - number of population units

The average value of the feature

Depending on the initial data, the arithmetic mean can be calculated in two ways:

1. If the statistical observation data are not grouped, or the grouped variants have the same frequencies, then the simple arithmetic mean is calculated:

2. If the frequencies are grouped in the data are different, then the weighted arithmetic mean is calculated:

Number (frequencies) of variants

Sum of frequencies

The arithmetic mean is calculated differently in discrete and interval variation series.

In discrete series, feature variants are multiplied by frequencies, these products are summed up, and the resulting sum of products is divided by the sum of frequencies.

In interval series, the value of a feature is given, as is known, in the form of intervals, therefore, before calculating the arithmetic mean, it is necessary to switch from an interval series to a discrete one.

As options for Xi, the middle of the corresponding intervals is used. They are defined as half the sum of the lower and upper bounds.

If the interval has no lower limit, then its middle is defined as the difference between the upper limit and half the value of the following intervals. In the absence of upper bounds, the middle of the interval is defined as the sum of the lower bound and half the value of the previous interval. After the transition to a discrete series, further calculations are carried out according to the method discussed above.

If a weight fi are given not in absolute terms, but in relative ones, then the formula for calculating the arithmetic mean will be as follows:

pi - relative values ​​of the structure, showing what percentage is the frequency of variants in the sum of all frequencies.

If the relative values ​​of the structure are given not in percentages, but in shares, then the arithmetic mean will be calculated by the formula:

39. Structural average.

40. Mode and median, their definition in variational series.

The structural average characterizes the composition of the statistical population according to one of the varying characteristics. These means are the mode and the median.

Fashion is the value of the variable that has the highest frequency in the given distribution series.

In discrete series of distributions, the mode is determined visually. First, the highest frequency is determined, and the modal value of the feature is determined from it. In interval series, the following formula is used to calculate the mode:

Xmo - the lower limit of the modality (interval of the series with the highest frequency)

Mo - interval value

fMo - modal interval frequency

fMo-1 - frequency of interval preceding modal

fMo+1 - frequency of the interval following the modal

median such value of a variable sign is called, which divides the distribution series into two equal parts according to the volume of frequencies. The median is calculated differently in discrete and interval series.

1. If the distribution series is discrete and consists of an even number of members, then the median is defined as the average of the two median values ​​of the ranked series of features.

2. If there is an odd number of levels in the discrete distribution series, then the median will be the middle value of the ranked series of features.

In interval series, the median is determined by the formula:

The lower bound of the median interval (the interval for which the accumulated frequency exceeds half the sum of frequencies for the first time)

Me - interval value

The sum of the frequencies of the series

The sum of the accumulated frequencies preceding the median interval

Median Interval Frequency

41. General concept of variation.

variation called the difference in the values ​​of the attribute in individual units of the population.

The variation arises due to the fact that the individual values ​​of the attribute are formed by the influence of a large number of interrelated factors. These factors often act in opposite directions, and their joint action forms the value of features in a particular unit of the population. The need to study variations is due to the fact that the average value, summarizing the data of statistical observation, does not show how the individual value of the trait fluctuates around it. Variations are inherent in the phenomena of nature and society. At the same time, the revolution in society is happening faster than similar changes in nature. Objectively, there are also variations in space and time.

Variations in space show the difference in statistical indicators related to various administrative-territorial units.

Variations in time show the difference in indicators depending on the period or point in time to which they refer.

42. The essence and significance of the indicators of variation.

43. Absolute indicators of variation (=42, no coefficient).

Examples of variations include the following indicators:

1. range of variations

2. average linear deviation

3. standard deviation

4. dispersion

5. ratio

1. Range of Variations is its simplest indicator. It is defined as the difference between the maximum and minimum value of the attribute. The disadvantage of this indicator is that it depends only on the two extreme values ​​of the attribute (min, max) and does not characterize the fluctuation within the population. R=Xmax-Xmin.

2. Average linear deviation is the average value of the absolute values ​​of the deviations from the arithmetic mean. Deviations are taken modulo, because otherwise, due to the mathematical properties of the mean, they would always be zero.

3. Standard deviation is defined as the root of the variance.

4. Dispersion(mean square of deviations) has the greatest use in statistics as an indicator of the measure of volatility.

The variance is a named indicator. It is measured in units corresponding to the square of the units of measurement of the trait under study.

5. Variation coefficient is defined as the ratio of the standard deviation to the average value of the feature, expressed as a percentage:

It characterizes the quantitative homogeneity of the statistical population. If this coefficient< 50%, то это говорит об однородности статистической совокупности. Если же совокупность не однородна, то любые статистические исследования можно проводить только внутри выделенных однородных групп.

44. Dispersion and its properties.

Dispersion - the average square of the deviations of the individual values ​​of the trait from their average value.

Dispersion properties:

1. The dispersion of a constant value is zero.

2. Reducing all values ​​of the attribute by the same value A does not change the value of the variance. This means that the average square of deviations can be calculated not from the given values ​​of the attribute, but from their deviations from some constant number.

3. Reducing all values ​​of the attribute by k times reduces the variance by k2 times, and the standard deviation - by k times. This means that all the values ​​of the attribute can be divided by some constant number (say, by the value of the interval of the series), calculate the standard deviation, and then multiply it by a constant number.

4. If we calculate the average square of deviations from any value A, then to some extent different from the arithmetic mean (X~), then it will always be greater than the average square of deviations calculated from the arithmetic mean. In this case, the mean square of deviations will be larger by a well-defined value - by the square of the difference between the average and this conditionally taken value.

45. Intragroup and intergroup dispersion.

Dispersion is divided into total, intergroup and intragroup. The total variance s2 measures the variation of a trait in the entire population under the influence of all the factors that caused this variation.

Intergroup variance (s2x) characterizes systematic variation, i.e. differences in the magnitude of the trait under study, arising under the influence of the trait-factor underlying the grouping.

The within-group variance (s2i) reflects random variation, i.e. part of the variation that occurs under the influence of unaccounted for factors and does not depend on the trait-factor underlying the grouping.

46. ​​The rule of adding variances.

There is a law relating the three types of dispersion. The total variance is equal to the sum of the average of the intragroup and intergroup variances:

This relation is called the rule of addition of variances. According to this rule, the total variance arising under the influence of all factors is equal to the sum of the variance arising due to the grouping attribute.

Knowing any two types of dispersions, one can determine or check the correctness of the calculation of the third type.

The rule for adding variances is widely used in calculating the indicators of the closeness of relationships, in analysis of variance, in assessing the accuracy of a typical sample, and in a number of other cases.

47. Relationships of social phenomena, their types, forms.

The variety of relationships in which there are socio-economic phenomena, give rise to the need for their classification.

According to the types, functional and correlation dependence is distinguished.

functional such a dependence is called, in which one value of the factor attribute X corresponds to one strictly defined value of the resultant attribute Y.

Unlike functional dependency, correlation expresses such a relationship between socio-economic phenomena, in which one value of the factor attribute X can correspond to several values ​​of the effective attribute Y.

There are direct and inverse relationships according to direction.

Straight they call such a dependence in which the value of the factor attribute X and the resultant attribute Y change in the same direction. That. as X increases, Y values ​​increase on average, and as X decreases, Y decreases.

Reverse the relationship between factor and resultant features, if they change in opposite directions.

50. Analysis of the relationship of qualitative features.

associations and contingents

If the signs have 3 or more gradations, then the Pearsen and Chuprov coefficients are used to study the relationships. They are calculated according to the formulas:

C - Pearsen coefficient

K - Chuprov coefficient

j - indicator of mutual contingency

mi - table columns

nj - strings

n - number of observations

51. Statistical methods for studying relationships.

An important place in the statistical study of relationships is occupied by the following methods:

1. Method of reduction of parallel data.

2. Method of analytical groupings.

3. Graphical method.

4. Balance method.

6. Correlation-regression.

1. Essence parallel data reduction method is as follows:

The initial data on the basis of X are arranged in ascending or descending order, and on the basis of Y, the corresponding indicators are recorded. By comparing the values ​​of X and Y, a conclusion is made about the presence and direction of dependence.

3. Essence graphic method is a visual representation of the presence and direction of relationships between features. To do this, the value of the factor attribute X is located along the abscissa axis, and the value of the resulting attribute along the ordinate axis. According to the joint arrangement of points on the graph, a conclusion is made about the direction and the presence of dependence. In this case, the following options are possible:

a \, b / (up), c \ (down).

If the points on the graph are arranged randomly (a), then there is no relationship between the studied features.

If the points on the graph are concentrated around the straight line (b) /, the relationship between the features is direct.

If the points are concentrated around the straight line (c) \, then this indicates the presence of an inverse relationship.

Based on the method of parallel data and the graphical method, indicators can be calculated that characterize the degree of closeness of the correlation dependence.

The most multiple of them is the Fechner sign coefficient. It is calculated by the formula:

C - the sum of the coinciding signs of the deviations of the individual values ​​of the attribute from the average.

H - sum of mismatches

This coefficient varies within (-1;1).

The value of KF=0 indicates the absence of dependence between the studied features.

If KF=±1, then this indicates the presence of a functional direct (+) and inverse (-) dependence. With a value of KF>? 0.6? it is concluded that there is a strong direct (inverse) relationship between the features.

Rank difference squares

(R2-R1), n ​​- number of pairs of ranks

This coefficient, like the previous one, varies within the same limits and has the same economic interpretation as KF.

52. Non-parametric indicators of the tightness of the relationship. Spearman. Kendall.

54. The concept of the rank of dynamics. Types of dynamic series.

In the analysis of socio-economic phenomena, one often has to resort to various conditional estimates, for example, ranks, and the relationship between individual features is measured using non-parametric correlation coefficients. These coefficients are calculated under the condition that the characteristics under study obey different distribution laws.

Ranging is a procedure for ordering objects of study, which is performed on the basis of preference.

Rank - this is the serial number of the attribute values, arranged in ascending or descending order of their values. If the attribute values ​​have the same quantitative assessment, then the rank of all these values ​​is taken equal to the arithmetic mean of the corresponding numbers of places that are determined. These ranks are called liaison.

The principle of numbering the values ​​of the studied features is the basis of non-parametric methods for studying the relationship between socio-economic phenomena and processes.

Among the nonparametric methods for estimating the tightness of the connection, the rank coefficients of Spearman (r) and Kendall (t) are of the greatest importance. These coefficients can be used to determine the frequency of relationships between both quantitative and qualitative features, provided that their values ​​are sorted or ranked according to the degree of decrease or increase of the attribute.

The correlation coefficient of ranks (Spearman coefficient) is calculated by the formula (for the case when there are no connected ranks). Spearman's coefficient takes any value in the range [-1;1].

Kendall's rank correlation coefficient (t) can also be used to measure the relationship between qualitative features that characterize homogeneous objects, ranked according to the same principle.

The calculation of this coefficient is performed in the following sequence:

1. X values ​​are ranked in ascending or descending order

2. Y values ​​are arranged in order corresponding to X values

3. For each rank Y, the number of following values ​​of ranks that exceed its value is determined

4. For rank Y, the number of ranks following it, less than its value, is determined. The total value is denoted by Q and is fixed with a sign (-)

5. The sum of points for all members of the series is determined.

To determine the tightness of the relationship between an arbitrary number of ranked features, multiple rank correlation coefficient(concordance factor) (W).

53. Indicators of mutual contingency.

To study the relationship of qualitative alternative features that take only 2 mutually exclusive values, the coefficient is used associations and contingents. When calculating these coefficients, the so-called. table of 4 stones, and the coefficients themselves are calculated by the formula:

If the association coefficient? 0.5, and the contingency coefficient? 0.3, then we can conclude that there is a significant relationship between the studied features.

If the signs have 3 or more gradations, then to study the relationships are used conjugacy coefficients Piersen and Chuprov. They are calculated according to the formulas:

C - Pearsen coefficient

K - Chuprov coefficient

j- mutual contingency index

K - number of values ​​(groups) of the first feature

K1 - number of values ​​(groups) of the second feature

fij - frequencies of the corresponding cells of the table

mi - table columns

nj - strings

To calculate the Pearsen and Chuprov coefficients, an auxiliary table is compiled:

When ranking qualitative features in order to study their relationship, the Kendall correlation coefficient is used.

n - number of observations

S is the sum of the differences between the number of sequences and the number of inversions by the second feature.

P is the sum of rank values ​​following the data and exceeding its value

Q - the sum of the rank values ​​following the data and less than its value (taken into account with the "-" sign).

In the presence of related ranks, the formula for the Kendall coefficient will be as follows:

Vx and Vy are determined separately for ranks X and Y by the formula:

55. Comparability of levels and closure of series of dynamics.

The most important condition for the correct construction of a series of dynamics is the comparability of all its constituent levels. This condition is solved either in the process of collecting and processing data, or by recalculating them.

The incompatibility of the levels of the series may arise due to a change units of measurement or units of account.

The comparability of the levels of a series of dynamics is directly affected by accounting methodology or calculation of indicators. For example, if in some years the average yield was calculated from the sown area, and in others - from the harvested area, then such levels will not be comparable.

The condition for comparability of the levels of a series of dynamics is periodization of dynamics. In the process of development in time, first of all, quantitative changes in phenomena occur, and then, at certain stages, qualitative leaps are made, leading to a change in the regularity of the phenomenon. Therefore, the scientific approach to the study of the series of dynamics is to divide the series covering large periods of time into those that would unite only periods of the same quality in the development of an aggregate characterized by one pattern of development.

The process of identifying homogeneous stages of development is called periodization of dynamics.

It is also important that in the series of dynamics intervals or moments, according to which the levels are determined, had the same economic sense. For example, when studying the growth of the livestock population, it is meaningless to compare the numbers of the livestock as of October 1 with January 1, since the first figure includes not only the cattle left for the winter, but also intended for slaughter, and the second figure includes only the cattle left for the winter.

The levels of the dynamics series may turn out to be incomparable in terms of covered objects due to the transition of a number of objects from one subordination to another.

The incompatibility of the levels of the series may arise due to changes in the territorial boundaries of regions, districts, etc. At the same time, speaking about the change in the territory to which the levels of the series for different times belong, it should be borne in mind that the question of comparability or incompatibility when the territory changes is solved in different ways, depending on the purpose of the study.

In order to bring the levels of a series of dynamics to a comparable form, sometimes one has to resort to a technique called “closing the series of dynamics”. Closure is understood as the union in one series (longer) of two or more series of dynamics, the levels of which are calculated according to different methodology or different territorial boundaries. To implement the closure, it is necessary that for one of the periods (transitional) there are data calculated according to different methodology (or within different boundaries).

60. Components of a series of dynamics.

A number of dynamics can be influenced by factors of an evolutionary and oscillatory nature, as well as be influenced by factors of various influences.

Influences of an evolutionary nature are changes that determine a certain general direction of development, as it were, a multi-year evolution that makes its way through other systematic and random fluctuations. Such changes in the dynamic series are called development trend, or trend.

Oscillatory influences are cyclical (opportunistic) and seasonal fluctuations. Cyclic (or periodic) consist in the fact that the value of the trait under study increases for some time, reaches a certain maximum, then decreases, reaches a certain minimum, increases again to the previous value, etc. Cyclical fluctuations in economic processes roughly correspond to the so-called conjuncture cycles. seasonal fluctuations- these are fluctuations that periodically repeat at some specific time of each year, days of the month or hours of the day. These changes are clearly observed on the graphs of many time series containing data for a period of at least one year.

Irregular fluctuations for socio-economic phenomena can be divided into two groups: a) sporadically occurring changes caused, for example, by war or environmental catastrophe; b) random fluctuations resulting from the action of a large number of relatively weak secondary factors.

61. Methods for identifying trends in time series.

62. Determination of the main trend of dynamics based on the enlargement of intervals and the moving average.

The levels of a series of dynamics are formed under the attention of 3 groups of factors:

1. Factors determining the main direction, i.e. development trend of the phenomenon under study.

2. Factors acting periodically, i.e. directional fluctuations by weeks of the month, months of the year, etc.

3. Factors acting in different, sometimes in opposite directions and not having a significant impact on the level of a given series of dynamics.

The main task of the statistical study of dynamics is to identify trends.

The main methods for identifying trends in time series are:

Interval coarsening method

moving average method

Analytical alignment method

1. Essence interval enlargement method is as follows:

The original series of dynamics is transformed and replaced by others consisting of other levels related to enlarged periods or points in time.

for example: a series of dynamics of the profit of a small enterprise for 1997 by quarters of the same year. At the same time, the levels of the series for enlarged periods or points in time can be either total or average indicators. However, in any case, the levels of the series calculated in this way more clearly reveal trends, since seasonal and random fluctuations cancel out and balance out when summing up or determining averages.

2. moving average method, like the previous one, involves the transformation of the original series of dynamics. To identify a trend, an interval consisting of the same number of levels is formed. In this case, each subsequent interval is obtained by shifting by 1 level from the initial one. According to the intervals thus formed, the sum is determined at the beginning, and then the averages. It is technically more convenient to define moving averages for an odd interval. In this case, the calculated average value will refer to a specific level of the time series, i.e. to the middle of the slip interval.

When determining a moving average over an even interval, the calculated value of the average refers to the interval between two levels, and thus loses economic meaning. This necessitates additional calculations related to centering according to the arithmetic simple formula from two adjacent non-centered averages.

64. The role of the index method in statistical research.

Individual for example, change in the production of cars of a certain brand. The individual index is denoted by i. Consolidated the index reflects the change in the entire set of elements of a complex phenomenon. If the indices do not cover all the elements of a complex phenomenon, but only a part, then they are called group or sub-indices. for example, product indices for individual industries.

65. Aggregate indices, their relationships.

Aggregate index - a complex relative indicator that characterizes the average change in a socio-economic phenomenon, consisting of incommensurable elements.

The Latin word "aggregate" means "added, summed up." The peculiarity of this form of the index is that in the aggregate form two sums of indicators of the same name are directly compared. At present, this is the most common form of indices used in practical statistics in many countries of the world.

The numerator and denominator of the aggregate index are the sum of two values, one of which changes (indexed value), and the other remains unchanged in the numerator and denominator (index weight).

An indexed value is a sign, the change of which is being studied (the price of goods, the stock price, the cost of working time for the production of products, the number of goods sold, etc.). Index weight - this is the value that serves for the purposes of comparing the indexed values.

Behind each economic index are certain economic categories. The economic content of the index predetermines the method of its calculation.

The methodology for constructing an aggregate index provides for the solution of three questions:

1. What value will be indexed

2. According to what composition of heterogeneous elements of the phenomenon is it necessary to calculate the index

3. What will serve as a weight when calculating the index.

When choosing the weight of the index, it is customary to be guided by the following rule: if the index of a quantitative indicator is being built, then the weights are taken for the base period; when constructing the index of a qualitative indicator, the weights of the reporting period are used.

66. Individual and composite aggregate indices.

The index is a relative value obtained by comparing the levels of socio-economic phenomena in time, in space or with a plan.

As a measure of comparison of heterogeneous products, you can use the price, cost or labor intensity of a unit of production.

In the development of index theory in our country, two directions have developed: generalizing, or synthetic, and analytical.

The difference between these directions is due to two possibilities for interpreting indices in their application.

The generalizing or so-called synthetic direction interprets the index as an indicator of the average change in the level of the phenomenon under study. In analytical theory, indices are perceived as indicators of a change in the level of the resulting value under the influence of a change in the indexed value.

The development of the second direction was due to the use of the index method in economic analysis.

Methods for constructing indices depend on the content of the phenomena under study, the methodology for calculating the initial statistical indicators, and the objectives of the study.

Individual are called indices that characterize the change in only one element of the population. for example, change in the production of cars of a certain brand. Individual index denoted i. Consolidated the index reflects the change in the entire set of elements of a complex phenomenon. If the indices do not cover all the elements of a complex phenomenon, but only a part, then they are called group or sub-indices. For example, product indices for individual industries.

Depending on the content and nature of the indexed value, there are indices of quantitative (volume) indicators (for example, the index of the physical volume of production) and indices of qualitative indicators (for example, price indices, cost prices).

When calculating indices, there is a difference between the compared level and the level with which the comparison is made, called the base level. In this case, two methods of calculating indices are possible - chain and basic. Chained indices are obtained by comparing the current levels with the previous one. Basic indices are obtained by comparison with the level of any one specific period, taken as the basis of comparison.

Depending on the calculation methodology, aggregate indices and averages of individual indices are distinguished. Individual indices are divided into arithmetic mean and harmonic mean indices. Aggregate indices of qualitative indicators can be calculated as indices of variable composition and indices of fixed (constant) composition. In indices of variable composition, indicators calculated on the basis of changing structures of phenomena are compared, and in indices of fixed composition, on the basis of an unchanged structure of phenomena.

67. The most important economic indices and their relationship.

There are interrelations between the most important indices, which make it possible to obtain others on the basis of some indices. Knowing, for example, the value of chain indices for any period of time, it is possible to calculate the basic indices. And vice versa, if the basic indices are known, then by dividing one of them by the other one can obtain chain indices.

The existing relationships between the most important indices make it possible to identify the influence of various factors on the change in the phenomenon under study, for example, the relationship between the index of the cost of production, the physical volume of production and prices. Other indexes are also related. So, production cost index is the product of the production cost index and the volume index of production.

The index of time spent on production can be obtained as a result of multiplying the index of the physical volume of production and the value, the reciprocal of the index of labor intensity, i.e. labor productivity index.

There is an important relationship between indices of the physical volume of production and indices of labor productivity.

Labor productivity index represents the ratio of the average production output (in comparable prices) per unit of time (or per employee) in the current and base periods. for example, the index of the physical volume of production is equal to the product of the labor productivity index and the index of working hours (or the number of employees).

The relationship between individual indices can be used to identify individual factors that affect the phenomenon under study.

The labor productivity index for production costs shows how many times the labor productivity increased (decreased), or how many percent was the decrease (growth) in labor productivity in the current period compared to the base one.

The index value reduced by 100% shows the percentage change in labor productivity in the current period compared to the base period.

The difference between the numerator and denominator shows the absolute amount of savings (overspending) of the cost of living labor in connection with the growth (decrease) of its productivity.

A change in the structure of a phenomenon is understood as a change in the proportion of individual groups of population units in their total number. Thus, the average salary at the enterprise may increase as a result of an increase in the wages of employees or an increase in the proportion of highly paid employees.

The variable composition index is an index that expresses the ratio of the average levels of the phenomenon under study, relating to different periods of time.

The variable composition index reflects a change not only in the indexed value (in this case, the cost), but also in the structure of the population (weights).

An index of constant (fixed) composition is an index calculated with weights fixed at the level of one of any period, and showing a change in only the indexed value.

The index of structural shifts is understood as an index that characterizes the effect of a change in the structure of the phenomenon under study on the dynamics of the average level of this phenomenon.

In statistical practice, there is often a need to compare the levels of an economic phenomenon in space: by countries, economic regions, regions, i.e. in the calculation of territorial indices. When constructing territorial indices, one has to decide what weights were used in their calculation.

In the theory and practice of statistics, various methods for constructing territorial indices are proposed, including standard weight method. This method lies in the fact that the values ​​of the indexed value are weighted not by the weights of any one region, but by the weights of the region, economic region, republic in which the compared regions are located.

P. S.: The answers to the tickets were taken from the lectures and from the textbook by Shmoylova R.A. "Theory of Statistics"

? SHVACHKIN MAXIM DE-103

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THEME 1

The subject of statistics as a science is...

statistics method

statistics

Quantitative patterns of mass varying social phenomena

groupings and classifications

Statistical science began to take shape ...

In the 17th century

in the 7th century

in the 19th century

before the beginning of modern reckoning

Indicate which of the following is not a characteristic feature of statistics as a science

the study of the quantitative side of mass social phenomena in close connection with the qualitative side

The study of all social and natural phenomena

study of phenomena in specific conditions of place and time

identification of trends and patterns in mass socio-economic phenomena and processes

The main branch of statistical science is ...

General theory of statistics

industrial statistics

probability theory

math statistics

An element of which branch of statistical science is construction statistics

economic statistics

general theory of statistics

social statistics

mathematical statistics

"Social physics" was called statistics by a representative of the "statistical-mathematical" school (who?) ...

Graunt, Halley (England, 17th century)

Achenwal (Germany, 18th century)

M.Lomonosov (Russia, 18th century)

Quetelet (Belgium, 19th century)

Point out the wrong sentence. Government statistics in Russia…

Publishes 1 monthly, 1 quarterly journal, 1 statistical yearbook

develops and approves forms of statistics. reporting, mandatory for execution by legal entities in the Russian Federation

It has territorial bodies in the regions of the country

presented by the State Statistics Committee of the Russian Federation

An employee for whom the collection of statistical data is professional activity, is called…

data collector

an extra

census taker

Statistician

Choose the most precise definition: "A statistical aggregate is..."

set of elements that have common features

a set of elements that have one common and one varying feature

any subject set of natural and social phenomena

Really existing set of homogeneous elements with common features and internal connection

What is the carrier of information in the statistical population?

Population unit

attributive variable

population attribute

A statistical population is different from a mathematical one...

what is taught in statistics

the existence of elements in the abstract representation

number of elements

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An element of a statistical population is...

element of the periodic table

mathematical set element

population attribute

Information carrier

The sign "land area for individual construction" is ...

attributive

quantitative

quality

quantitative-qualitative

The sign of "social stratum in society" is ...

attributive

quality

quantitative

quantitative-qualitative

Variation is:

population change

change of mass phenomena in time

change in the structure of the statistical population in space

Change in the values ​​of a feature within the observed population

Which of the following features is variable?

the speed at which a body falls in a vacuum

dollar exchange rate

The price of one kilogram of grapes

boiling point of water

Theme 2

What is the difference between statistical observation and the observation of a writer, artist

observation time difference

Different Purpose of Surveillance

Scientific organization and planning

the difference in the object of observation

The list of signs (or questions) to be recorded during the observation process is called

monitoring program

monitoring tools

statistical form

instruction

The question in the statistical survey form “How much time do you devote to watching TV programs (hours per week)?”, is in the form of compilation ...

closed

open

open-closed

mixed

The question in the statistical survey form “How often do you go to the cinema?”: “Almost every week”, “Once a month”, “Less than once a month” - is in the form of compilation ...

indirect

open-closed

Closed

open

unit of observation

population unit

reporting unit

Population

The object of statistical observation is ...

unit of observation

population unit

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accounting unit

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never match

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same

Sometimes they can match

The period (period) of observation is

critical moment (date) of observation

The time during which the statistical forms are filled out

specific day of the year, hour of the day, as of which the registration of signs for each unit of the population should be carried out

Continuous statistical observation of long-term processes that have a fixed beginning, a stage of development and a fixed end is ...

specially organized statistical observation

Register form of observation

selective observation of the main array

a form of statistical observation, the census of the population of Russia refers to ...

one-time, specially organized observation

periodic, register, selective observation

Periodic, specially organized, continuous observation

Russia's population census is being conducted...

once every 25 years

once every 5 years

Once every 10 years

once every 15 years

The population census of the Russian Federation was carried out from October 9 to October 16, 2002. The critical moment was 00 am from October 08 to 09. The counter came to the family on October 16th. A child was born in the family on October 14. What should the counter do about this child?

consult management

mark in notepad

put on the register

Do not write in the census form

The population census of the Russian Federation was carried out in the period from October 9 to October 16, 2002. The critical moment was 00 am from October 08 to 09. The counter came to the family on October 11th. A family member died on October 10. How should the counter

mark in notepad

Submit with a note of death

do not enter information about the deceased in the census form

enter without a note of death

The population census of the Russian Federation was carried out from October 9 to October 16, 2002. The critical moment was 0 am from October 08 to 09. The counter came to the family on October 15 and got to the wedding. Two hours ago, the newlyweds returned from the registry office after registering their marriage (they had not been married before). What should the enumerator write on the census form in the question: "Are you currently married?" about each spouse?

Not married

is married

put a dash, because difficult to determine

Why are censuses usually held in winter?

lower transport costs

savings in personnel training resources are achieved

no need for a critical moment of observation

The least mobility of respondents

Does the Russian Federation have such a form of statistical observation as a population register?

Only being designed

Not