Statistical Observation Authority. Forms, types and methods of statistical observation

1. The concept of statistical observation, stages of its implementation.

2. Basic organizational forms of statistical observation. Types and methods of statistical observation.

3. Program and methodological issues statistical observation.

4. Organizational issues of statistical observation.

5. Errors in statistical observation.

1. The concept of statistical observation and the stages of its implementation.

Statistical observation - this is a massive, systematic, scientifically organized observation of the phenomena of social and economic life, which consists of recording selected characteristics for each unit of the population.

Statistical observation is carried out by state statistics bodies, research institutes, economic services of banks, exchanges, and firms.

The process of conducting statistical observation includes the following stages:

1) preparation of observation;

2) conducting mass data collection;

3) preparing data for automated work;

4) development of proposals for improving statistics. observations.

First stage includes:

Determination of the purpose and object of observation, the composition of signs to be registered;

Development of documents for data collection;

Selecting a reporting unit, methods and means of obtaining data, etc.

Second phase includes work on filling out statistical forms.

On third stage the collected data is subject to arithmetic and logical control.

On fourth stage produced:

Analysis of the reasons that led to the incorrect filling of stats. forms;

Development of proposals to improve surveillance.

2. Basic organizational forms of statistics. Observations. Types and methods of stat. Observations.

Statistical observation is carried out in 2 forms:

1) by providing reports;

2) by conducting specially organized statistics. observations.

Reporting is an organized form of statistical observation in which information is received in the form of mandatory reports within certain deadlines and in approved forms. Reporting as a form of statistical observation is based on primary accounting and is its generalization.

Primary accounting is a registration of various facts (events, processes, etc.) produced as they occur and, as a rule, on a primary document.

The management of statistical reporting and its organization are entrusted to the state statistics bodies. All forms of statistical reporting are approved by state statistics bodies. Submitting reports on unapproved forms is considered a violation of reporting discipline, for which heads of enterprises and departments are held accountable.

The list of reporting is a list of reporting forms indicating their most important details.

Reporting program- system of performance indicators of a trading enterprise.

General reporting- this is reporting containing the same data for a certain sector of the national economy and for enterprises (institutions, etc.) of the entire national economy.

IN specialized reporting contains specific indicators of individual industries, agriculture, etc.

Based on the period of time for which reporting is presented, and its duration, a distinction is made between current and annual reporting. If information is presented for the year, then such reporting is called annual. Reporting for all other periods within less than a year, respectively quarterly, monthly, weekly, etc., is called current.

According to the method of presentation, reporting is distinguished urgent, when all information is submitted by teletype, telegraph, and postal

In practice commercial work reporting is subdivided on the:

1) nationwide - provided both to a higher organization and to the relevant state bodies. statistics;

2) intradepartmental - which is submitted only to higher trade authorities;

3) current - presented during the year;

4) annual - the most complete in terms of the composition of displayed indicators.

Specially organized statistical observation- represents the collection of information through censuses, one-time records and surveys. For example: population census, census of equipment, remaining materials, etc.

Types of statistical observation differ in the time of data recording and in the degree of coverage of units of the population under study.

By time of data recording distinguish:

Continuous (ongoing) monitoring;

Intermittent (periodic) observation.

Intermittent observation is divided into:

Periodic;

One-time.

Current (continuous) is an observation that is carried out systematically. In this case, facts are recorded as they occur. (For example, civil registration). During ongoing observation, a significant gap cannot be allowed between the moment the fact occurs and the moment it is recorded.

Intermittent (periodic) called an observation that is repeated at certain intervals. (For example, annual livestock censuses conducted as of January 1).

One-time (one-time) observation carried out as needed, from time to time, without observing strict frequency or even once. (For example, studying customer opinions about the quality of goods).

According to the degree of coverage, they are distinguished:

Solid

Not continuous stat. observation.

Solid is an observation in which all units of the population being studied are examined without exception. (For example, the All-Union Population Census of 1989). Through continuous observation, reports are obtained from enterprises and institutions.

Not continuous is called such an observation in which predetermined statistical units are examined. totality. (For example, studying trade turnover and prices in city markets). Main advantage: this type observations increases the efficiency of statistics. material.

Depending on the research task and character object not continuous observation could be:

Selective;

Main array method;

Monographic.

Selective is an observation in which the characteristics of the entire set of facts are given based on some of them, selected at random. It is widely used in various sectors of the national economy: in industry - to control product quality; in trade - to study the demand of the population, etc.

Main Array Method consists in the fact that that part of the population units in which the value of the studied characteristic is predominant in the entire volume is subjected to examination. (Thus, monitoring of the work of city markets has been organized. Of all the cities for observation, 308 cities- the largest industrial and cultural centers, where over 50% of the total urban population lives. The turnover of markets in these cities accounts for over 60% of the total turnover of market trade).

Monographic survey- this is a detailed, in-depth study and description of individual units of the totality that are characteristic in some respect. It is carried out with the aim of identifying existing or emerging trends in the development of this phenomenon.

Stat methods observations.

Stat. information can be obtained in various ways, the most important of which are:

Direct observation;

Documentary accounting;

Direct is an observation in which the registrars themselves, by measuring, weighing or counting, establish the fact to be recorded, and on this basis make entries in the observation forms. (For example, when taking a census of equipment, information is entered into a form based on a personal inspection of the machines, etc.)

Documentary method observation is based on the use of statistics as a source. information from various types of accounting documents.

Survey is a method of observation in which answers to the questions being studied are recorded from the words of the interviewee.

The following types of surveys are used in statistics:

Oral (expeditionary);

Self-registration;

Correspondent;

Questionnaire;

Appearance.

At oral questioning specially trained workers (counters, recorders) receive the necessary information based on a survey of relevant persons and themselves record the answers in the observation form.

At self-registration the forms are filled out by the respondents themselves, and the enumerators give them the questionnaire forms, explain the rules for filling them out, and then collect them.

Correspondent method consists in the fact that information is provided to the bodies conducting surveillance by their correspondents. This method does not require large expenses, but it does not provide high quality materials.

Questionnaire method involves collecting information in the form of questionnaires. This method of collecting information is used for incomplete observation and is used in surveys where high accuracy is not required. It is used when conducting sociological surveys.

Programme-methodological and organizational issues of statistical observation

The beginning of statistical research proceeds in the following sequence: precisely formulated purpose of the study→ are placed specific tasks, and thus the information that can be obtained during the observation process is clarified → determined object and unit of observation→ being developed program→ selected view And observation method.

Observation object– a set of socio-economic phenomena and processes that are subject to research, and the exact boundaries within which statistical information will be recorded. In a number of cases, one or another qualification is used to delimit the object of observation. A qualification is a restrictive feature that all units of the population under study must satisfy.

Unit of observation called component object, which serves as the basis of the account and has characteristics that are subject to registration during observation.

Surveillance program– this is a list of issues on which information is collected, or a list of characteristics and indicators to be registered. The observation program is drawn up in the form of a form (questionnaire, form) in which primary information is entered. A necessary addition to the form is instructions (or instructions on the forms themselves) explaining the meaning of the question. The composition and content of the questions in the observation program depend on the objectives of the study and on the characteristics of the social phenomenon being studied.

When organizing statistical observation, it is established observation period, i.e. the period of time during which the observation will be carried out, and the exact time to which the recorded information relates is determined - objective observation time(this can be either a specific moment, or one or another period (day, decade, month, quarter, year)). The point in time to which the recorded information is dated is called critical moment of observation.

The main characteristics of statistical observation are presented in Fig. 2.1.

Reporting- this is an organizational form in which observation units (accountable persons) submit information about their activities to the relevant authorities in a timely manner in the form of regulated forms. It is mandatory, documented, since reporting indicators are compiled according to primary accounting data (operational, accounting), and legally confirmed by the signature of the manager. Report forms are called statistical reporting forms. Each of them has its own code and name.

Specially organized statistical observations carried out in the form of censuses, one-time registration and special surveys.

Census- This is a specially organized registration of data for a specific date. During censuses, information is obtained for which no systematic and complete accounting is maintained using appropriate documentation. Censuses are usually conducted at regular intervals (after 5 years, 10 years, etc.), i.e. periodically. Periodic surveys contribute to the study of development patterns, structural changes, etc.

One-time accounting, like a census, is carried out for the purpose of registering facts on a certain date, and takes place if primary accounting materials or current reporting are used to obtain information. With one-time accounting, statistical forms (forms), as a rule, are filled out by employees of specific enterprises and organizations, which significantly saves time and money. One-time accounting is irregular, it is carried out as the need for data arises.

Special statistical survey organized if additional detail of certain indicators is required.

The indicated organizational forms of statistical observation, being complementary,

Table 1.1

Forms, types and methods of statistical observation

Let us consider the forms, types and methods of statistical observation in more detail.

Forms of statistical observation

1.Periodic reporting – This is a statistical observation that is carried out at least once a year. Periodic reporting of an enterprise can be monthly, quarterly, semi-annual and annual.

2. If the necessary statistical data are not available during the reporting period, specially organized statistical observation.

Census – This is a specially organized observation of mass social phenomena and processes, which is carried out on a certain date in time: a population census, a census of unidentified equipment, a census of livestock, fruit trees, etc.

One-time observation – This is a specially organized statistical observation for the study of social phenomena, which is carried out regularly once every 2, 3 or 5 years.

Special statistical survey carried out as necessary and is selective.

The following types of statistical observation are distinguished.

Types of statistical observation

I. By frequency:

1. Current is an observation that is carried out continuously as the phenomenon occurs.

2. One-time – This is an observation that is carried out as needed, usually once every 2, 3, 5 years.

3. Periodic – This is an observation that is carried out at certain, usually equal, intervals.

II. By coverage:

1. Continuous is an observation in which all units of the population are examined.

2. Sampling is an observation in which a certain, scientifically based part of the population is studied, and the results of the observation are distributed to the entire population.

3. The main array is an observation in which the most typical (main) part of the population is examined.

4. Monographic – consists of detailed description one or more units of the population being studied.

Methods for conducting statistical observation

Methods of conducting statistical observation include:

Direct – carried out by recording facts directly by the person conducting the observation.

Documentary – based on the use of various documents as sources of information about the object being studied.

A survey is the process of obtaining data by recording the responses given by the persons being surveyed.

Expedition survey - carried out directly by specially trained persons.

A questionnaire is a survey that is conducted by sending out or distributing questions and receiving them back.

Correspondent – ​​forms are sent to specially trained individuals, which they periodically fill out and send back.

Self-registration is the registration of answers to questions posed by the respondents themselves.

Statistical observations are divided into types according to the following criteria:

by time of data recording;

in terms of completeness of coverage of population units;

Types of statistical observation by registration time:

Current (continuous) observation - carried out to study current phenomena and processes. Facts are recorded as they occur. (registration family marriages and divorces)

Continuous observation - carried out as necessary, while temporary breaks in data recording are allowed:

 Periodic observation - carried out at relatively regular intervals (population census).

 One-time observation - carried out without observing strict frequency.

Based on the completeness of coverage of population units, the following types of statistical observation are distinguished:

Continuous observation is the collection and receipt of information about all units of the population being studied. It is characterized by high material and labor costs and insufficient information efficiency. It is used in the population census, when collecting data in the form of reporting, covering large and medium-sized enterprises of various forms of ownership.

Non-continuous observation - based on the principle of random selection of units of the population being studied, while all types of units present in the population must be represented in the sample population. It has a number of advantages over continuous observation: reduction of time and money costs.

Continuous observation is divided into:

Sample observation - based on a random selection of units that are subject to observation.

Monographic observation consists of examining individual units of a population characterized by rare qualitative properties. An example of monographic observation: characteristics of the work of individual enterprises to identify shortcomings in work or development trends.

The main array method consists of studying the most significant, largest units of the population, which, according to the main feature, have the largest share in the population being studied.

The momentary observation method consists of conducting observations at random or constant time intervals with notes on the state of the object under study at one time or another.

Methods of statistical observation

Direct statistical observation is observation in which the registrars themselves, by direct measurement, weighing, and counting, establish the fact to be recorded.

Documentary observation is based on the use of various types of accounting documents. Includes a reporting method of observation - in which enterprises submit statistical reports on their activities in a strictly mandatory manner.

A survey involves obtaining the necessary information directly from the respondent.

The following types of survey exist:

Forwarding - registrars receive the necessary information from the persons being interviewed and record it in the forms themselves.

Method of self-registration - the forms are filled out by the respondents themselves, the registrars only hand out the forms and explain the rules for filling them out.

Correspondent - information is provided to the relevant authorities by a staff of voluntary correspondents.

Questionnaire - information is collected in the form of questionnaires, which are special questionnaires, convenient in cases where it is not required high accuracy results.

Appearance - consists of providing information to the relevant authorities in person.

Selective observation

The concept of selective observation

Selective observation is a type of incomplete observation. It covers a selected portion of units in the population. The purpose of sample observation is to characterize the entire population of units using a selected part of units. In order for the selected part to be representative (i.e., to represent the entire population of units), sample observation must be specially organized. Therefore, in contrast to the general population, which represents the entire population of units under study, the sample population represents that part of the units of the general population that is the object of direct observation.

For obvious reasons, the sampling method can be widely used by government statistics agencies. It allows you to obtain the necessary reliable information with significant savings in money and costs. The guarantee of representativeness is ensured by the use of scientifically based methods for selecting units that are subject to examination.

It should immediately be borne in mind that when comparing indicators from the results of a sample study with characteristics for the entire population, deviations may occur. The magnitude of these deviations is called observation error, which can be either a registration error (imperfect technical conditions) or a representativeness error (random or systematic violation of the rules in the selection of units).

The following conventions are used in statistics:

N is the volume of the general population;

n is the volume of the sample population;

Average in the population;

Average in the sample population;

p is the proportion of units in the general population;

w is the proportion of units in the sample population;

General variance;

S 2 - sample variance;

The standard deviation of a characteristic in the population;

S is the standard deviation of the characteristic in the sample population.

Types of sampling, selection methods and sampling errors

According to the method of selection (method of formation) of a sample of units from the general population, the following types of sample observation are common:

simple random sampling (properly random);

typical (stratified);

serial (nested);

mechanical;

combined;

stepped.

A simple random sample (properly random) is the selection of units from the general population by random selection, but subject to the probability of selecting any unit from the general population. Selection is carried out by drawing lots or using a table of random numbers.

Typical (stratified) sampling involves dividing a heterogeneous population into typological or regionalized groups according to some significant characteristic, after which a random selection of units is made from each group.

What is characteristic of serial (cluster) sampling is that population initially divided into certain equal-sized or unequal-sized series (units within the series are related by a certain characteristic), from which series are selected by random selection and then continuous observation is carried out within the selected series.

Mechanical sampling is the selection of units at regular intervals (alphabetically, at time intervals, by spatial method, etc.). When carrying out mechanical selection, the general population is divided into groups of equal size, from which one unit is then selected.

Composite sampling is based on a combination of several sampling methods.

Multi-stage sampling is the formation within the general population of initially large groups of units, from which smaller groups are formed, and so on until those groups or individual units that need to be studied are selected.

Sampling can be repeated or non-repetitive. In repeated selection, the probability of selecting any unit is unlimited. In case of non-repetitive selection, the selected unit is not returned to the original population.

For selected units, generalized indicators (average or relative) are calculated and subsequently the results of the sample study are distributed to the entire population.

The main task in sampling research is to determine sampling errors. It is customary to distinguish between the average and maximum sampling errors. To illustrate, we can suggest calculating the sampling error using the example of a simple random selection.

12 Absolute and relative values ​​in statistics. Absolute values ​​are the results of statistical observations. In statistics, unlike mathematics, all absolute quantities have a dimension (unit of measurement), and can also be positive and negative. Units absolute values ​​reflect the properties of units of a statistical population and can be simple, reflecting 1 property (for example, the mass of a load is measured in tons) or complex, reflecting several interrelated properties (for example, ton-kilometer or kilowatt-hour). Units absolute values ​​can be of 3 types:

Natural- used to calculate quantities with homogeneous properties (for example, pieces, tons, meters, etc.). Their disadvantage is that they do not allow the summation of heterogeneous quantities.

Conditionally natural- are applied to absolute quantities with homogeneous properties, but manifesting them differently. For example, the total mass of energy carriers (firewood, peat, coal, petroleum products, natural gas) is measured in t.e.f. - tons of standard fuel, since each type has a different calorific value, and 29.3 mJ/kg is taken as the standard. Similarly, the total number of school notebooks is measured in standard units. - conventional school notebooks size 12 sheets. Similarly, canning production products are measured in u.c.b. - conventional cans with a capacity of 1/3 liter. Similar products detergents is reduced to a conditional fat content of 40%. Cost units of measurement are expressed in rubles or other currencies, representing a measure of the value of an absolute value. They allow you to summarize even heterogeneous values, but their disadvantage is that it is necessary to take into account the inflation factor, therefore statistics always recalculate cost values ​​in comparable prices. Absolute values ​​can be momentary or interval. Momentary absolute values ​​show the level of the phenomenon or process being studied at a certain point in time or date (for example, the amount of money in your pocket or the value of fixed assets on the first day of the month). Interval absolute values ​​are the final accumulated result for a certain period (interval) of time (for example, salary for a month, quarter or year). Interval absolute values, unlike moment ones, allow subsequent summation. An absolute statistical value is designated X, and their total number in the statistical aggregate is N.The number of quantities with the same characteristic value is indicated f and is called frequency (recurrence, occurrence). Absolute statistical values ​​themselves do not give a complete picture of the phenomenon being studied, since they do not show its dynamics, structure, and the relationship between parts. Relative statistical quantities are used for these purposes. A relative statistical quantity is the result of the ratio of two absolute statistical quantities. If absolute quantities are correlated with the same dimension, then the resulting relative quantity will be dimensionless (the dimension will be reduced) and is called a coefficient.

More often instead of a name relative statistic a shorter synonymous term is used - index (from Lat. index- indicator, coefficient).

Depending on the types of correlated absolute values ​​when calculating relative values, different types of indices are obtained: dynamics, plan target, plan implementation, structure, coordination, comparison, intensity.

13. Average values. General principles of their application The average value is a general indicator characterizing the typical level of a phenomenon. It expresses the value of a characteristic per unit of the population. The average always generalizes the quantitative variation of a characteristic, i.e., in the average values, individual differences between units of the population due to random circumstances are suppressed. In contrast to the average, the absolute value characterizing the level of a characteristic of an individual unit of a population does not allow one to compare the values ​​of a characteristic among units belonging to different populations. So, if you need to compare the levels of remuneration of workers at two enterprises, then you cannot compare two employees of different enterprises on this basis. The compensation of workers selected for comparison may not be typical for these enterprises. If we compare the size of wage funds at the enterprises under consideration, the number of employees is not taken into account and, therefore, it is impossible to determine where the level of wages is higher. Ultimately, you can only compare average indicators, i.e., how much one employee earns on average at each enterprise. Thus, there is a need to calculate average size as a generalizing characteristic of the population. Let's look at some general principles application of average values. 1. When determining the average value in each specific case, one must proceed from the qualitative content of the characteristic being averaged, take into account the relationship of the characteristics being studied, as well as the data available for calculation. 2. The average value must first of all be calculated from a homogeneous population. Qualitatively homogeneous populations can be obtained by the grouping method, which always involves the calculation of a system of generalizing indicators. 3. Overall averages must be supported by group averages. For example, let’s assume that an analysis of the dynamics of the yield of an individual agricultural crop shows that the overall average yield in the republic is decreasing. However, it is known that the yield of this crop depends on soil, climatic and other conditions and varies in individual areas. 68 Having grouped districts based on differences and analyzed the dynamics of group averages, one can find that in certain groups of districts the average yield either has not changed or is increasing, and the decrease in the overall average for the republic as a whole is due to an increase in the share of districts with lower yields in general production of this agricultural crop. Obviously, the dynamics of group averages more fully reflects the patterns of changes in yield, and the dynamics of the general average shows only the overall result. 4. A reasonable choice of the population unit for which the average is calculated is necessary. Let us now consider the types of average values, features of their calculation and areas of application. Average values ​​are divided into two large classes: power averages, structural averages. Power means include the most well-known and frequently used types, such as geometric mean, arithmetic mean and square mean. The mode and median are considered as structural averages. Let's focus on power averages. Power averages, depending on the presentation of the source data, can be simple or weighted. The simple average is calculated based on ungrouped data and has the following general form: where X, is the option (value) being averaged

18 Concept and classification of dynamics series Dynamics series are a series of numerical data placed in chronological sequence. They are also called dynamic series, time series. The dynamics series characterizes the magnitude of the phenomenon being studied at a specific moment or over a certain period of time. In each series of dynamics there are two main elements: 1. time indicator t; 2.corresponding levels of development of the phenomenon being studied y. Time indications in dynamics series are either specific dates (moments) or individual periods (years, quarters, months, days). The levels of the dynamics series reflect a quantitative assessment (measure) of the development over time of the phenomenon being studied. They can be expressed in absolute, relative or average values. The dynamics series differ in the following ways: 1) By time. Depending on the nature of the phenomenon being studied, the levels of time series can relate either to certain dates (moments) of time, or to individual periods. In accordance with this, the dynamics series are divided into moment and interval. Moment dynamics series display the state of the phenomena being studied at certain dates (moments) in time. An example of a moment series of dynamics is the following information on the payroll number of store employees in 2009 (Table 2): Table 2. Headcount store workers in 2009

A feature of the moment series of dynamics is that its levels may include the same units of the population being studied. Although there are intervals in a moment series—gaps between adjacent dates in the series—the value of a particular level does not depend on the duration of the period between two dates. Thus, the main part of the store staff, which makes up the payroll as of January 1, 2009, continues to work during this year, is displayed in the levels of subsequent periods. Therefore, when summing the levels of the moment series, repeated counting may occur. Using moment series of dynamics in trade, commodity inventories, the state of personnel, the amount of equipment and other indicators are studied that reflect the state of the phenomena being studied at individual dates (points) in time. Interval dynamics series reflect the results of the development (functioning) of the phenomena being studied over individual periods (intervals) of time. An example of an interval series is data on retail turnover of a store in 2000–2004. (Table 3): Each level of the interval series already represents the sum of levels over shorter periods of time. In this case, a unit of the population that is part of one level is not included in other levels. The peculiarity of the interval dynamics series is that each of its levels consists of data for shorter intervals (subperiods) of time. For example, summing up the turnover for the first three months of the year, we get its volume for the first quarter, and summing up the turnover for four quarters, we get its value for the year, etc. Other things being equal, the level of the interval series is greater, the longer the interval is, to which this level belongs. The property of summing levels over successive time intervals makes it possible to obtain dynamics series for more enlarged periods. Using interval series, dynamics in trade are used to study changes in the time of receipt and sale of goods, the amount of distribution costs and other indicators that reflect the results of the functioning of the phenomenon being studied for individual periods. A statistical display of the phenomenon being studied over time can be represented by dynamics series with cumulative totals. Their use is determined by the need to display the results of the development of the studied indicators not only for a given reporting period, but also taking into account previous periods. When compiling such series, a sequential summation of adjacent levels is performed. This achieves a summary of the results of the development of the indicator being studied since the beginning of the reporting period (year, month, quarter, etc.). d.). Dynamic series with cumulative totals are constructed when determining the total volume of trade turnover in retail trade. Thus, by summarizing commodity-money reports for the latest operating periods (five days, weeks, decades, etc.). 2) According to the form of presentation of the levels. Dynamic series can also be constructed, the levels of which are relative and average values. They can also be either momentary or interval. In interval series of dynamics of relative and average values, direct summation of levels in itself is meaningless, since relative and average values ​​are derivatives and are calculated through the division of other quantities. 3) Based on the distance between dates or time intervals, complete or incomplete dynamics series are distinguished. Complete time series occur when the dates of registration or end of periods follow each other at equal intervals. These are equally spaced series of dynamics. Incomplete – when the principle of equal intervals is not observed. 4) Based on the number of indicators, isolated and complex (multidimensional) dynamics series can be distinguished. If one indicator is analyzed over time, we have an isolated dynamics series. A complex series of dynamics is obtained when a system of indicators interconnected by the unity of a process or phenomenon is given in chronological order.

And methods of observation. We are talking about highlighting them in statistics. We suggest first considering the types of observation that are used in this branch of knowledge. The need to choose a data collection option is determined by the fact that there are several types of observation. They differ from each other mainly in the way in which facts are taken into account over time. From this point of view, the following types of observation are distinguished: systematic, periodic and one-time.

Systematic, periodic and one-time observation

Systematic observation, which is carried out continuously and as signs of the phenomenon of interest appear, is usually called ongoing. It is carried out on the basis of containing the necessary information for a fairly full characteristics phenomena of primary documents.

Periodic observation is carried out at certain equal intervals. An example is

If the observation is carried out from time to time, there is no strict frequency, or it is of a one-time nature, we're talking about about one-time observation.

Continuous and continuous observation

Types of observation in statistics are distinguished taking into account the differences in information in terms of completeness of coverage of the population. In this regard, a distinction is made between non-continuous and continuous. The latter is called one that takes into account all units of the population under study without exception. However, its organization is not always practical or possible, especially when it comes to product quality control. Continuous observation in in this case leads to the fact that a lot of enterprise products are excluded from the sphere of use. Therefore, it is necessary to carry out partial (non-continuous) observation. It takes into account only part of the units of the population and gives an idea of ​​the phenomenon as a whole and its characteristic features.

Continuing to consider the forms, types and methods of observation, we note that incomplete observation has the following advantages:

1) much less communication and labor costs are required compared to continuous research, since the number of surveyed units is reduced;

2) data can be collected on a broader program and in more short time in order to comprehensively reveal, within given limits, the features of the population of interest to us, to carry out a deep study of it;

3) non-continuous observation data are used to control materials obtained during continuous;

4) this species must be representative (representative).

Selection of units for incomplete observation

Non-continuous observation is deliberately oriented towards taking into account a specific part of the units, which makes it possible to obtain generalizing stable characteristics of the population as a whole. In practice, statistics are used different kinds observation method. At the same time, the quality of the non-continuous one is, of course, inferior to the results obtained with the continuous one. However, in some cases only partial observation is possible.

The units to be studied are selected in such a way that, based on the data obtained from them, a true picture of the phenomenon of interest as a whole is formed. Consequently, one of the main features of non-continuous observation is that the selection of population units is organized in the following ways:

Monographic;

Main array;

Selective;

Questionnaire.

Main Array Method

The selection of units of a certain population that predominate according to the characteristic being studied involves the method of the main array. However, it is not so often used when a non-continuous view is used, and this method of observation does not ensure the selection of precisely those units that would represent the totality as a whole, all its parts. Selection using the main array is carried out when the most significant, largest populations are taken, which predominate in their total mass according to the characteristic being studied.

Selective observation

In order to obtain a characteristic of the population as a whole in terms of some of its units, it is used based on the principles of sampling. In this option, the random nature of the selection guarantees the safety of the results obtained and prevents their bias.

Monographic description

Let us supplement the types of observation with a monographic description. It represents a specific type of observation in statistics. This is a detailed study of a single typical object that is interesting from the point of view of the whole.

These are the main types of non-continuous observation.

Population and sample

Generalizing indicators of the population in the sampling method are established on the basis of some part of it (quite small - about 5-10%). In this case, the population from which this part of the units is selected is usually called the general one. The part of the units that was selected is called sample population(otherwise known as sampling). Research using the sampling method is carried out with minimal costs funds and labor and in a shorter time. This reduces registration errors and improves efficiency.

Application of the sampling method in practice

Describing the main types of observation, one cannot help but dwell in more detail on selective observation, which is very popular. It is only possible when only destructive can be accomplished. This type is common in departmental and state statistics (studying the budget of families of employees, peasants, workers, as well as living conditions). It is also popular in trade (the effectiveness of new forms of trade, demand for goods from the population), etc.

The sampling method is, in fact, a large number of samples that differ significantly from each other. As a rule, they are based on the principle of random selection from the general population.

Examples of using the sampling method

Examples of observation types provide a clear demonstration of their use. Let's give a few examples of selective, and you will better understand its features. Today, it is the most theoretically developed of the non-continuous ones, since it is based on the principle of random selection. Each unit of the population during random sampling has the same probability of being included in the sample. When conducting a lottery draw, for example, this principle applies, since an equal chance of winning exists for all tickets. The draw also uses random selection. If you select 1 thousand out of 10 thousand schoolchildren for the purpose of studying their academic performance, then this can be done as follows: write the names of the schoolchildren on separate pieces of paper and blindly select 1000.

Non-repetitive and repeated selection

Random selection can be both non-repetitive and repeated. In practice, non-repetition is most often used, that is, a unit included in the sample does not return back to the general population, which means the number of the latter is constantly decreasing. Lottery draws follow exactly this pattern. When re-selected, the selected unit is returned back to the population. Consequently, the number of the latter remains unchanged during the sampling process. If we look at our example with schoolchildren, we can note the following: in this case, if a piece of paper with a last name was among those selected by chance, it would be returned back again and could again be included in the sample.

Expert selection methods

It is very important that no factors, such as the commission organizing the survey or persons, can influence it. In other words, it is necessary that the principle of random selection be respected. However, in practice, its implementation is often difficult. There are areas of statistics in which expert selection methods predominate. This situation arises due to various circumstances. For example, it occurs when selecting goods for calculating price indices or when forming the composition of “baskets” for assessing the cost of living. In such cases, abandoning the random selection method can significantly increase accuracy. However, in this case, the objectivity of the study is lost, and sometimes various types of observation errors arise, since everything in this case depends on the qualifications of the expert.

Mechanical (systematic) selection

Mechanical (systematic) selection is often used in practice. Let’s say that out of 10 thousand schoolchildren you need to select a thousand. In this case, they do this: all the guys are placed in alphabetical order, and then every tenth of them is selected.

Since the interval in this case is 10, a 10% selection is carried out (10,000 divided by 1000). If there is a third student in the top ten (you can choose him by lot), those selected in this case will be the 13th, 23rd, 33rd... 9993rd. With systematic selection, as we see, the general population is divided mechanically into a number of groups, and one unit is taken from each (in our example, one schoolchild). It should be noted that mechanical (systematic) selection is always non-repetitive. It should also be emphasized that the selected units are distributed evenly throughout the entire population.

Methods of observation in statistics

It is necessary to distinguish between methods and types. We have just looked at the latter; let us now move on to studying the methods. The fact is that types of observation can also be distinguished regardless of the ways and sources of obtaining primary information. From this point of view, a distinction is made between documentary observation, survey and direct observation.

Direct is an observation that is carried out by counting, measuring the values ​​of certain characteristics, by taking readings from instruments by the persons who carry it out (they are called recorders).

Due to the fact that other methods and types of statistical observation cannot be used, quite often it is carried out using a survey on a specific list of questions. The answers are recorded in a special form. Depending on how they are received, they are distinguished between correspondent and forwarding, as well as the method of self-registration. Let's briefly describe each of them.

Forwarding is carried out by a special person (forwarder, counter) orally. This person fills out the survey form or form.

The correspondent method is organized by distributing survey forms to a certain circle of persons prepared accordingly (they are called correspondents). These people, according to the agreement, must fill out the form and then return it to the organization. When surveying by self-registration, a check is made to ensure that the forms are filled out correctly. As with the correspondent method, the questionnaires are filled out by the respondents themselves, but the collection and distribution of them, as well as monitoring the correctness of completion and instructions are carried out by the enumerators.

Forms of observation in statistics

Considering the forms, methods, types of statistical observation, we did not talk only about the forms. There are three of them: register, specially organized observation and reporting. As you can see, the types and forms of statistical observation are not the same thing. You should understand the difference between them.

Reporting is the main form of observation. With its help, state statistics bodies receive information from organizations and enterprises in the form of signed responsible persons reporting documents.

Specially organized observation is a collection of information organized by statistical authorities to study phenomena not covered by reporting or for a more in-depth study of reporting data, their clarification and verification. It is carried out in the form of various types of surveys and censuses.

We have described almost all the main methods, types and forms of statistical observation. Only the last form remains - registers. It occurs in the case of continuous monitoring of the processes occurring for a long time, which have a definite beginning, development and end. The facts of the state of the population units are continuously recorded. In statistical practice, a distinction is made between enterprise registers and population registers. The latter represent a regularly updated and named list of the country's inhabitants. The Enterprise Register contains enterprises with all kinds of economic activity and the values ​​of certain characteristics for each unit.

So, we have examined the forms, methods, types of statistical observation. Of course, we touched on them only briefly, but we noted the most important ones.