The processing of the collected primary data, including their grouping, generalization and presentation in tables, constitutes the second stage of the statistical study, which is called summary.

There are 3 main forms of presentation of processed statistical data: textual, tabular and graphical.

At the third stage of the statistical study, based on the final summary data, scientific analysis of the studied phenomena: various generalizing indicators are calculated in the form of average and relative values, certain patterns are identified in the distributions, dynamics of indicators, etc. Based on the identified patterns, forecasts are made for the future.

Statistical observation is the first stage of statistical research. Almost always, in accordance, of course, with the goals and objectives of the study, work begins with taking into account the facts and collecting primary material. Primary material is the foundation of statistical research. The success of the entire study as a whole depends on the quality of statistical observation. It should be organized in such a way that objective, accurate data about the phenomenon under study are obtained as a result. Incomplete, inaccurate data that do not characterize the process well enough, all the more distorting it, lead to errors. And the analysis carried out on such a basis will be erroneous. It follows that the accounting of facts and the collection of primary material must be carefully thought out and organized.

It should be noted once again that statistical observations are always massive. The law of large numbers comes into force - the larger the population, the more objective the results will be.

Statistical observation can be divided into three stages: 1. Preparation of observation. This is the formulation of the monitoring program, the definition of indicators grouped into layouts of the final statistical tables.

The questions that make up the content of the program should follow from the purpose of the study or the hypothesis that the study is supposed to confirm. An important element is the layouts of the final statistical tables. It is they who are the project for the development of the results of observation, and only if they are available, it is possible to identify all the issues that need to be included in the program and avoid including unnecessary information.

2. Direct collection of material. This is the most time-consuming part of the research. Statistical reporting as special form organization of data collection is inherent only in state statistics. All other information is collected through a variety of static tools. It is necessary to point out two main requirements for the collected data: reliability and comparability. And what is highly desirable (in market conditions, it increases many times over) is timeliness.

3. Control of the material before its analysis. No matter how carefully the observation tools are compiled, the performers are instructed, the observation materials always need to be controlled. This is due to the massive nature of statistical work and the complexity of their content.

The object of any statistical study is a set of units of the phenomenon under study. The object can be the population at the census, enterprises, cities, company personnel, etc. In a word, the object of observation is the statistical population under study. It is very important to define the boundaries of the population under study, which clearly define the population under study. For example, if the goal is to study the activities of small enterprises in the region, then it should be determined what form of ownership it belongs to (state, private, joint, etc.), according to what criterion enterprises will be selected: industry specifics, sales volume, time from the moment registration, status (active, inactive, temporarily idle), etc. The set must be homogeneous, otherwise additional difficulties will arise in the analysis process and errors are almost always inevitable.

Along with the definition of the object of observation and boundaries, it is important to determine the unit of the population and the unit of observation. A population unit is an individual constituent element of a statistical population. The unit of observation is the phenomenon, the object, the signs of which are subject to registration. The set of units of observation constitutes the object of observation. For example, the goal is to investigate the impact various factors on the labor productivity of workers at the mines of Ispat-Karmet OJSC. In this case - the population is defined by the goal itself - the miners working at the mines "Ispat-Karmet", the unit of the population is the miner as a carrier of information, and the unit of observation is the mine. Briefly: the unit of the population is what is being examined, the unit of observation is the source of information.
To carry out statistical observation, it is necessary to collect data on a given basis, namely: to designate a statistical population that consists of materially existing objects, a unit and the purpose of a one-time survey of an object, and draw up a program of statistical observation.

At the first stage, a sample collected data according to the indicated characteristics, the data are sorted in ascending order. Then, a frequency distribution table should be compiled with sequential filling in the corresponding columns in the table.

At the second stage, in order to process the collected primary data, it is necessary to group and generalize the selected elements according to a given attribute, to designate the numerical characteristics of the sample. This stage of statistical research is called summary. Summary - scientific processing of primary data in order to obtain generalized characteristics of the phenomenon under study according to a number of features that are essential for it, i.e. primary materials are brought together, form statistical aggregates, which are characterized by final absolute generalizing indicators. At the summary stage, we move from the characterization of individual varying features of the units of the population - to the characterization of the entire population as a whole or to the characterization of their general manifestation in the mass.

Should be found scope according to the formula:

R=x(max) - x(min);

fashion M(0), which shows the value that occurs most often, median M(e), which characterizes the average value (it does not exceed half of the members of the series) corresponds to the variant in the middle of the ranged variation series. The position of the median is determined by its number: Nme \u003d (n + 1) / 2, where n is the number of units in the population and average arithmetic value for the indicated group, which is calculated by the formula:

The results of the work can be presented graphically in the form of a histogram and a frequency distribution polygon.

The data obtained reflect the general that is inherent in all units of the studied population. As a result of statistical observation, objective, comparable, complete information should be obtained, which allows, at subsequent stages of the study, to provide evidence-based conclusions about the nature and patterns of development of the phenomenon under study.

Practical task

Conduct a statistical study to find out the information about growth 2 5 randomly selected students of the Tomsk Polytechnic University.

Make a frequency distribution table, find the range, mode, median and arithmetic mean of height (in cm) for the indicated young men.

To get an idea about a particular phenomenon, to draw conclusions, it is necessary to conduct a statistical study. The subject of statistical research in health care and medicine can be the health of the population, the organization of medical care, various sections of the activities of medical institutions, factors external environment that affect health status.

The methodical sequence of performing a statistical study consists of certain stages.

Stage 1. Drawing up a plan and program of research.

Stage 2. Collection of material (statistical observation).

Stage 3. Material development, statistical grouping and summary

Stage 4. Statistical analysis of the phenomenon under study, formulation of conclusions.

Stage 5 Literary processing and presentation of the results.

Upon completion of the statistical study, recommendations and management decisions are developed, the results of the study are put into practice, and efficiency is evaluated.

In conducting a statistical study, the most important element is the observance of a strict sequence in the implementation of these stages.

First stage statistical research - drawing up a plan and program - is preparatory, at which the purpose and objectives of the study are determined, a plan and research program are drawn up, a program for summarizing statistical material is developed and organizational issues are resolved.

When starting a statistical study, it is necessary to accurately and clearly formulate the purpose and objectives of the study, to study the literature on this topic.

The goal determines the main direction of research and is, as a rule, not only theoretical, but also practical. The goal is formulated clearly, clearly, unambiguously.

To disclose the goal, the research tasks are defined.

An important point preparatory phase is the development of an organizational plan. The organizational plan of the study provides for the definition of the place (administrative-territorial boundaries of the observation), time (specific terms for the implementation of the observation, development and analysis of the material) and the subject of the study (organizers, performers, methodological and organizational leadership, research funding sources).

Pl A n research d ov A nia includes:

Definition of the object of study (statistical population);

The scope of the study (continuous, non-continuous);

Types (current, one-time);

Ways to collect statistical information. Research program includes:

Definition of the unit of observation;

List of questions (accounting signs) to be registered in relation to each unit of observation*

Development of an individual accounting (registration) form with a list of questions and features to be recorded;

Development of table layouts, in which the results of the study are then entered.

A separate form is filled out for each unit of observation, it contains a passport part, clearly formulated questions of the program, put in a certain sequence, and the date of filling out the document.

As accounting forms, accounting medical forms used in the practice of medical institutions can be used.

Other medical records (medical histories, and individual cards outpatient, child development history, childbirth history), reporting forms of medical institutions, etc.

To enable the statistical development of data from these documents, information is copied onto specially designed accounting forms, the content of which is determined in each individual case in accordance with the objectives of the study.

At present, in connection with the machine processing of the results of observation using a computer, program questions can be formalized , when questions in the accounting document are put in the form of alternatives (yes, no) , or ready-made answers are offered, from which a specific answer should be selected.

At the first stage of the statistical study, along with the observation program, a program * of the summary of the data obtained is compiled, which includes the establishment of the principles of grouping, the selection of grouping characteristics , determination of combinations of these signs, drawing up layouts of statistical tables.

Second phase- collection of statistical material (statistical observation) - consists in the registration of individual cases of the phenomenon under study and the accounting signs characterizing them in registration forms. Before and during the performance of this work, instruction (oral or written) of the observers is carried out, and they are provided with registration forms.

In terms of time, statistical observation can be current and one-time.

At current observation Yu denia the phenomenon is studied for some separate period of time (week, quarter , year, etc.) by daily recording of the phenomenon as each case occurs. An example of a current observation is accounting for the number of births , dead, sick , discharged from the hospital, etc. This takes into account rapidly changing phenomena.

At one-time observation Yu denia statistical data are collected at a certain (critical) point in time. One-time observations are: a population census, a study of the physical development of children, accounting for hospital beds for horses of the year, certification of medical institutions, etc. Preventive examinations of the population also belong to this type. One-time registration reflects the state of the phenomenon at the time of study. This type of observation is used to study slowly changing phenomena.

The choice of the type of observation over time is determined by the purpose and objectives of the study. For example, the characteristics of hospitalized patients can be obtained as a result of the current registration of those who left the hospital (current observation) or by a one-day census of patients who are in the hospital (one-time observation).

Depending on the completeness of the coverage of the phenomenon under study, a continuous and non-continuous study is distinguished.

At continuous The study studies all the units of observation included in the population, i.e. the general population. A continuous study is carried out in order to establish the absolute dimensions of the phenomenon, for example, the total population, the total number of births or deaths, total number sick with a particular disease, etc. The continuous method is also used in cases where information is necessary for operational work (accounting for infectious diseases, the workload of doctors, etc.)

At discontinuous The study examines only part of the general population. It is divided into several types: questionnaire, monographic, main array, selective. The most common method in medical research is the sampling method.

Monographic method- gives a detailed description of individual units of the population, characteristic in any respect, and a deep, comprehensive description of objects.

Main Array Method- involves the study of those objects in which the vast majority of units of observation are concentrated. The disadvantage of this method is that a part of the population remains uncovered by the study, although small in size, but which can differ significantly from the main array.

Questionnaire method- this is the collection of statistical data using specially designed questionnaires addressed to a certain circle of people. This study is based on the principle of voluntariness, so the return of questionnaires is often incomplete. Often the answers to the questions posed bear the imprint of subjectivity and chance. This method is used to obtain an approximate description of the phenomenon under study.

Sampling method- is reduced to the study of some specially selected part of the units of observation to characterize the entire general population. This method has the advantage of obtaining results with a high degree of reliability as well as a significantly lower cost. The study employs a smaller number of performers , moreover, it requires less time.

In medical statistics, the role and place of the sampling method is especially great, since medical workers usually deal with only a part of the phenomenon under study: they study a group of patients with a particular disease, analyze the work of individual departments and medical institutions , evaluate the quality of certain events, etc.

According to the method of obtaining information in the course of statistical observation and the nature of its implementation, several types are distinguished:

1) direct observation(clinical examination of patients , conducting laboratory , instrumental research , anthropometric measurements, etc.)

2) sociological methods: interview method (face-to-face survey), questioning (correspondence survey - anonymous or non-anonymous), etc .;

3) documentary research A nie(copy of information from accounting and reporting medical documents, information from official statistics of institutions and organizations.)

Third stage- grouping and summary of material - begins with checking and clarifying the number of observations , completeness and correctness of the information received , identifying and eliminating errors, duplicate records, etc.

For the correct development of the material, encryption of primary accounting documents is used. , those. designation of each feature and its group with a sign - alphabetic or numeric. Encryption is a technique , facilitating and accelerating material development , improving the quality, accuracy of development. Ciphers - symbols - are developed arbitrarily. When coding diagnoses, it is recommended to use the international nomenclature and classification of diseases; when coding professions - a dictionary of professions.

The advantage of encryption is that, if necessary, after the end of the main development, you can return to the material for development in order to clarify new relationships and dependencies. Encrypted accounting material makes it easier and faster , than unencrypted. After checking, the features are grouped.

grouping- division of the totality of the studied data into homogeneous , typical groups according to the most significant features. Grouping can be carried out on qualitative and quantitative grounds. The choice of a grouping feature depends on the nature of the studied population and the objectives of the study.

Typological grouping is carried out according to qualitative (descriptive, attributive) features, for example, by gender , profession, disease groups, severity of the course of the disease, postoperative complications, etc.

Grouping by quantitative (variation) features is carried out on the basis of the numerical size of the feature , For example , by age , the duration of the disease, the duration of treatment, etc. Quantitative grouping requires a solution to the question of the size of the grouping interval: the interval can be equal, and in some cases - unequal, even include the so-called open groups.

For example , when grouping by age, open groups can be determined: up to 1 year . 50 years and older.

When determining the number of groups proceed from the purpose and objectives of the study. It is necessary that groupings could reveal the patterns of the phenomenon under study. A large number of groups can lead to excessive crushing of the material, unnecessary detailing. A small number of groups leads to shading characteristic features.

Having finished grouping the material, proceed to the summary.

WITH vodka- generalization of isolated cases , received as a result of a statistical study, into certain groups, their calculation and inclusion in the layout tables.

A summary of the statistical material is carried out using statistical tables. Table , not filled with numbers , called a layout.

Statistical tables are list , chronological, territorial.

The table has a subject and a predicate. The statistical subject is usually placed on horizontal lines on the left side of the table and reflects the main, main feature. The statistical predicate is placed from left to right along the vertical columns and reflects additional accounting features.

Statistical tables are divided into simple , group and combination.

IN simple tables the numerical distribution of the material according to one attribute is presented , its constituent parts (Table 1). A simple table usually contains a simple list or summary of the totality of the phenomenon under study.

Table 1

Distribution of the dead in the N. hospital by age

IN group tables presents a combination of two signs in connection with each other (Table 2).

table 2

Distribution of the dead in N. hospital by sex and age

IN combin A qi O these tables the distribution of the material according to three or more interrelated features is given (Table 3).

Table 3

Distribution of deaths in N. hospital with different diseases by age and sex

Diagnosis of the underlying disease	Age
0-14	15-19	20-39	40-59	60 and >	Total
m	and	m	and	m	and	m	and	m	and	m	and	m+f
Diseases of the circulatory system.	-	-	-	-
Injury and poisoning		-		-					-
malignancy. neoplasms.	-	-	-	-	-	-
Other zab.	-	-	-	-
Everyone got sick.		-		-

When compiling tables, certain requirements must be met:

Each table should have a heading that reflects its content;

Within the table, all columns should also have clear, concise titles;

When filling out the table, all cells of the table must contain the corresponding numerical data. The cells of the table remaining blank due to the absence of this combination are crossed out ("-"), and in the absence of information in the cell, "n.s." or "...";

After filling the table in the bottom horizontal row and in the last vertical column on the right, the results of vertical columns and horizontal lines are summed up.

Tables must have a single sequential numbering.

In studies with a small number of observations, summarization is done manually. All accounting documents are decomposed into groups in accordance with the sign code. Next, the data is calculated and recorded in the corresponding cell of the table.

Currently, computers are widely used in sorting and summarizing material. . which allow not only to sort the material according to the studied characteristics , but do the calculations.

Fourth stage- statistical analysis - is a crucial stage of the study. At this stage, the calculation of statistical indicators (frequency , structures , the average size of the phenomenon under study), their graphic representation is given , dynamics , trends, connections between phenomena are established . forecasts are given, etc. The analysis involves the interpretation of the data obtained, the assessment of the reliability of the results of the study. In conclusion, conclusions are drawn.

Fifth stage- Literary processing is final. It involves the finalization of the results of a statistical study. The results can be presented in the form of an article, report, report , dissertations, etc. There are certain requirements for each type of design , which must be observed in the literary processing of the results of a statistical study.

The results of medical and statistical research are being introduced into healthcare practice. Various options for using the results of the study are possible: familiarization with the results of a wide audience of medical and scientific workers; preparation of instructive and methodological documents; formulation of a rationalization proposal and others.

STATISTICAL VALUES

For a comparative analysis of statistical data, statistical values ​​are used: absolute , relative , medium.

Absolute values

The absolute values ​​obtained in the summary tables during the statistical study reflect the absolute size of the phenomenon (number of health care facilities, number of hospital beds, population , the number of deaths, births, illnesses, etc.). A number of statistical studies ends with obtaining absolute values. In some cases, they can be used to analyze the phenomenon under study. , For example , when studying rare phenomena , if necessary, know the exact absolute size of the phenomenon , if necessary, pay attention to individual cases of the phenomenon under study, etc. With a small number of observations , in the case when it is not required to determine the regularity , absolute numbers can also be used.

In a significant proportion of cases, absolute values ​​cannot be used for comparison with data from other studies. For this, relative and average values ​​are used.

Relative values

Relative values ​​(indicators , coefficients) are obtained as a result of the ratio of one absolute value to another. The most commonly used indicators are: , extensive, ratios , visibility.

Intensive- frequency indicators , intensity, prevalence of the phenomenon in the environment , producing this phenomenon. In health care, morbidity is being studied , mortality , disability, birth rate and other indicators of population health. Wednesday , in which the processes take place is the population as a whole or its individual groups (age, gender, social , professional, etc.). In medical-statistical studies, a phenomenon is, as it were, a product of the environment. For example , population (environment) and sick (phenomenon); sick (environment) and dead (phenomenon), etc.

The value of the base is selected in accordance with the value of the indicator - by 100, 1000, 10000, 100000, depending on this, the indicator is expressed as a percentage , ppm , prodecimille, prosantimille.

The intensive indicator is calculated as follows: for example, in Iran in 1995. 67283 thousand inhabitants lived, 380200 people died during the year.

Intensive indicators can be general and special.

General intensive indicators characterize the phenomenon as a whole . For example , total fertility rates , mortality, morbidity, calculated for the entire population of the administrative territory.

Special intensive indicators (by group) are used to characterize the frequency of the phenomenon in different groups (morbidity by sex, age , mortality among children under 1 year of age , lethality for individual nosological Forms, etc.).

Intensive indicators are used: to determine the level . frequencies , prevalence of the phenomenon; to compare the frequency of the phenomenon in two different populations; for learning changes in the frequency of the phenomenon in dynamics.

extensive- indicators of specific gravity, structure, characterize the distribution of the phenomenon into its constituent parts, its internal structure. Extensive indicators are calculated by the ratio of the part of the phenomenon to the whole and are expressed in percentages or fractions of a unit.

The extensive indicator is calculated as follows: for example, in Greece in 1997 there were 719 hospitals, including 214 general hospitals.

Extensive indicators are used to determine the structure of the phenomenon and a comparative assessment of the ratio of its constituent parts. Extensive indicators are always interconnected, since their sum is always equal to 100 percent: for example, when studying the structure of morbidity, the proportion of an individual disease may increase with its true growth; at the same level, if the number of other diseases has decreased; with a decrease in the number of this disease , if the decrease in the number of other diseases occurs at a faster rate.

Ratios- represent the ratio of two independent, independent of each other , qualitatively different values. Correlation indicators include indicators of provision of the population with doctors, secondary medical workers, hospital beds, etc.

The calculation of the ratio indicator is as follows: for example, in Lebanon with a population of 3789 thousand inhabitants in medical institutions in 1996 there were 3941 doctors.

visibility- are used for the purpose of a more visual and accessible comparison of statistical values. Visualization metrics provide a convenient way to convert absolute, relative, or average values ​​into an easy-to-compare Form. When calculating these indicators, one of the compared values ​​is equated to 100 (or 1), and the remaining values ​​are recalculated accordingly to this number.

The visibility indicators are calculated as follows: for example, the population of Jordan was: in 1994. - 4275 thousand people, in 1995 - 4440 thousand people , in 1996 - 5439 thousand people.

Visibility indicator: 1994-100%;

1995	=	4460 *100	=	103.9%;
1996	=	5439*100	=	127.2%

The visibility indicators indicate by how many percent or how many times there was an increase or decrease in the compared values. Visual indicators are most often used to compare data over time , to present the patterns of the phenomenon under study in a more visual form.

When using relative values, some errors can be made. Here are the most common ones:

1. Sometimes a change in the frequency of a phenomenon is judged on the basis of extensive indicators that characterize the structure of the phenomenon, and not its intensity.

3. When calculating special indicators, you should choose the right denominator for calculating the indicator: for example , the postoperative mortality rate should be calculated in relation to the operated , not all patients.

4. When analyzing indicators, the Time factor should be taken into account:

it is impossible to compare indicators calculated for different periods of time: for example, the incidence rate for a year and for half a year , which can lead to erroneous judgments. 5. It is impossible to compare with each other the general intensive indicators calculated from sets that are heterogeneous in composition, since the heterogeneity of the composition of the medium can affect the value of the indicator.

Average values

Average values ​​give a generalizing characteristic of the statistical population according to a certain changing quantitative attribute.

The average value characterizes the entire series of observations with one number, expressing the general measure of the trait under study. It levels out random deviations of individual observations and gives a typical characteristic of a quantitative trait.

One of the requirements when working with averages is the qualitative homogeneity of the population for which the average is calculated. Only then will it objectively reflect the characteristic features of the phenomenon under study. The second requirement is that the average value only expresses the typical sizes of a trait when it is based on a mass generalization of the studied trait, i.e. calculated on a sufficient number of observations.

Average values ​​are obtained from distribution series (variation series).

Variation series- a number of homogeneous statistical values ​​characterizing the same quantitative accounting attribute, differing from each other in their value and arranged in a certain order (decreasing or increasing).

The elements of the variation series are:

Option- v - numerical value of the studied changing quantitative trait.

Frequency- p (pars) or f (frequency) - the frequency of a variant in a variation series, showing how often one or another variant occurs in this series.

Total number of observations- n (numerus) - sum of all frequencies: n=ΣΡ. If the total number of observations is more than 30, the statistical sample is considered large; if n is less than or equal to 30, it is considered small.

Variational series are discontinuous (discrete), consisting of integers, and continuous, when the values ​​​​of the variant are expressed as a fractional number. In discontinuous rows, adjacent options differ from each other by an integer, for example: the number of pulse beats, the number of breaths per minute, the number of days of treatment, etc. In continuous series, options can differ by any fractional value of one. Variation series are of three types. Simple- a series in which each option occurs once, i.e. frequencies are equal to one.

ABOUT bovine A series in which variants occur more than once.

grouped A ny- row. in which the options are combined into groups according to their size within a certain interval, indicating the frequency of occurrence of all options included in the group.

A grouped variational series is used with a large number of observations and a sick range of extreme values ​​of the variant.

The processing of the variational series consists in obtaining the parameters of the variational series (mean value, standard deviation and average error of the mean value).

Types of averages.

In medical practice, the following averages are most often used: mode, median, arithmetic mean. Less commonly used are other averages: geometric mean (when processing the results of titration of antibodies, toxins, vaccines); root mean square (when determining the average diameter of a section of cells, the results of skin immunological tests); average cubic (to determine the average volume of tumors) and others.

Fashion(Mo) - the value of the trait, most often found in the aggregate. For fashion, they take the variant to which it corresponds the largest number frequencies of the variation series.

Median(Me) - the value of the trait, which occupies the median value in the variation series. It divides the variation series into two equal parts.

The magnitude of the mode and median is not affected by the numerical values ​​of the extreme options available in the variation series. They cannot always accurately characterize the range of variations and are relatively rarely used in medical statistics. The arithmetic mean value characterizes the variation series more accurately.

WITH arithmetic mean(M, or) - is calculated on the basis of all numerical values ​​of the studied trait.

In a simple variational series, where options occur only once, the simple arithmetic mean is calculated using the formula:

Where V - numerical values ​​option,

n - number of observations,

Σ - sum sign

In the usual variational series, the arithmetic weighted average is calculated by the formula:

Where V is the numeric values ​​of the option.

Ρ - frequency of occurrence of the variant.

n is the number of observations.

S - sum sign

An example of calculating the arithmetic weighted average is shown in Table 4.

Table 4

Determination of the average duration of treatment of patients in a specialized department of the hospital

In the example above, the mode is 20 days, since it is repeated more often than others - 29 times. Mo = 20. Serial number median is determined by the formula:

The place of the median falls on the 48th option, the numerical value of which is 20. The arithmetic mean, calculated by the formula, is also 20.

Mean values ​​are important generalizing characteristics of the population. However, individual values ​​of the attribute are hidden behind them. Average values ​​do not show variability, fluctuation of the trait.

If the variation series is more compact, less scattered, and all individual values ​​are located around the average, then the average value gives a more accurate description of this population. If the variation series is stretched, the individual values ​​deviate significantly from the average, i.e. there is a large variability of a quantitative trait, then the average is less typical, worse reflects the entire series as a whole.

Averages of the same magnitude can be obtained from series with different degrees of dispersion. So, for example, the average duration of treatment of patients in a specialized department of a hospital will also be 20 if all 95 patients were in hospital for 20 days. Both calculated averages are equal to each other, but obtained from series with varying degrees of variation.

Therefore, to characterize the variation series, in addition to the average value, another characteristic is needed , allowing to estimate the degree of its fluctuation.

received materials.

summary indicators.

Each observation is carried out with a specific purpose. When conducting it, it is necessary to establish what is to be examined. The following questions need to be addressed:

Object of observation

Unit of observation

Qualification

sign

The observation program is drawn up in the form of forms (questionnaires, forms), in which primary data are entered. A necessary addition to the forms is an instruction that explains the meaning of the questions.

terms of observation;

preparatory work;

For example, the critical moment of the micro-census of 1994. was 0.00 am on the night of February 13-14. By establishing the critical moment of observation, one can determine the true state of affairs with photographic accuracy.

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Stages of statistical research. Collected during the first stage of statistical research - statistical observation - data on the value of any feature of the studied population

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Collected during the first stage of the statistical study - statistical observation - data on the value of any feature of the studied population should be processed in such a way that an accurate and detailed answer to all the questions posed by the purpose of the study is obtained. The task of the second stage of statistical research is statistical processing (summaries) - consists in ordering and generalizing the primary material, bringing it into groups and, on this basis, giving a generalized description of the totality. The quality of the initial statistical material predetermines the quality of the generalizing indicators obtained as a result of the statistical summary.

Distinguish summary simple and complex (statistical grouping).

Simple Summary is an operation to calculate the totals for a set of units of observation. Complex summary - this is a set of operations that includes grouping observation units, counting the totals for each group and for the entire population, and presenting the results of the summary and grouping in the form of statistical tables.

Statistical grouping is reduced to the division of the population into groups according to to the selected feature essential for the units of the population (grouping feature ). The choice of a grouping feature, i.e. sign , according to which the units of the studied population are united into groups, - one of the most significant and complex issues in the theory of grouping and statistical research . From right choice grouping trait often depend on the results of the entire statistical study.

Statistical observation. Stages of statistical research

Grouping makes it possible to obtain such results by which it is possible to identify the composition of the population, the characteristic features and properties of typical phenomena, to discover patterns and relationships.

The simplest and most commonly used way of summarizing statistical data is distribution ranks . The statistical series (law) of distribution is the numerical distribution of units of the population according to the trait under study. Let some SW be discrete, i.e. can only take fixed (on some scale) values X i . In this case, a series of probabilities P(X i) for all ( i=1, 2, …, n) admissible values ​​of this quantity is called its distribution law.

Depending on the grouping feature used, statistical series can be attributive and variational (quantitative).

Attribute rows distributions reflect the qualitative state of the units of the population (gender of a person, Family status, industry affiliation of the enterprise, its form of ownership, etc.), and variational - have a numerical expression (production volume, family income, age of a person, academic score, etc.).

An example of an attribute series is the distribution of students in a group by gender.

Variational (quantitative) grouped series can be discrete or interval . A discrete variational distribution series is a series in which the numerical distribution of population units according to a discrete attribute is expressed as an integer finite value. An example is the distribution of workers by category, the distribution of city families by the number of children, and so on. An interval distribution series is a series in which the characteristic values ​​are given as an interval. The construction of interval variation series is expedient, first of all, for random variables characterized by a continuous variation of a feature (i.e., when the value of a feature in population units can take on any values, even if within certain limits).

So, the probability distribution law of a discrete SW carries all the information about it. This law (or simply the distribution random variable) can be specified in three ways:

— in the form of a table of quantity values ​​and their corresponding probabilities;

- in the form of a diagram or, as it is sometimes called, a distribution histogram;

- in the form of a formula, for example, for normal, binomial, etc. distribution.

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Stages of statistical research

Stages of statistical research.

Statistical study- this is a collection, summary and analysis of data (facts) on socio-economic, demographic and other phenomena and processes, scientifically organized according to a single program public life in the state with the registration of their most significant features in the accounting documentation.

Distinctive features (specifics) of statistical research are: purposefulness, organization, mass character, consistency (complexity), comparability, documentation, controllability, practicality.

Statistical research consists of three main stages:

1) collection of primary statistical information(statistical observation) - observation, collection of data on the values ​​of the studied attribute of units of statistical cos-ty, kt is the foundation of future statistical analysis. If a mistake was made during the collection of primary statistical data or the material turned out to be of poor quality, this will affect the correctness and reliability of both theoretical and practical conclusions.

2) statistical summary and processing of primary information- Data is organized and grouped. The results of statistical grouping and summaries are presented in the form of statistical tables, which is the most rational, systematized, compact and visual form of presentation of mass data.

3) generalization and interpretation of statistical information- analysis of statistical information.

All these stages are interconnected, the absence of one of them leads to a break in the integrity of the statistical study.

Stages of stat research

1. Goal setting

2. Definition of the object of observation

3. Definition of units of observation

4. Drawing up a research program

5. Drawing up instructions for filling out the form

6. Summary and grouping of data (brief analysis)

Basic concepts and categories of statistical science.

1. Statistical population is a set of phenomena that have one or more common features and differing from each other in the values ​​of other signs. Such, for example, are the totality of households, the totality of families, the totality of enterprises, firms, associations, etc.

2. Sign - this property, a characteristic feature of the phenomenon, subject to statistical study

3. Statistical indicator- this is a generalizing quantitative characteristic of the social economy of phenomena and processes in their qualitative certainty in the conditions of a particular place and time. Statistical indicators can be divided into two main types: accounting and estimated indicators (sizes, volumes, levels of the phenomenon under study) and analytical indicators (relative and average values, variation indicators, etc.).

4. Unit of owls- this is each individual, subject to statistical study.

5. Variation- this is the variability of the magnitude of the attribute in individual units of co-phenomena.

6. Regularity- called the repetition and order of change in phenomena.

The main stages of statistical observation.

St-some observation is a scientifically based collection of data on the social economy phenomenon of social life.

CH stages:

1. Preparation for statistical observation - involves the use of the method of mass observations, which is nothing more than the collection of primary statistical information. (solution of scientific, methodological and organizational and technical issues).

2. Summary and grouping of primary stats- the collected information is summarized and distributed in a certain way using the method of stat groupings. including work, begins with the distribution of census forms, questionnaires, forms, statistical reporting forms and ends with their submission after filling in to the bodies conducting the observation.

3. Analysis of statistical information- using the method of generalizing indicators, the analysis of statistical information is carried out.

4. Development of proposals for improving the CH- analyzes the reasons that led to the incorrect filling of statistical forms and develops proposals for improving the observation.

Obtaining information during CT SN requires a considerable amount of financial labor and time. (opinion polls)

Grouping statistics.

grouping- this is the division of owls into groups according to essential features.

Reasons for grouping: the originality of the object of the statistical study.

The grouping method solves the following problem: allocation of socio-economy types and phenomena; study of the structure of the phenomenon and structural changes occurring in it; revealing the relationship and dependence between phenomena.

These tasks are solved with the help of typological, structural and analytical groupings.

Typological group– identification of types of social-economic phenomena (group of industrial enterprises by form of ownership)

Structural group– study of structure and structural shifts. With the help of such groups, the following can be studied: the composition of us-I by gender, age, place of residence, etc.

Analytical group- identifying the relationship between features.

Stages of building SG:

1.selection of a grouping feature

2.determination of the required number of groups, into kt it is necessary to divide the studied owl

3. set the boundaries of the gr-ki intervals

4. setting for each group of indicators or their system, which should characterize the selected groups.

grouping systems.

Grouping system- this is a series of interrelated statistical groupings according to the most significant features, comprehensively reflecting the most important aspects of the phenomena under study.

Typological group- this is the division of the studied qualitatively heterogeneous society into classes, social-economy types (group of industrial enterprises by form of ownership)

Structural group- characterizes the composition of a homogeneous cos-ty according to certain characteristics. With the help of such groups, the following can be studied: the composition of us-I by gender, age, place of residence, etc.

Analytical group- are used in the study of the relationship between the signs, one of the kt is factorial (influences the change in performance), the other is productive (features that change under the influence of factors).

Construction and types of distribution series.

Stat number of distribution- this is an ordered distribution of units of owls into groups according to a certain varying trait.

Distinguish: attributive and variational happy distributions.

Attributive- these are r.r., built on qualitative grounds. R.r. taken in the form of tables. They characterize the composition of the owls according to the existing features, taken over several periods, these data allow us to study the change in the structure.

variational are r.r. built on a quantitative basis. Any variation series consists of 2 elements: variants and frequencies.

Options individual values ​​of the attribute are considered, which it takes in the variation series, i.e.

specific value of the variable attribute.

Frequencies- this is the number of individual options or each group of the variation series, i.e. these are numbers showing how often certain variants occur in the r.r.

Variation row:

1.discrete- characterizes the distribution of units of owls on a discrete basis (the distribution of families according to the number of rooms in individual apartments).

2.interval– the feature is presented as an interval; it is expedient first of all at a continuous variation of a sign.

The most convenient r.r. analyze with them. graphic image, which makes it possible to judge the form of distribution. A visual representation of the nature of the change in the frequencies of the variational series is given by a polygon and a histogram, there is an ogive and a cumulate.

Statistical tables.

ST is a rational and common form of presenting statistical data.

The table is the most rational, visual and compact form of presentation of statistical material.

The main techniques that determine the technique for the formation of ST trace:

1. T should be compact and contain only those initial data that directly reflect the studied socio-economy phenomenon in the article.

2. The heading of the table and the names of the columns and lines should be clear and concise.

3.inf-tion is located in the columns (columns) of the table, ends with a summary line.

5. it is useful to number columns and lines, etc.

According to the logical content, STs are a “stat sentence”, the main elements being the subject and the predicate.

Subject the name of the object, characterized by numbers. this is m.b. one or more owls, otd units of owls.

Predicate ST are indicators that characterize the object of study, i.e. the subject of the table. The predicate is the top headings and the state of the content column from left to right.

9. The concept of absolute value in statistics .

Stat pok-whether is a qualitatively defined variable that quantitatively characterizes the object of study or its properties.

A.v.- this is a generalizing indicator that characterizes the size, scale or volume of a particular phenomenon in specific conditions of place and time.

Ways of expression: natural units (t., pcs., quantity); labor dimension (slave. Wr, labour); value expression

How to get: registration of facts, summary and grouping, calculation according to defined methodology (GDP, ratings, etc.)

Types of AB: 1.individual AB - characterize individual elements of general phenomena 2. Total AB - har-t indicators for co-objects.

Absolute change (/_\) is the difference between 2 AB.

Stages and methods of statistical research

Statistical research consists of three main stages:

Statistical observation is the first stage. In the course of it, primary statistical information and data are collected, which will become the basis for future statistical analysis. Statistical observation methods are represented by censuses, statistical reporting, questioning, and selective observation.

Statistical summary is the second stage. In the course of it, the processing of primary information takes place; specific single information is summarized, forming a set in order to identify typical features and patterns inherent in the phenomenon under study as a whole. The main method of statistical summary is grouping, when the studied phenomena are divided into the most important types, characteristic groups and subgroups according to essential features. The results of the statistical grouping and summaries are presented in the form of tables and graphs.

Generalization and analysis of statistical information is the third stage. Statistical analysis is the final stage of statistical research.

The main stages of the analysis are the following:

1. establishing the facts and their assessment;

2. establishing the characteristic features and causes of the phenomenon;

3. comparison of the phenomenon with the basic phenomena - normative, planned and others;

4. formulation of hypotheses, conclusions and assumptions;

5. statistical verification of the hypotheses put forward with the help of special generalizing statistical indicators.

General indicators- absolute, relative, average values ​​and index systems - are used at this stage. Common features the formation of generalizing indicators are established by measuring their deviations and bringing them to an average indicator. The study of deviations - "variations" - together with the use of average and relative values ​​is of great practical and scientific importance. Indicators of deviations of "variations" characterize the degree of homogeneity of the statistical population according to the desired attribute. Indicators of "variations" determine the degree and boundaries of variation. Of considerable interest is the relationship of signs of "variations".

All these three stages are inextricably linked by an organic unity. Thus, statistical observation is meaningless without further analysis, and analysis is impossible without information obtained at the stage of primary data processing.

The processing of empirical research data is usually divided into several stages:

1) Primary data processing:

- Compilation of tables;

— Transformation of the form of information;

- Data checking.

2) Statistical data analysis:

— Analysis of primary statistics;

— Evaluation of the reliability of differences;

— Data normalization;

— Correlation analysis;

- Factor analysis.

In most cases, it is advisable to start data processing with the compilation of pivot tables.

Pivot data table- this is a kind of "accumulator" of all the data obtained as a result of the study, ideally it should contain the data of all subjects according to all research methods. Pivot tables are usually compiled in Microsoft Office Excel, or Word, Access.

The basis for the pivot table of the source data is the following form. Each line contains the values ​​of all indicators of one subject. Each column (field) contains the values ​​of one indicator for all subjects. Thus, in each cell (cell) of the table, only one value of one indicator of one subject is recorded. The topmost line contains the subject's number in order, full name (or some other identifier), measured indicators, scale ratings, etc. This line makes it easier to navigate the table. In each subsequent line, the name of the subject and the values ​​​​of all parameters measured from him are recorded; of course, for all subjects in the same order of indicators.

Subjects can be listed in alphabetical order, but it is better to use this principle at the lowest level of division. First, it is better to divide the subjects according to their belonging to any subgroups that will be compared with each other. Within these subgroups, it is useful to sort the subjects by gender, age, or another parameter that is important to you.

Transformation of the form of information.

It is advisable to enter all the signs of interest to you in the table in the form of a decimal number, that is, pre-calculate minutes into decimal fractions of an hour, seconds into decimal fractions of a minute, the number of months into a decimal fraction of a year, etc. This is necessary because the data format for most computer programs in use today imposes its own limitations. Also, try not to enter various text characters (periods, commas, dashes, etc.) into the table without special need.

All information that can be encoded by numbers is better converted into numerical form. This will provide more opportunities for different types data processing. The exception is the first line, which contains the names (more often short names– abbreviations) of measured indicators. In the form of numbers in the table, you can enter information about those parameters of the sample that can supposedly be significant factors, but you have in qualitative terms.

Methods and main stages of statistical research

The simplest operations can be: numerical coding (men - 1, women - 2; trained - 1, not passed - 2, etc.) and the conversion of qualitative indicators into ranks.

Data checking.

After creating a table on paper or computer, it is necessary to check the quality of the received data. To do this, it is often enough to carefully examine the data array. You should start checking by identifying errors (typos), which consist in the fact that the order of the number is written incorrectly. For example, 100 is written instead of 10, 9.4 is written instead of 94, etc. If you look closely at the columns, this is easy to detect, since parameters that vary greatly are relatively rare. Most often, the values ​​of one parameter have the same order or nearest orders. When collecting data on a computer, it is important to comply with the requirements for the data format in the statistical program used. First of all, this applies to the sign, which must separate the integer part from the fractional part in a decimal number (dot or comma).

The use of methods of mathematical statistics in the processing of primary empirical data is necessary to improve the reliability of conclusions scientific research. At the same time, it is not recommended to limit the use of indicators such as arithmetic averages and percentages. They most often do not provide sufficient grounds for reasonable conclusions from empirical data.

The choice of the method of statistical analysis of the obtained empirical data is a very important and responsible part of the study. And it's better to do it before the data is received. When planning a study, it is necessary to think in advance which empirical indicators will be recorded, by what methods they will be processed, and what conclusions can be drawn with different processing results.

When choosing a statistical criterion it is necessary, first of all, to identify the type of variables (features) and the scale of measurement that was used when measuring indicators and other variables - for example, age, family composition, level of education. Variables can be any indicators that can be compared with each other (that is, measured). It should be borne in mind that nominative and ordinal scales can be widely used in studies: verbal and non-verbal behavioral responses, gender, level of education - all this can be considered as variables. The main thing is to have clear and precise criteria for assigning them to one type or another, depending on the hypotheses and tasks set.

When choosing a statistical criterion, one should also focus on the type of data distribution that was obtained in the study. Parametric tests are used when the distribution of the received data is considered to be normal. A normal distribution is more likely (but not necessarily) to be obtained with samples of more than 100 subjects (it may work with a smaller number, or it may not work with a larger number). When using parametric criteria, it is necessary to check the normality of the distribution.

For nonparametric criteria, the type of data distribution does not matter. With small sample sizes of subjects, it is advisable to choose non-parametric criteria that give greater reliability to the conclusions, regardless of whether the study obtained normal distribution data. In some cases, statistically valid conclusions can be drawn even with samples of 5-10 subjects.

Many studies look for differences in measured indicators among subjects with certain characteristics. When processing relevant data, criteria can be used to identify differences in the level of the trait under study or in its distribution. To determine the significance of differences in the manifestation of a trait in studies, indicators such as the paired Wilcoxon test, the Mann-Whitney U-test, the x-square (x2) test, Fisher's exact test, and the binomial test are often used.

In many studies, the search for the relationship of the studied indicators in the same subjects is carried out. Correlation coefficients can be used to process the relevant data. The relationship of values ​​with each other and their dependence is often characterized by Pearson's linear correlation coefficient and Spearman's rank correlation coefficient.

The data structure (and, accordingly, the structure of the studied reality), as well as their relationship, is revealed by factor analysis.

In many studies, it is of interest to analyze the variability of a trait under the influence of any controlled factors, or, in other words, to assess the influence of various factors on the studied trait. For mathematical data processing in such problems, the Mann-Whitney U-test, the Kruskal-Wallis test, the Wilcoxon T-test, the ? 2 Friedman. However, to study the influence, and even more so the mutual influence of several factors on the parameter under study, analysis of variance may be more useful. The researcher proceeds from the assumption that some variables can be considered as causes, and others as consequences. Variables of the first kind are considered factors, while variables of the second kind are considered to be effective features. This is the difference between analysis of variance and correlation analysis, in which it is assumed that changes in one attribute are simply associated with certain changes in another.

In many studies, the significance of changes (shift) of any parameters and manifestations over a certain period of time, under certain conditions (for example, under conditions of corrective action) is revealed. Formative experiments in practical psychology solve precisely this problem. To process the relevant data, coefficients can be used to assess the reliability of the shift in the values ​​of the trait under study. For this, sign criteria, the Wilcoxon T-test, are often used.

It is important to pay attention to the limitations that each criterion has. If one criterion is not suitable for the analysis of the available data, it is always possible to find some other one, perhaps by changing the type of presentation of the data itself. Before doing statistical analysis of empirical data, it is useful to check whether there are critical values ​​corresponding to the amount and type of your data. Otherwise, you may be disappointed when your calculations turn out to be in vain due to the absence of critical values ​​​​in the table with the sample size that you had.

After getting acquainted with the procedure for calculating the criterion, you can carry out "manual" data processing or use the statistical program of a personal computer.

For computer processing, the most popular programs are SPSS and Statistica.

The use of statistical programs in computer processing speeds up the processing of the material by several orders of magnitude and provides the researcher with such methods of analysis that cannot be implemented in manual processing. However, these advantages can be fully utilized if the researcher has the necessary level of training in this area. Usually, the more powerful a computer program (the more powerful it is), the more time it takes to master. Thus, spending time studying it with rare access to a powerful statistical apparatus is not entirely effective. Very often, the use of such programs to solve even simple tasks also requires a certain amount of skills.

In order to avoid unnecessary difficulties and time costs, it is much more effective to turn to professionals. They will qualitatively and professionally carry out all the necessary mathematical and statistical analysis of your research data: analysis of primary statistics, assessment of the reliability of differences, data normalization, correlation and factor analysis, etc.

After carrying out the necessary statistical analysis of the data, it is necessary to correlate the results obtained with the initially posed hypothesis, with the theoretical justifications of the authors who have studied this topic and previous researchers. Formulate conclusions and interpret the results.

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Main stages of statistical research

Consider the most important method of statistics - statistical observation.

Usage various ways and techniques of statistical methodology

requires the availability of comprehensive and reliable information about the studied

object. The study of mass social phenomena includes the stages of collecting

statistical information and its primary processing, information and grouping

observation results in certain aggregates, generalization and analysis

received materials.

At the first stage of statistical research, primary

statistical data, or raw statistical information that

is the foundation of the future statistical building. For the building to be

solid, solid and high-quality should be its basis. If when collecting

primary statistical data, an error was made or the material turned out to be

poor quality, it will affect the correctness and reliability of both

theoretical as well as practical findings. Therefore, statistical

observation from the initial to the final stage - obtaining the final

materials - should be carefully thought out and clearly organized.

Statistical observation provides the source material for generalization, the beginning

which serves as a summary. If during statistical observation about each of its

unit receive information that characterizes it from many sides, then the data

summaries characterize the entire statistical population and its individual parts.

At this stage, the population is divided according to the signs of difference and combined according to

signs of similarity, total indicators are calculated for groups and in

in general. Using the grouping method, the studied phenomena are divided into the most important

types, characteristic groups and subgroups according to essential features. By using

groupings are limited qualitatively homogeneous in a significant respect

totality, which is a prerequisite for the definition and application

summary indicators.

On final stage analysis using summary indicators

relative and average values ​​are calculated, a summary assessment is given

variations of signs, the dynamics of phenomena is characterized, indices are applied,

balance constructions, indicators are calculated that characterize the tightness

connections in the change of signs. For the most rational and clear

presentation of digital material, it is presented in the form of tables and graphs.

3. Statistical observation: concept, basic forms.

This is a scientific and organizational work to collect data. Forms: stat. 1) reporting, cat. based on documentary accounting. since 1998, 4 unified forms of federal state supervision have been introduced: FP-1 (project issue), FP-2 (investment), FP-3 (financial state of organizations), FP-4 (number of -t workers, labor), 2) specially organized observation (census), 3) a register is a s-ma pok-lei, which characterizes each unit of observation: registers of us- niya, pr-ty, construction sites and contractors. org-tions, retail and wholesale trade. Types of observation: 1) continuous, non-continuous (selective, qualified based on the main array method, monograph). Observation is current, period., One-time. Observation methods: direct, documentary, survey (forwarding agent, questionnaire, private, correspondence). Statistical observations are carried out according to the plan, which includes: program-methodological issues (goals, tasks), organizational issues (time, place). As a result of the observations, errors occur, the cat reduces the accuracy of the observations, therefore, data control is carried out (logical and counting). As a result of checking the authentic data, the following observation errors are revealed: random. errors (registration errors), intentional errors, unintentional (system. and non-system.), errors of representativeness (representativeness).

Program-methodological issues of statistical observation.

Program and methodological issues of statistical observation

Each observation is carried out with a specific purpose.

When conducting it, it is necessary to establish what is to be examined. The following questions need to be addressed:

Object of observation - a set of objects, phenomena, from which information should be collected. When defining an object, its main distinctive features(signs). Any object of mass observations consists of their individual units, so it is necessary to decide what is the element of the totality that will serve as the unit of observation.

Unit of observation - this is an integral element of the object, which is the carrier of signs subject to registration and the basis of the account.

Qualification are certain quantitative restrictions for the object of observation.

sign - this is a property that characterizes certain features and characteristics inherent in the units of the studied population.

Organizational issues of statistical observation.

The observation program is drawn up in the form of forms (questionnaires, forms), in which primary data are entered.

A necessary addition to the forms is an instruction that explains the meaning of the questions.

The organizational issues of the program include:

terms of observation;

critical moment of observation;

preparatory work;

The period of observation to which the recorded information is referred. It is called the objective observation time. This might be a certain period of time (day, decade, month) or a certain moment. The moment to which the recorded information relates is called the critical moment of observation.

For example, the critical moment of the micro-census of 1994. was 0.00 h.

on the night of February 13-14. By establishing the critical moment of observation, one can determine the true state of affairs with photographic accuracy.

Preparatory work provides for the provision of observation with documents, as well as the compilation of a list of reporting units, forms, instructions.

Documents m. will be filled in during the observation or based on its results.

An important place in the system of preparatory work is the selection and training of personnel, as well as the briefing of those who will participate in the observation.

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Stages of statistical research.

Stage 1: Statistical observation.

Stage 2: Reduction and grouping of the results of observation into certain populations.

Stage 3: Generalization and analysis of the received materials. Identification of interrelations and scales of phenomena, determination of patterns of their development, development of predictive estimates. It is important to have comprehensive and reliable information about the object under study.

At the first stage of statistical research, primary statistical data, or initial statistical information, is formed, which is the foundation of the future statistical "building".

STAGES OF STATISTICAL RESEARCH

In order for the “building” to be durable, solid and of high quality, its foundation must be. If a mistake was made in the collection of primary statistical data or the material turned out to be of poor quality, this will affect the correctness and reliability of both theoretical and practical conclusions. Therefore, statistical observation from the initial to the final stage must be carefully thought out and clearly organized.

Statistical observation provides the source material for generalization, the beginning of which is summary. If, during statistical observation, information is obtained about each of its units that characterizes it from many sides, then these reports characterize the entire statistical aggregate and its individual parts. At this stage, the population is divided according to the signs of difference and combined according to the signs of similarity, the total indicators are calculated for the groups and as a whole. Using the grouping method, the studied phenomena are divided into the most important types, characteristic groups and subgroups according to essential features. With the help of groupings, qualitatively homogeneous populations are limited, which is a prerequisite for the definition and application of generalizing indicators.

At the final stage of the analysis, with the help of generalizing indicators, relative and average values ​​are calculated, an assessment of the variation of signs is given, the dynamics of phenomena is characterized, indices and balance constructions are applied, indicators are calculated that characterize the closeness of relationships in changing signs. For the purpose of the most rational and visual presentation of digital material, it is presented in the form of tables and graphs.

The cognitive value of statistics thing is:

1) statistics provides a digital and meaningful coverage of the phenomena and processes under study, serves as the most reliable way to assess reality; 2) statistics gives probative force to economic conclusions, allows you to check various "walking" statements, individual theoretical positions; 3) statistics has the ability to reveal the relationship between phenomena, to show their form and strength.

1. STATISTICAL OBSERVATION

1.1. Basic concepts

Statistical observation — this is the first stage of statistical research, which is a scientifically organized accounting of facts characterizing the phenomena and processes of social life, and the collection of data obtained on the basis of this accounting, scientifically organized according to a single program.

However, not every collection of information is a statistical observation. One can talk about statistical observation only when statistical regularities are studied, i.e. those that manifest themselves in a mass process, in a large number of units of some set. Therefore, statistical observation should be planned, massive and systematic.

Plannedness statistical observation lies in the fact that it is prepared and carried out according to a developed plan, which includes questions of methodology, organization, collection of information, quality control of the collected material, its reliability, and presentation of the final results.

Mass the nature of statistical observation implies that it covers a large number of cases of manifestation of this process, sufficient to obtain truthful data characterizing not only individual units, but the entire population as a whole.

Systematic statistical observation is determined by the fact that it must be carried out either systematically, or continuously, or regularly.

The following requirements are imposed on statistical observation:

1) completeness of statistical data (completeness of coverage of units of the studied population, aspects of a particular phenomenon, as well as completeness of coverage over time);

2) reliability and accuracy of data;

3) their uniformity and comparability.

Any statistical research must begin with the formulation of its goals and objectives. After that, the object and unit of observation are determined, a program is developed, and the type and method of observation are selected.

Object of observation- a set of socio-economic phenomena and processes that are subject to research, or the exact boundaries within which statistical information will be recorded . For example, during a population census, it is necessary to establish what kind of population is subject to registration - cash, that is, actually located in a given area at the time of the census, or permanent, that is, permanently living in a given area. When surveying industry, it is necessary to establish which enterprises will be classified as industrial. In some cases, one or another qualification is used to limit the object of observation. Qualification- a restrictive feature that all units of the studied population must satisfy. So, for example, during the census of production equipment, it is necessary to determine what is attributed to production equipment, and what to hand tools, which equipment is subject to the census - only operating or also under repair, in stock, reserve.

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

So, for example, in a population census, the unit of observation is each individual person. If the task is also to determine the number and composition of households, then each household will be the unit of observation along with the person.

Observation program- this is a list of issues on which information is collected, or a list of signs 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 an instruction (or indications on the forms themselves), explaining the meaning of the question. The composition and content of the questions of the observation program depend on the objectives of the study and on the characteristics of the social phenomenon being studied.

Introduction

1. Methodology for obtaining initial data

2. Statistical summary and grouping of primary data

2.1 Grouping

2.2 Determination of arithmetic and structural averages

2.3 Histogram and cumulate

2.4 Cost of fixed assets

2.5 Production volume

3. Correlation analysis

3.1 Study of the relationship between factor and performance characteristics. Building a correlation table

3.2 Determination of the degree of closeness of communication

4. Regression analysis

4.1 Simulation

4.2 Prediction

Conclusion

Used literature and programs

Introduction

The statistical study of the phenomena of social life begins with the stage of statistical observation, during which, in accordance with cognitive goals and objectives, an array of initial data about the object under study is formed, i.e. the information base of the study is formed, on which accounting and control, planning, statistical analysis and management are carried out. At this stage, methods of mass observation based on the "law of large numbers" are used, since quantitative patterns of mass phenomena are clearly manifested in the study of only a sufficiently large number of socio-economic phenomena and processes.

Any statistical observation should be prepared and carried out according to a clearly developed plan, which includes issues of methodology, organization and technique of data collection, control of its quality and reliability. Thus, statistical observation must have a program and an organizational plan for conducting it. At the same time, it is necessary to resolve questions about the method, form, type, means, timing, place of organization and conduct of observation, etc., which, in turn, determines its plannedness.

Statistical observation should not be carried out spontaneously, from time to time, but systematically: either continuously or periodically - at regular intervals. This is due to the spatio-temporal variation of the studied socio-economic phenomena and processes.

Statistical observation can be carried out by state statistics bodies, research institutes, economic and analytical services of various organizational structures.

The second stage of statistical research is a statistical summary and grouping of statistical observation data. As a result of statistical observation, information is obtained about each unit of the population, which has numerous features that change in time and space. Under these conditions, it becomes necessary to systematize and generalize the results of statistical observation and obtain, on this basis, a summary characteristic of the entire object using generalizing indicators, in order to make it possible to identify characteristics, specific features of the statistical population as a whole and its individual components and to discover the patterns of the studied socio-economic phenomena and processes. From what has been said, it follows that a summary of the primary statistical material is necessary.

The statistical summary is carried out according to a specially developed program that ensures the completeness and reliability of the results obtained. This program contains a list of groups into which the set of observation units can be divided according to individual characteristics, as well as a system of indicators characterizing the studied set of phenomena as a whole and its individual parts.

The third stage of statistical research is the analysis of statistical information. At this stage, based on the results of a statistical study, conclusions are obtained that are useful for practical actions, and a forecast of the phenomenon or process under study is also carried out.

1. Methodology for obtaining initial data

In order to study the dependence of the volume of production on the value of fixed assets for the period 2006-2007. the territorial body of state statistics for the Chelyabinsk region organized a statistical study of instrument-making enterprises.

Produced 20 percent typical sample.

The object of statistical observation is a set of instrument-making enterprises in the city of Chelyabinsk and the Chelyabinsk region. The reporting unit of statistical observation is an instrument-making enterprise.

In order to improve the system of sample surveys of instrument-making enterprises, the Goskomstat of the Russian Federation has developed a target Program.

According to the Program, in order to save resources, 20% of the total number of enterprises in the Chelyabinsk region operating on the date of work will be examined. The activities of the Program include a number of organizational, methodological, software and technological works that ensure the preparation and conduct of sample surveys of instrument-making enterprises, the subject of which covers such an issue as the dependence of the volume of production on the value of fixed assets. In order to ensure proper procedures for the preparation of sample surveys of enterprises, the activities of the Program also include the training of personnel in surveys and outreach. The Program is expected to be implemented during 2008-2009. The results of a sample observation of instrument-making enterprises in the city of Chelyabinsk and the Chelyabinsk region in terms of two indicators (production volume and cost of fixed assets) are shown in table 1.

Table 1 . The main performance indicators of instrument-making enterprises in the city of Chelyabinsk and the Chelyabinsk region for the period 2006 - 2007.

Factory No.	The cost of fixed assets	Production volume, million rubles	Factory No.	The cost of fixed assets	Production volume, million rubles

2. Statistical summary and grouping of primary data

2.1 Grouping

According to the statistical observation data, it can be seen that the variation of signs manifests itself in relatively narrow boundaries and the distribution is uniform. In this case, a grouping is built at equal intervals. The number of groups depends primarily on the degree of fluctuation of the trait: the greater the fluctuation of the trait (range of variation), the more groups can be formed. Below are the formulas for building a statistical grouping.

Since the sample size is not large, we use the formula to determine the number of groups:

Interval value h according to the formula:

; (1.2)

The value obtained by formula (1.2), which will be the interval step, is rounded off (rounding should not differ from the original value by more than 10-15%). In this case, for the first interval, the lower bound will be , and the upper - (+ h) etc. Thus, the lower limit of the i -th interval is equal to the upper limit of the (i -1) -th interval. Abstract >> Philosophy

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Marketing research in tourism

Cheat sheet >> Physical education and sports

Tourism of the region, scientific and statistical research in the field of tourism, training ... (member of the commission). 3. Basic stage: organization of certification work ... etc.). Method is a way of knowing, research phenomena public life, reception or system of receptions in...

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QUESTIONS FOR THE EXAM

Subject "Statistics"

Section 1. General statistics

The subject of statistical science and the tasks of statistics at the present stage.

Complete and reliable statistical information is the necessary basis on which the process of economic management is based. Making managerial decisions at all levels - from a national or regional level to the level of an individual corporation or private firm - is impossible without proper statistical support. It is the statistical data that make it possible to determine the volume of gross domestic product and national income, to identify the main trends in the development of economic sectors, to assess the level of inflation, to analyze the state of financial and commodity markets, to study the standard of living of the population and other socio-economic phenomena and processes.

Statistics is a science that studies the quantitative side mass phenomena and processes inextricably linked with their qualitative side, the quantitative expression of the laws of social development in the specific conditions of place and time.

The techniques and methods of data collection, processing and analysis used at all stages of the study are the subject of study. general theory statistics, which is the basic branch of statistical science. The methodology developed by her is used in macroeconomic statistics, sectoral statistics (industry, Agriculture, trade and others), population statistics, social statistics and other statistical fields.

Statistical population, its types. Units of the population and classification of their features.

The statistic is Natural resources peoples, populations and natural phenomena taken together within certain boundaries of place and time affect the economic life of society. It is a single whole consists of its individual units. Each of which can be described by a number of properties and features that they possess. Each of the features of the properties of units of the statistical population reflects specific feature characterizing this unit of the population.

A sign is a feature of a unit. aggregates. Unit selection aggregates, the list of features that characterize depend on the purpose and objectives of this statistical study.

Unit stat. aggregates form together a single whole in a number of properties and features that differ from each other. These differences are called feature variation. Variation is possible under the influence of external causes.

Classification of signs:

Qualitative (attribute) are determined by the presence or absence of any quality

Quantitative expressed in numbers

Discrete ones take an integer value - continuous ones take any real value.

The method of statistics and the main stages of statistical research.

Statistics has its own system of methods and methods of research aimed at the methods of commercial patterns, manifestation in the structure, dynamics (development) and the relationship of social phenomena.

The main method of statistical research. 3 stages:

1) stat. observation

2) summary and grouping of results

3) analysis of the received data

The method of mass observation (the law of large numbers) is carried out by the scientific and organizational collection of information, the study of socio-economic processes or phenomena (population census).

The grouping method distributes the entire mass into disposable groups and subgroups. The results are calculated for each group and subgroup with the results in the form of tables. Statistical indicators are processed and the results are analyzed to obtain reasonable conclusions about the state of the study of phenomena and patterns economic development. Conclusions are drawn up in text form and are accompanied by graphs and tables.

The Ministry of Statistics includes: regional, city department of statistics, regional department of statistics. Within the Min. stat. includes: analytical, information resource and registration standards and classifications of the organization stat. observations and balances, stat. Finance of the balance of payments, stat. prices, goods, markets, services.

To obtain statistical information, state and departmental statistics bodies, as well as commercial structures, conduct various kinds of statistical research. The process of statistical research includes three main stages: data collection, their summary and grouping, analysis and calculation of generalizing indicators.

The results and quality of all subsequent work largely depend on how the primary statistical material is collected, how it is processed and grouped. Insufficient elaboration of the program-methodological and organizational aspects of statistical observation, the lack of logical and arithmetic control of the collected data, non-compliance with the principles of group formation can ultimately lead to absolutely erroneous conclusions.

No less complex, time-consuming and responsible is the final, analytical stage of the study. At this stage, average indicators and distribution indicators are calculated, the structure of the population is analyzed, the dynamics and relationships between the studied phenomena and processes are studied.