Purpose: to consider the main methods of chemical identification.

1. The essence of chemical identification.

2. Qualitative analysis.

3. Quantitative analysis.

4. Methods of quantitative analysis.

Chemical identification is the establishment of the type and state of molecules, ions, radicals, atoms and other particles based on a comparison of experimental data with the corresponding reference data for known particles. Identification - establishing the identity of an unknown connection with another known one.
To do this, compare the physico-chemical constants, properties and reactions of both substances. Before identification, the substances are thoroughly purified, a preliminary study is carried out: they are compared state of aggregation, color, viscosity, test for solubility in water, organic solvents, bases and acids, determine combustibility and other properties. For example, in molecular analysis, identification is the establishment chemical formula compounds or its most important fragments. Identification is the goal of qualitative analysis, which usually precedes quantitative determinations.
BUT) The properties of a substance depend on its purity.
B) Molecular analysis - determination of the quality and quantity of the composition of chemical compounds and their mixtures.
In a qualitative analysis, a mixture of a chemical compound is usually preliminarily separated by various methods (chromatography, rectification, crystallization, extraction, precipitation, thermal diffusion, etc.); then, for the separated substances, the so-called integral molecular features are determined, which include molar mass, total elemental composition, density, solubility, phase transition temperatures, refractive indices, ionization potentials, as well as absorption spectra of electromagnetic radiation, mass spectra, etc. These characteristics of chemical compounds are compared with the corresponding constants and spectra of reference samples, and the absence of depression is established (decrease and increase in the interval) of the melting point of the mixture of the identified compound and the reference substance (i.e. known substance, identified with the investigated).
AT) Isotopic analysis - determination of the isotopic composition of a chemical element. Isotopic analysis various elements can be implemented on various physical principles. The most common is the mass spectrometric method, which can be used to carry out isotopic analysis of all, without exception, elements of the periodic system. Mass spectrometers to determine the isotopic composition must be very accurate. Electron impact ionization is used to analyze the isotopic composition of light elements (carbon, hydrogen, oxygen, sulfur, nitrogen, etc.). In this case, all methods of introducing the gas phase are suitable, as in organic mass spectrometers.
G) Phase analysis - definition chemical composition and the number of individual phases in heterogeneous systems, or individual forms compounds of elements in ores, alloys, semiconductors, etc. The object of phase analysis is always solid.
The subject of analytical chemistry is chemical identification (qualitative analysis) and measurement (quantitative analysis).
1.1 Qualitative analysis
Qualitative analysis has its own goal detection of certain substances or their components in the analyzed object. Detection is carried out by identification substances, that is, establishing the identity (sameness) of the AS of the analyzed object and the known AS of the substances to be determined under the conditions of the analysis method used. To do this, this method preliminarily examines reference substances in which the presence of the substances to be determined is known. For example, it has been found that the presence spectral line with a wavelength of 350.11 nm in the emission spectrum of the alloy, when the spectrum is excited by an electric arc, indicates the presence of barium in the alloy; the blueness of an aqueous solution when starch is added to it is an AC for the presence of I 2 in it and vice versa.
A detailed qualitative chemical analysis makes it possible to determine the elemental (atomic), ionic, molecular (material), functional, structural and phase compositions of inorganic and organic substances.
In the analysis of inorganic substances, elemental and ionic analyzes are of primary importance, since knowledge of the elemental and ionic composition is sufficient to establish the material composition of inorganic substances. The properties of organic substances are determined by their elemental composition, but also by their structure, the presence of various functional groups. Therefore, the analysis of organic substances has its own specifics.
Qualitative chemical analysis is based on a system of chemical reactions characteristic of a given substance - separation, separation and detection.
The following requirements apply to chemical reactions in qualitative analysis.
1. The reaction should proceed almost instantly.
2. The reaction must be irreversible.
3. The reaction must be accompanied by an external effect (AS):
a) a change in the color of the solution;
b) the formation or dissolution of a precipitate;
c) release of gaseous substances;
d) flame coloring, etc.
4. The reaction should be sensitive and, if possible, specific.
Reactions that make it possible to obtain an external effect with an analyte are called analytical, and the substance added for this - reagent. Analytical reactions carried out between solids, are classified as reactions dry way", and in solutions -" wet way».
"Dry" reactions include reactions carried out by grinding a solid test substance with a solid reagent, as well as by obtaining colored glasses (pearls) by fusing some elements with borax.
Much more often, the analysis is carried out "wet way", for which the analyte is transferred into solution. Reactions with solutions can be performed by test tube, drop and microcrystalline methods. When test-tube semi-microanalysis is performed in test tubes with a capacity of 2-5 cm 3 . To separate the precipitates, centrifugation is used, and evaporation is carried out in porcelain cups or crucibles. Drop analysis (N.A. Tananaev, 1920) is carried out on porcelain plates or strips of filtered paper, obtaining color reactions by adding one drop of a reagent solution to one drop of a solution of a substance. Microcrystalline analysis is based on the detection of components through reactions that form compounds with a characteristic color and shape of crystals observed under a microscope.
1.2Quantitative analysis
Quantitative analysis - determination of the content (mass, concentration, etc.) or quantitative ratios of components in the analyzed sample. The components to be determined can be atoms, molecules, isotopes, functional groups, phases, etc. Usually, quantitative analysis is based on the use of the dependence of the physical properties of the object under study or the product of its transformation on the composition that are measurable.
Quantitative chemical analysis is based on a chemical reaction between the analyte and the reagent.
The chemical reactions used in this assay are subject to the following requirements:
1) the reaction should proceed quickly enough and be practically irreversible;
2) the substances that have entered into the reaction must react in strictly defined quantitative ratios, i.e. the reaction must be stoichiometric and not be accompanied by side reactions;
3) as a result of the reaction, compounds with a certain molecular composition should be obtained;
4) the course of the reaction should not be affected by impurities present in the analyte;
5) the reaction should allow one to fairly easily determine the moment of its completion, as well as the mass of the reaction product or the volume of the reagent solution spent on its implementation.
2. Methods of quantitative analysis
2.1Amperometric titration
Amperometric titration, a quantitative analysis method based on linear potential sweep voltammetry. The end point of the titration is set according to the dependence of the diffusion current Id at a constant potential Ec of the indicator electrode on the volume V of the added titrant.
2.2Potentiometric titration
Potentiometric titration is based on the determination of the equivalence point from the results of potentiometric measurements. Near the equivalence point, there is a sharp change (jump) in the potential of the indicator electrode. This is observed, of course, only when at least one of the participants in the titration reaction is a participant in the electrode process.
2.3 Acid-base titration
In acid-base titration, a glass electrode is usually used as an indicator, as a rule, it is included in a set of commercially available pH meters. The potentiometric method allows the quantitative determination of components in a mixture of acids if the dissociation constants differ by at least three orders of magnitude. For example, when titrating a mixture containing hydrochloric (HCl) and acetic acids, two jumps are found on the titration curve. The first indicates the end of the HCl titration, the second jump is observed during the titration of acetic acid. There are also several jumps in the titration curves of polybasic acids, the dissociation constants of which differ significantly (chromic, phosphoric, etc.).
The use of non-aqueous solvents opens up wide possibilities for the analysis of multicomponent mixtures without separation. For example, determining the content of hydrochloric and monochloroacetic acids in a mixture by titration of an aqueous solution is a difficult task due to the difficulty of detecting two titration jumps. When titrated in acetone, both jumps are expressed quite clearly and the content of each acid in the mixture can be calculated.
2.4 Complexometric titration
Potentiometric titration of cations with complexone III (EDTA) can be carried out using the corresponding metal as an indicator electrode: titration of copper salts with a copper electrode, zinc salts with zinc, etc. or a suitable ion selective electrode. However, many metal indicator electrodes are irreversible, and the number of ion-selective electrodes is small.
For complexometric titrations, a universal electrode Hg|HgY2- or Au(Hg)|HgY2- can be used where Au(Hg) is amalgamated gold; HgY2- - mercury complex with ethylenediaminetetraacetic acid anion. With this type of mercury electrode any ions can be titrated which form complexes with Y4 with a stability constant not exceeding that of the mercury complex. These are, for example, ions of magnesium (Mg2+), calcium (Ca2+), cobalt (Co2+), nickel (Ni2+), copper (Cu2+), zinc (Zn2+), etc.
2.5 Titration according to the precipitation method
Indicator electrodes in potentiometric titration methods that use precipitation reactions are metal or membrane electrodes that are sensitive to the ion to be determined or the precipitant ion. In practice, the precipitation method can be used to determine the cations of silver, mercury, zinc, lead, anions of chlorine, bromine, iodine, and some others. A mixture of halides, for example I- and Cl-, can be titrated without separating with silver nitrate. The silver electrode makes it possible to detect two jumps during such a titration. The first jump indicates the titration of the iodide ion and can be used to calculate the content of this ion, the second jump refers to the end of the precipitation of the chloride ion. From the second jump, the total halide content or chloride ion concentration can be calculated if the iodide ion concentration is known from the titration data prior to the first jump.
2.6 Redox titration
Redox titration curves can be plotted in coordinates either pM - V (titrant) or E - V (titrant), if pM=-lg[M] ([M] - concentration of the reaction participant, E - potential of the system, V (titrant ) is the volume of the titrant The first type of titration curves are of practical interest when an indicator electrode sensitive to M is available. , most commonly platinum.

Qualitative analysis is intended for the qualitative discovery of individual chemical elements, ions and functional groups. The presence in the analyzed mixture of individual substances, elements, ions and functional groups is usually detected using chemical qualitative reactions or on the basis of some physical properties of substances - spectra in the visible and ultraviolet regions of light, radioactive radiation, ability to to adsorption.

Quantitative analysis is carried out in various ways. Chemical methods are widespread, in which the amount of a substance is determined by the amount of reagent used for analysis, by the amount of sediment, etc. Often, for the quantitative determination of substances, their physical properties are used - the magnitude of the refractive angle of solutions of substances, the color intensity, the value electric current flowing through the solution.

ANALYSIS METHODS

The analysis can be carried out by chemical, instrumental (physical and physico-chemical) methods.

Chemical analysis methods include chemical interaction substances. The results of a chemical reaction between a substance and a reagent are important here. Chemical methods of analysis are widely used for qualitative analysis, since the nature of the precipitate, the change in color of the solution, the formation of a certain gas can determine which substance is present in the solution.

In quantitative chemical analysis, the resulting precipitate is weighed, the reagent solution is added until the color of the solution or other physical characteristics of the substance change, and the amount of the substance is determined by the amount of the reagent used for analysis.

Instrumental (physical, physico-chemical) methods of analysis use the physical properties of substances. Qualitative analysis when using physical methods is carried out by changing the color of the flame that occurs when a substance is introduced into it, by the absorption and emission spectra of the substance, by the melting point, boiling point and other properties that are characteristic of substances. Quantitative analysis by physical methods is carried out by observing changes in the physical properties of a substance with a change in its quantity. Usually, the intensity of color, the angle of refraction of the solution, the magnitude of the electric current passing through the solution depend on the amount of the substance, and this dependence can be used to determine the amount of the substance.

Physico-chemical methods of analysis combine physical and chemical methods. When carrying out physical and chemical methods, the result of a chemical reaction is observed by changes in the physical properties of a substance or its solution. Physicochemical methods have become widespread and are being intensively developed.

The analysis of a substance can be carried out in order to establish its qualitative or quantitative composition. Accordingly, a distinction is made between qualitative and quantitative analysis.

Qualitative analysis allows you to establish what chemical elements the analyzed substance consists of and what ions, groups of atoms or molecules are included in its composition. When studying the composition of an unknown substance, a qualitative analysis always precedes a quantitative one, since the choice of a quantitative determination method constituent parts of the analyte depends on the data obtained from its qualitative analysis.

Qualitative chemical analysis is mostly based on the transformation of the analyte into some new compound that has characteristic properties: a color, a certain physical state, a crystalline or amorphous structure, a specific smell, etc. chemical transformation, which occurs in this case, is called a qualitative analytical reaction, and the substances that cause this transformation are called reagents (reagents).

Another example of a qualitative chemical analysis is the detection of ammonium salts by heating the analyte with an aqueous solution of sodium hydroxide. Ammonium ions in the presence of OH "-ions form ammonia, which is recognized by the smell or by the blue color of wet red litmus paper.

When analyzing a mixture of several substances similar in chemical properties, they are preliminarily separated and only then characteristic reactions are carried out for individual substances (or ions), therefore, a qualitative analysis covers not only individual reactions for detecting ions, but also methods for their separation.

Quantitative analysis allows you to establish the quantitative ratio of the constituent parts of a given compound or mixture of substances. Unlike qualitative analysis, quantitative analysis makes it possible to determine the content of individual components of the analyte or the total content of the analyte in the test product.

Methods of qualitative and quantitative analysis, which allow determining the content of individual elements in the analyzed substance, are called elemental analysis, functional groups - functional analysis; individual chemical compounds characterized by a certain molecular weight - molecular analysis.

A set of various chemical, physical and physico-chemical methods for separating and determining individual structural (phase) components of heterogeneous! systems that differ in properties and physical structure and are limited from each other by interfaces are called phase analysis.

I. Already in the course of the study, one can assume about its results, but usually these conclusions are considered as preliminary, and more reliable and thorough data can be obtained only as a result of a thorough analysis.

Data analysis in social work is about integrating all the collected information and bringing it to a form convenient for explanation.

Methods for analyzing social information can be conditionally divided into two large classes in accordance with the form in which this information is presented:

– qualitynatural methods focused on the analysis of information presented mainly in verbal form.

– quantitativemethods are mathematical in nature and represent processing techniques digital information.

Qualitative analysis is a prerequisite for the application of quantitative methods, it is aimed at revealing the internal structure of data, that is, at clarifying those categories that are used to describe the studied sphere of reality. At this stage, the final definition of the parameters (variables) necessary for an exhaustive description takes place. When there are clear descriptive categories, it is easy to move on to the simplest measurement procedure - counting. For example, if you select a group of people who need some help, then you can count the number of such people in a given microdistrict.

In qualitative analysis, it is necessary to compression informacia, that is, to obtain data in a more compact form.

The main technique for compressing information is coding- the process of analyzing qualitative information, which includes the selection of semantic segments text or real behavior, their categorization (naming) andreorganization.

To do this, in the text itself find and mark keythe words, that is, those words and expressions that carry the main semantic load directly indicate the content of the text as a whole or its separate fragment. Different types of highlighting are used: underlining with one or two lines, color coding, making notes in the margins, which can be in the form of both additional icons and comments. For example, you can highlight those fragments where the client speaks about himself. On the other hand, one can single out everything related to his health, one can separate those problems that the client is able to solve on his own, and those problems for which he needs outside help to solve.

Fragments similar in content are labeled in a similar way. This makes it easy to identify them and, if necessary, to collect them together. Then the selected fragments are searched for under different headings. Analyzing the text, you can compare its individual fragments with each other, revealing similarities and differences.

The material processed in this way becomes easily visible. The main moments come to the fore, as if towering above the mass of details. It becomes possible to analyze the relations between them, to reveal their general structure and, on this basis, to put forward some explanatory hypotheses.

When several objects are studied simultaneously (at least two) and when comparison with the aim of finding similarities and differences becomes the main method of analysis, comparative methodd. The number of objects studied here is small (most often two or three), and each of them is studied in sufficient depth and comprehensively.

It is necessary to find a form of data presentation that is most convenient for analysis. The main approach here is schematization. Schema always simplifies real relationship, coarsens the true picture. In this sense, the schematization of relations is at the same time the compression of information. But it also involves finding a visual and easily visible form of information presentation. This is the purpose of collating data into tables or diagrams.

For ease of comparison, the material is reduced to tables. The general structure of the table is as follows: each cell is the intersection of a row and a column. The table is convenient because it can include both quantitative and qualitative data. The point of a table is to be able to look at it. Therefore, usually the table should fit on one sheet. The pivot table used for analysis is often drawn on a large piece of paper. But a large table can always be divided into several parts, that is, several tables can be made from it. Most often, the row corresponds to one case, and the columns represent its various aspects (features).

Another technique for concise and visual presentation of information is diagrams. There are different types of diagrams, but almost all of them are structural diagrams, on which elements are depicted by conditional figures (rectangles or ovals), and links between them are represented by lines or arrows. For example, using a diagram it is convenient to present the structure of any organization. Its elements are people, more precisely, positions. If the organization is large, then larger structural elements - subdivisions - are selected as elements. Using the diagram, it is easy to represent the hierarchy of relationships (subordination system): senior positions are located above in the diagram, and junior positions are below. The lines connecting the elements indicate exactly who reports directly to whom.

Representation in the form of diagrams can also be used to identify the logical structure of events or text. In this case, first, a semantic analysis is carried out and key events or components are outlined, and then they are presented in graphical form so that the connection between them becomes as clear as possible. It is clear that schematization leads to a coarsening of the picture due to the omission of many details. However, there is a compression of information, its transformation into a form convenient for perception and memorization.

Thus, the main methods of qualitative analysis are coding and visual presentation of information.

II. Quantitative analysis includes methods of statistical description of the sample and methods of statistical inference (testing of statistical hypotheses).

Quantitative (statistical) methods of analysis are widely used in scientific research in general and in the social sciences in particular. Sociologists resort to statistical methods to process the results of mass opinion polls. Psychologists use the apparatus of mathematical statistics to create reliable diagnostic tools - tests.

All methods of quantitative analysis are usually divided into two large groups. Statistical methodswhom descriptions aimed at obtaining a quantitative characteristic of the data obtained in a particular study. Statistical methodsoutput make it possible to correctly extend the results obtained in a particular study to the entire phenomenon as such, to draw conclusions of a general nature. Statistical methods make it possible to identify stable trends and build on this basis theories intended to explain them.

Science always deals with the diversity of reality, but it sees its task in discovering the order of things, some stability within the observed diversity. Statistics provides convenient methods for such analysis.

The use of statistics requires two basic conditions:

a) it is necessary to have data on a group (sample) of people;

b) these data must be presented in a formalized (codified) form.

It is necessary to take into account the possible sampling error, since only individual respondents are taken for the study, there is no guarantee that they are typical representatives of the social group as a whole. Sampling error depends on two things: on the sample size and on the degree of variation of the trait that interests the researcher. The larger the sample, the less likely it is to include individuals with extreme values ​​of the variable under study. On the other hand, the lower the degree of variation of the trait, the closer each value will be to the true mean in general. Knowing the sample size, and having obtained a measure of the dispersion of observations, it is not difficult to derive an indicator called standard error of the mean. It gives the interval in which the true mean of the population must lie.

Statistical inference is the process of testing hypotheses. Moreover, initially, the assumption is always made that the observed differences are of a random nature, that is, the sample belongs to the same general population. In statistics, this assumption is called zero gihypothesis.

The analysis of empirical data is one of the most important stages of sociological research, its success is largely determined by the level of professional training of the researcher: his logical and methodological culture of thinking, knowledge of the object and subject, sociological experience. Thus, the completeness of “reading” the information contained in tables and diagrams, its logical processing and meaningful interpretation essentially depend on the depth of the sociologist’s knowledge of the object and subject with which he is dealing. Great importance also have his ability to objectively analyze data. The objectivity and professional integrity of a sociologist who carries out a qualitative analysis of information consists, in particular, in the following:

having revealed any connection or regularity, he must compare them with previously established facts, and also refer to the accompanying data that support (or refute) the interpretation scheme he has chosen;

describing the identified links and trends, it should be specified under what conditions and situations they take place;

carrying out a qualitative analysis of information, the researcher should try to formulate the social problem behind the data obtained;

in no case and under no circumstances should he "adjust" empirical data to the desired result.

Only compliance with these rules will make it possible to make a qualitative analysis of empirical information sufficiently reliable, meaningful, and accurate.

The researcher proceeds to this stage of work after mathematical processing of the empirical material and obtaining a linear distribution (usually in percent) for all variables (features). Before proceeding directly to data analysis, it is necessary to carry out a general quality control of the information received: to identify errors and omissions made during data collection, to reject any observation units that do not correspond to the sampling model, etc.

Depending on the program goals, data analysis can be more or less deep, carried out according to the “full scheme” or interrupted at a certain stage. In full, it includes three successive stages: a description of the data obtained, their explanation, and a forecast of possible changes in the fragment of social reality that was the object of the study. Each stage involves the use of a corresponding class of analysis procedures. The class of descriptive procedures includes grouping and typology. The second class is formed by logical-analytical procedures, with the help of which social relationships and deterministic dependencies are revealed. The third class of prognostic procedures is extrapolation, modeling and expertise.

Let's consider each of these methods of analysis in more detail.

I. Description procedure. In general, the description acts as a function scientific knowledge, which consists in a consistent, complete and logically connected fixation of the elemental composition, properties and relationships of the studied object (phenomenon, process), that is, its structure based on the empirical information obtained. The main objectives of a qualitative analysis according to a descriptive plan are:

ordering of the initial empirical data;

search for stable links and trends in the change of an object (phenomenon, process);

search for stable combinations of properties of the studied objects (phenomena).

The analysis of sociological information according to the descriptive plan includes several stages. On the first of them, ordering is carried out according to individual characteristics, simple distributions are studied, and possible distortions are identified. This makes it possible to give a general assessment of the sample set and private subsamples (sex and age, territorial, ethnic, professional, etc.), which is necessary to solve two problems: first, in order not to lose the idea of their “first principle”, and secondly, to understand how the features of the samples can affect the interpretation of a particular conclusion.

For example, linear distribution data on average for a sample of voters in a particular constituency indicates that the main qualities that a candidate for deputy should possess, according to respondents, are intelligence and creativity in work. Before interpreting this conclusion, the sociologist must address the main characteristics of the sample: perhaps it is dominated by people with a high level of education or carriers of creative professions,

The next stage of descriptive analysis consists in the procedure of “compression” of empirical information: enlargement of the initial scales, identification of typical groups subject to further analysis, formation of index features, etc. This allows, on the one hand, to reduce the number of variables, and on the other hand, to generalize the material at the primary level, to make it “observable” for the researcher. This procedure is especially important in the OSI, which does not imply a subtle interpretation of unimportant particulars. For example, if in further analysis we are interested in groups of supporters and opponents of a public action, then the original 4-term scale, which was used to measure the attitude of respondents to this action (“I fully approve” – “rather approve” – “rather disapprove” - “I completely condemn”), it may be advisable to enlarge, dividing the respondents into two groups - supporters and opponents of the event. In addition, in order to enlarge the initial information, as well as to turn qualitative features into quantitative (i.e., measurable) indicators, indices are constructed at this stage of the analysis. In sociology, an index is understood as an integrated indicator of the level of development or manifestation of a trait, measured using scales. It can be expressed as:

a) weighted average of the values ​​of each of the answer options in the rank scale;

b) the value of the difference between high and low, positive and negative manifestations of a qualitative trait (contrast index), for example, as the difference between the number of groups of people who fully approve and completely condemn an ​​event.

To convert qualitative information into quantitative information, each attribute value is first assigned certain numerical values ​​(“I fully approve” - 1; “I rather approve” - 2, etc.), which act as primary indices of one or another manifestation of this attribute. Then the secondary index is constructed as a certain integral numerical value obtained as a result of mathematical operation with primary indices (calculation of arithmetic mean values ​​or difference between extreme values, etc.). The secondary index characterizes the quantitative manifestation of the trait under study as a whole: the level of support, awareness, agreement, satisfaction, reflected by several variables.

The generalization of information on more capacious structures requires an intermediate interpretation of the aggregated features, since these are new properties that need to be interpreted in a certain way, i.e. give them some meaning. In general, the initial empirical interpretation of the basic concepts is carried out at the stage of research programming. And accordingly, any new aggregate indicators obtained in the course of a qualitative analysis should be “included” in the developed interpretation scheme.

For example, if we study the causes of poor lecture attendance by students, then at the first stage of the analysis we need to turn a set of initial data on lecture attendance by students A, B, C, ... into a certain index characterizing the level of lecture attendance by this group. Then we must evaluate (interpret) it as high, medium or low, thus turning it into a social indicator of the phenomenon under study.

On the basis of the obtained social indicators, with the help of descriptive statistics procedures, a meaningful interpretation of the sociological research data is carried out in order to test descriptive hypotheses.

Descriptive analysis methods. These include, first of all, the methods of simple and cross grouping and empirical typology.

Grouping. Suppose that linear distribution data showed that the opinions of the respondents were divided about a certain political event: 60% approved it, 40% condemned it. By themselves, these figures do not say anything about the reasons for such a polarization of opinions, the trends of this process and the forecast of changes in public opinion in the future. To try to answer all these questions, the sociologist must know which socio-demographic groups represent the carriers of a particular opinion, if possible, how they reacted to similar events in the past (or elsewhere), etc.

To achieve this goal, at the first stage of the analysis, a simple grouping is carried out - the selection of homogeneous groups within the surveyed population according to a significant (for the purposes of this study) feature. Such a sign can be any socio-demographic characteristic (gender, age, education, place of residence) or a judgment expressed by the respondents, or some forms of behavior, etc.

For example, when studying the problem of deviant behavior of adolescents, in the surveyed population it is logical to single out a group that has a sign of certain forms of deviations, and a group that does not have this sign (i.e., normal teenagers).

Quantitative indicators are grouped into ranked series as the attribute increases or decreases, and qualitative indicators are grouped according to the principle of constructing disordered nominal scales.

The number of members of a group is called frequency, and the ratio of the size of a given group to the total number of observations is called shares or relative frequency. The simplest analysis of groups is the calculation of frequencies by percentage.

The following analysis procedure according to the descriptive plan involves comparing the grouped data: 1) with data from other studies; 2) among themselves; 3) with any related external signs.

1. Comparison with data from other studies - subject to the comparability of sociological information - is carried out in two possible forms:

a) the form of comparison of data related to the same object, but obtained in different periods of time (for example, in repeated studies). This allows you to identify the dynamics and main trends in the change of the object;

b) the form of comparison of the results of studies conducted on different objects, but within the same period of time. This allows, with certain reservations, to confirm the hypothesis about the correctness of the results obtained in a one-time study. For example, in 1994, BSU sociologists, studying the problems of religiosity in the Republic of Belarus, obtained a result according to which the proportion of believers among the population was 33% (another 8.5% answered that they were “on the way to faith”). These data were compared with the research data of Russian sociologists, according to which in 1992-1993. the proportion of believers among Russians was 40%. Such a comparison made it possible to assume that the figure obtained in the Republic of Belarus is not accidental, that it more or less adequately reflects the real state of affairs in the study area.

2. Comparison as a ratio between the elements of the number series makes it possible to fairly reliably interpret the results of groupings in the event that the modal (largest) value is clearly distinguished in the number series. Comparison of elements among themselves then consists in their ranking (for example, according to the degree of satisfaction of students with the organization of the educational process).

3. Comparison of data with related external features is carried out in cases where the distribution of the numerical values ​​of the series makes it difficult to correlate them with each other. For example, in order to assess the priority interests of TV viewers, we need to compare the share of those who watched information and political programs on certain days with the shares of those who watched feature films, sports programs, etc. on those days.

In this way, comparative analysis data obtained by the method of simple grouping allows us to draw conclusions about the state and nature of changes in the phenomenon under study, but does not give an idea of ​​the stable relationships between its individual characteristics and, accordingly, about the causes of the changes taking place.

The task of finding stable relationships and interdependencies, process trends are solved by the method cross grouping - classification of facts, previously ordered according to two criteria. Cross grouping is carried out in the form of tables, which indicate which features are matched, and the total number of objects included in the grouping.

Table 5.9

Attitude towards religious faith depending on age (%)

This table illustrates the use of cross grouping to find a trend, process dynamics. The data presented in it testify that the number of believers increases monotonously with the age of the respondents. On the contrary, the proportion of people with an indefinite, wavering consciousness decreases with age: the older a person is, the more definite his position in relation to faith becomes. Obviously, this can also explain the fact that the number of non-believers also increases in the group of people over 60 years old, i.e. this group has the largest number of both believers and non-believers, and the smallest number of waverers.

When reading a table built on the basis of cross grouping, it is important to know what is taken as 100%: data by row or by column? As V.A. Yadov, “it depends on two circumstances: on the nature of the sample and on the logic of the analysis.... If the sample is representative and reflects the proportions of the studied groups of the general population, then it is possible to analyze the data in two ways: according to the logic “from cause to effect” and “from effect to the reasons."

Consider the following example. Suppose that 1000 teenagers were interviewed, 200 of them found some form of social deviations (deviations), and 800 did not. Hypothesis: one of the factors influencing the growth of deviant behavior is the absence of one of the parents in the family.

Let's assume that the respondents, depending on the type of family (complete - incomplete), were distributed as follows:

Table 5.10

Initial cross-grouping of data: family type and social behavior type (N=1000 people)

Let's analyze according to the logic “from cause to effect”. We suggested that one of the reasons for the occurrence of deviations in adolescents may be incomplete family composition. With this approach, data per line is taken as 100%, that is, we compare the share of “deviants” living in complete families with the share of “deviants” living in single-parent families (see Table 5.11).

Table 2a

Influence of family type on the social behavior of adolescents (in %)

Conclusion: adolescents from incomplete families are more likely to have deviations in social behavior.

Now we will analyze according to the logic “from the effect to the causes”. Here, the column data is taken as 100%, i.e. we compare within the group of adolescents with deviant behavior: the number of those living in intact families with the number of those living in single-parent families (see Table 5.12).

Table 5.12

The share of adolescents with different types of social behavior in complete and single-parent families (in %)

Conclusion: three-quarters of the surveyed teenagers with deviant behavior live in incomplete families. In this case, both retrospective and design analyzes confirmed the initial hypothesis about the influence of family type on the type of social behavior of adolescents.

If the sample is not representative, then the percentage should be carried out for each subsample separately. Typically, such subsamples are formed according to characteristics that are possible causes of the phenomenon under study: gender and age, social status, etc. Here, the discrepancy between the proportions of subsamples and the distribution of the population will not distort the conclusion (the logic of Table 5.11).

However, in real practice, a sociologist, as a rule, is faced with the need to identify and take into account the mutual determinations of not one, but several factors at once that affect the phenomenon under study. This procedure is carried out as follows.

Let us assume that the purpose of the study is to find factors that influence the low performance of students in any academic discipline. Hypotheses are put forward that the main reasons for the low academic performance of students can be: lack of interest in the content of the course; poor relationship with the teacher; low preparation of students, which does not allow them to master the educational material.

It is possible that the analysis will reveal the presence of a stable relationship between the level of academic performance and the level of interest in the course content. It is possible that the found connection is only an appearance, i.e. it has the character of concomitant or subsequent, but not causal dependence. In this case, both signs either change, obeying some third factor, or the lack of interest among students is a function that mediates, for example, their low preparedness and, as a result, poor academic performance. In this case, a relationship analysis is performed, which turns the two-dimensional distribution table into a three-dimensional one. Let's take an example. The results of the study on satisfaction with living conditions showed that there is a relationship between this variable and the gender of the respondents: men are generally more satisfied with their living conditions than women. However, it is too early to draw a final conclusion. It is known that among women there are more elderly and lonely people (both due to the greater natural life expectancy, and lower, in comparison with men, mortality as a result of accidents, wars, etc.). In our society, this category of people is economically poorly protected and their living conditions are often worse than those of other social groups. Therefore, it is possible that the two-dimensional grouping data is explained by the higher proportion of older people among women. We construct a three-dimensional matrix in which, in addition to the independent variable (sex) and the dependent variable (satisfaction with living conditions), we introduce a control factor (age).

Table 5.13

Degree of satisfaction with living conditions

by sex and age (in %)

The data presented in the table indicate that our preliminary conclusion is valid only for older age groups: from 45 - 59 years old and especially - over 60 years old. At a younger age, there are no significant differences in the level of satisfaction with living conditions depending on the gender of the respondents.

Empirical typology. This is the most powerful method of analysis according to a descriptive plan, which allows a) to form typological groups according to several simultaneously specified criteria; b) find stable combinations of the properties of social objects (phenomena) that are considered in a multidimensional social space.

The first procedure is carried out at the stage of research programming, its purpose is to identify homogeneous groups that have the most stable qualitative characteristics to be studied. The fact is that the ordinary consciousness of a mass person is characterized by mobility, eclecticism, internal inconsistency. His opinions and assessments are often formed not on the basis of some set of stable beliefs and values, but under the influence of external factors, momentary events. For example, the attitude towards a political figure may be determined by how well or unsuccessfully he spoke on television the day before. In addition, respondents' answers may be determined not so much by their personal position as by social fashion, normative ideas of a particular social group, etc. (for example, religion became the object of this kind of fashion in the early 1990s, in connection with which a significant increase in the number of believers, or rather people who call themselves believers, was observed in the post-Soviet space). In operational sociological research, due to their target specifics, it is very important to obtain accurate information about the number of certain groups that hold certain views and their behavioral attitudes. In this case, to filter out random, insincere or impulsive choices, groups are formed on the basis of respondents' answers not to one, but to a block of logically related questions. For example, in electoral studies, as D.G. Rotman, such a block includes the following variables:

b) a measure of political patency (the opportunity to be elected);

c) faith in the prospects of a politician (party);

d) an assessment of the specific actions of this leader at the moment.

Further, on the basis of the answers received, groups of “tough supporters” are formed (this includes respondents who gave the most positive assessments to this leader according to all criteria in all questions), “tough opponents” (respondents who in all cases refused to trust this person and rated him activity is negative). The rest are included in the group of "fluctuating" .

In the same way, to assess the level of religiosity of the population, it is not enough to fix, through self-identification, the number of people who believe in God, since faith can be purely external, declarative, etc. character. In order to reliably determine the proportion of genuine believers, it is necessary to introduce into the number of group-forming criteria such signs as belonging to a certain confession and stable cult behavior. And if today about half of the population of the Republic of Belarus consider themselves believers, then in a combination of three signs, their share is reduced to 7-8%.

The second procedure of empirical typology is to search for stable combinations of the properties of the phenomena under study.

Any fragment of social reality as an object of research interest has at the same time a huge number of interconnected and interdependent properties. Moreover, this relationship is often repeatedly mediated: for example, the correlation between two features can be caused by some third feature that has remained outside the sociologist's field of vision.

cluster analysis– method of multidimensional classification of objects, i.e. a method that allows classification according to many criteria at once. It is very important that it works with both quantitative and qualitative features, which is especially important when analyzing mixed data that includes both quantitative and qualitative information.

Cluster analysis allows you to divide the data set into homogeneous groups in such a way that the differences between objects of the same group are much smaller than between objects. different groups. The criterion of difference (similarity) for quantitative features is most often distance measures in Euclidean space, for qualitative ones - measures of connection or similarity (chi-square, Yule coefficient, and others).

Factor analysis– method statistical analysis a large number features, allowing to reveal their structural relationships. The main problem solved by means of factor analysis is to find methods for the transition from a certain number of relatively easily measured features of the phenomenon under study to a certain number of latent (outwardly unobservable) factors behind them, the existence of which can only be assumed. This method makes it possible to reveal the structure of any complex social phenomenon (process), as well as to determine the factors that determine it. The names that are given to the selected factors are, as a rule, conditional and are selected by association with those features that are most strongly associated with this factor, i.e. have the highest factor loading. The factor load is understood as the significance of one or another attribute in the distinguished group of variables. Thus, factor analysis allows us to weigh the significance of each of the elements of the phenomenon (process) under study in the overall structure of this latter.

The procedure of empirical typology allows you to go directly to the analysis of stable (i.e., significant for the purposes of the study) relationships and involves the implementation of a meaningful interpretation of the collected data.

Interpretation- this is a set of values, meanings that are attached by the researcher to the received empirical information or social indicators. In the general case, these data are interpreted by means of images of consciousness, which must be adequate to comprehended social reality. Meanwhile, the relationship between real objects and their image is always approximate, incomplete. And in this sense, any interpretation, in order to be relatively correct, must be inextricably linked with the specific content of the sphere of social life to which it belongs, which is why it is always situational and unique. “No matter how complete and specific the information received,” writes G.S. Batygin, - it is always placed in a certain "coordinate system" and acts as a fragment of a larger picture, the content of which is scientific and life experience sociologist."

Of course, the basis for interpreting and explaining the data should be laid down in the research program at the stage of empirical operationalization and interpretation of the basic concepts. Their totality forms a certain interpretive scheme, which acts as a specific semantic matrix that gives the researcher a certain “perspective” on the problem. The construction of such schemes is an unformalizable operation that involves high level theoretical, methodological and analytical culture of a sociologist.

Then, on the basis of the developed interpretation scheme, the initial hypotheses are tested, and, if necessary, their addition and refinement.

However, there are often significant difficulties in interpreting survey data for several reasons. Let's name some of them.

1. As a rule, people's stereotypical ideas about something are studied in the OSI. At the programming stage, these representations are subjected to logical-verbal processing and transformation, and in the everyday behavior of people, the functioning of stereotypes is usually carried out at an unconscious level. As a result, by asking the respondent one question or another and offering a set of ready-made answers, we thus, as it were, “program” his consciousness, because it is quite likely that, participating in the survey, he is thinking about this problem for the first time in his life. In this case, the answers may be random, self-contradictory, or presented in terms imposed on him in the questionnaire.

2. Each person, being a unique individuality, at the same time acts as a bearer of a certain social group consciousness, i.e. shares the norms, values, opinions of those social groups to which it belongs. As a result, sociologists quite often encounter the phenomenon of “split” consciousness: the same respondent can express negative assessments and at the same time have positive attitudes towards any value, existing, as it were, in two “reference systems” - normative-group and individual- pragmatic.

The fact that these two levels of consciousness do not always agree with each other, V.A. Yadov connects with differences in the content and structure of individual and group interests. The former act as a prerequisite for “behavioral programs”, while the latter serve as the basis for “normative prescriptions”, which often do not agree with the former.

The tools for collecting and analyzing data used in the practice of sociological research are based on the tradition of “rigorous” testing of hypotheses that has developed in natural science. This tradition suggests that hypotheses must be unambiguous and based on the law of the excluded middle. All material that does not meet these requirements is often taken as information "noise" and excluded from the analysis. However, it should be remembered that in sociology the technology of “strict” testing of hypotheses is not always justified; it can impose on the researcher simplified and, as a result, erroneous schemes of interpretation, where all situational deviations from a certain normative model are considered as erroneous or accidental.

In this sense, rigorous methods of testing hypotheses cannot give an idea of ​​the deep social context of the studied relationships; they act only as source material for further interpretation and explanation. As G.S. Batygin, “the actual sociological interpretation lies “beyond” empirical data and is determined by the specifics of the phenomenon or process being studied. It includes the idea of ​​a specific situation in which the act of measurement is “inscribed” (observation, questioning, experiment). In this case, the latter becomes one of the elements of the life situation, i.e. object of study".

Thus, along with direct formalized verification of hypotheses, the sociological interpretation scheme also includes some non-formalized ideas, knowledge, intuition of the researcher, which form that specific social context that allows one to choose from many possible “readings” of empirical data one that is most adequate to reality.

II . Explanation Procedure. If information is analyzed within the framework of an explanatory type of research, then we do not have the right to limit ourselves to descriptive procedures, we need to deepen the interpretation and proceed to explain the facts by identifying possible influences on aggregated properties, identified social types, etc.

Under explanation the function of scientific knowledge is understood, carried out either by comprehending the law to which the object under study is subject, or by establishing those connections and relationships that constitute its essential features. In essence, explanation in science is the act of including empirical knowledge about the object (process, phenomenon) to be explained in a broader context of theoretical knowledge.

Depending on the type of connection between the object and the factors, conditions, etc. that determine it, there are several basic forms of scientific explanation.

Causal, when:

a) one object (phenomenon, process) is explained by establishing a regular connection with other objects that precede it in time;

b) the current state of the object is explained by its past states.

genetic when the object being explained is included in the chain of cause-and-effect relationships, within which it, being a consequence of one phenomenon, itself becomes the cause of another. Moving along this chain to the initial state of the object, we can reconstruct its genesis as a whole, which allows us to give the most reliable forecast of its changes in the future.

Structural-functional, when a social object is considered as a structurally dissected integrity, each element of which performs a certain role in the system, i.e. has its own functional purpose, which means that it behaves in a natural way in accordance with its place in the structure of the object.

According to the criterion of reliability, one can distinguish confident and alleged explanation.

A confident explanation is carried out when the empirical information necessary to establish causation between the object and the factors influencing it, is contained in full in the source materials of the study. However, this kind of explanation is possible only in relation to some particular tendencies, limited in their spatio-temporal parameters. In the OSI, in addition, a necessary (but not sufficient) condition for a confident explanation is the presence of the results of a series of repeated measurements of the monitoring type, which would demonstrate an obvious trend in the change in the state of the social object.

But, as a rule, when studying a social phenomenon, its explanation requires going beyond the boundaries of available empirical information: secondary data analysis, appeal to the specific social context of the phenomenon under study, cultural and historical comparisons, etc. In this case, we can only talk about an explanation of a hypothetical nature, when all of the above procedures confirm the conclusions made, however, the information that they (procedures) allow to obtain is not contained directly in the source materials of this study.

Let us give an example of this kind of qualitative analysis carried out by Belarusian State University sociologists in 1994 when studying the influence of the Chernobyl factor on the growth of religiosity of the population living in the zone radioactive contamination. The initial hypothesis here was that any cataclysms of a catastrophic nature that cause sharp and long-term negative changes in the lives of large masses of people (wars, revolutions, economic crises) in one way or another contribute to the strengthening of religiosity in any society. This is evidenced by the data of world and national history. To test the hypothesis during the survey, two sub-samples were formed: the first consisted of people living in the Chernobyl zone, whose health (and sometimes life) is under constant threat; the second was made up of people living in “clean” places. Given the equality of their basic socio-demographic characteristics, the differences in the level of religiosity could be attributed to the disturbing influence of the Chernobyl factor. However, the results of the survey did not reveal the expected differences: the number of believers in both sub-samples turned out to be approximately the same. As hypotheses explaining this fact, the following assumptions were put forward:

1. Possibly impact Chernobyl disaster on the state of mass consciousness is of an indirect, complex nature: if in the first years of perestroika it (the catastrophe) was a unique event against the backdrop of relative political and economic stability, then after 1991 this stability was drastically lost. Negative factors of economic and political life came to the fore (the collapse of the USSR, economic collapse, etc.), which, in terms of their significance for the personal destinies of people, turned out to be comparable to Chernobyl, and in some ways “blocked” it. To prove this assumption, a comparative analysis of two studies conducted by different research groups of BSU in 1990 and 1994 was carried out. Both surveys were conducted in both “clean” and contaminated areas of the Republic of Belarus (see Table 5.14).

Table 5.14

Significance of Chernobyl problems for the population of the Republic of Belarus (in %)

The data given in the table testify to the following. The number of those who assess the Chernobyl problems as the most important for themselves is approximately the same, although it would be more logical to expect the significance of the event to fade with time. This, however, did not happen; on the contrary, the proportion of people for whom the Chernobyl problems have receded into the background has halved (from 29.7% to 13.7%). At the same time, the number of those for whom these problems are quite acute, but along with other equally important problems, has grown significantly (from 30.9% to 47.5%).

Thus, a descriptive analysis of the comparative data presented in Table 5.14 leads to the following explanation:

The significance of the Chernobyl factor in the mass consciousness does not decrease with time, but in the context of a general systemic crisis, the role of economic and political factors increases, they seem to “catch up” in importance with the Chernobyl problems and form in subjective perception a single crisis syndrome that negatively affects the psycho-emotional state of people.

In other words, the Chernobyl factor ceases to influence the consciousness of the affected population in its “pure” form on its own and begins to influence indirectly, through a combination of socio-economic factors (material difficulties, the inability to purchase environmentally friendly products, poor health, etc.). And this factor of living conditions is common to the entire population of the Republic of Belarus, regardless of place of residence.

2. The second hypothesis, designed to explain the absence of a visible influence of the Chernobyl factor on the religiosity of the population, is related to the specifics of the vision of the causes of the accident by believers of different confessional trends.

In both sub-samples, two-thirds of believers are Orthodox, about 17% are Catholics. The share of representatives of other confessions turned out to be statistically unreliable, therefore, in order to control the data, in addition to the population living in the “dirty” and “clean” zones, a survey was conducted among the parishioners of the three main Christian denominations in Minsk: Orthodox, Catholics and Protestants. An analysis of the comparative results showed that they assess the causes of the Chernobyl disaster in a very different way (see Table 5.15). As such reasons, the survey featured the main polar dichotomy of judgments, one of which was rational-secular in nature (“this is the result of human irresponsibility, God has nothing to do with it”), and the second came down to a religious-sacred interpretation (“this is the result of divine providence, punishment for the sins of the people).