Sociological surveys of the population are often conducted among large groups of people. The idea that the reliability of the results will be higher if each member of the society answers the questions is often erroneous. Due to the enormous time, money and laboriousness, such a survey is unacceptable. With an increase in the number of respondents, not only will expenses increase, but the risk of receiving incorrect data will also increase. From a practical point of view, many questionnaires and encoders will reduce the likelihood of reliable control of their actions. Such a survey is called continuous.
In sociology, an incomplete study, or a selective method, is most often used. Its results can extend to a large population of people, which is called the general.
Definition and significance of the selective method
Selective method - this is a quantitative way of selecting a part of the studied units from the total mass, while the results of the survey will be distributed to each individual who has not taken part in this.
The selective method is both the subject of scientific research and academic discipline. It acts as a means of obtaining reliable information about the general population and helps to evaluate all its parameters. The conditions for the selection of units subsequently affect the statistical analysis of the results. If selective procedures are carried out poorly, the use of even the most reliable methods of processing the collected information will be useless.
Key concepts of choice theory
A general population is the interconnection of units with respect to which the conclusions of a sample study are formulated. As it can be the residents of one country, a specific locality, the work team of the enterprise, etc.
The sample population (or sample) is part of the general population, which was selected using special techniques and criteria. For example, in the process of formation statistical criteria are taken into account.
The number of individuals included in a given population is called its volume. But it can be expressed not only by the number of people, but also by polling stations, settlements, that is, definitely large units, including observation units. But this is already a multi-stage sampling.
The unit of selection is the constituent parts of the general population; they can be either directly observation units (single-stage sampling) or larger units.
A large role in obtaining reliable research results using the selective method is such a property as representativeness of selection. That is, the part of the general population that has become respondents should fully reproduce all its characteristics. Any deviation is considered a mistake.
Stages of applying the selective method
Each empirical case study consists of stages. In the case of applying the selective method, their priority will be arranged as follows:
- Creating a sample design: the general population is established, selection procedures, volumes are characterized.
- Implementation of the project: during the collection of sociological information, the questionnaires complete tasks with an indication of the method of selecting respondents.
- Identification and correction of representativeness errors.
Types of Samples in Sociology
After determining the population, the researcher proceeds to sample procedures. They can be divided into two types (criteria):
- The role of probabilistic laws during sampling.
- The number of stages of selection.
If the first criterion is applied, then random sampling and non-random selection are distinguished. Based on the latter, it can be argued that the sample can be single-stage and multi-stage.
Sample Types directly reflected not only at the stages of preparation and conduct of the study, but also on its results. Before you give preference to one of them, you should understand the content of concepts.
The definition of "random" in everyday use has received a completely opposite meaning than in mathematics. Such selection is carried out according to strict rules, no deviation from them is allowed, since it is important to ensure that each unit in the population has the same chance of being included in the sample. If these conditions are not met, this probability will be different.
In turn, random sampling is divided into:
- simple;
- mechanical (systematic);
- nesting (serial, cluster);
- stratified (typical or regionalized).
Simple Type Content
A simple sampling method is done using a table random numbers. Initially, the sample size is determined; a complete list of numbered respondents in the general population is created. Special tables are used for selection contained in mathematical and statistical publications. Any use different from them is prohibited. If the sample size represents a three-digit number, then the number of each selection unit should be three-digit, namely: from 001 to 790. The last number means the total number of people. The study will be attended by those people who were assigned a number in the specified range, which appears in the table.
Systematic content
Systematic selection is computationally based. An alphabetical list of all elements of the general population is preliminarily compiled, a step is established, and only then, the sample size. Formula for step presented as follows:
N: n, where N is the population and n is the sample.
For example, 150,000: 5,000 = 30. Thus, one in thirty people will be selected to participate in the survey.
Socket Type Essence
Nest sampling is used in conditions if the studied population of people consists of small in the number of natural groups. In this case, it should be noted that at the first step the list number of such nests is determined. Using a table of random numbers, selection is made and a continuous survey of all respondents consisting in each selected nest is carried out. Moreover, the more they took part in the study, the smaller the average sampling error. However, it is possible to use such a technique provided that there is a similar feature in the studied nests.
The essence of stratified choice
A stratified sample differs from the previous ones in that, on the eve of the selection, the general population is divided into strata, that is, homogeneous parts that have a common feature. For example, the level of education, electoral preferences, level of satisfaction with various aspects of life. The simplest option is to divide the subjects by gender and age. It is fundamentally necessary to conduct a selection in such a way that from each stratum a number of persons is allocated that is proportional to the total number.
The sample size in this case may be less than in the situation with random sampling, but the representativeness will be higher. It should be recognized that stratified sampling will be the most expensive financially and informationally, and nested sampling will be the most profitable in this regard.
Non-random quota sampling
There is also quota sampling. She is the only type of nonrandom selection that has a mathematical justification. A quota sample is formed from units that should be represented by proportions and correspond to the general population. In this form, a targeted distribution of characteristics is carried out. If the studied signs are opinions and assessments of people, then gender, age, and respondent education are often quota-based.
In a sociological study, two methods of selection are also distinguished: repeated and non-repeated. At the first, the selected unit after the survey returns to the population to continue to participate in the selection. In the second option, respondents are sorted, which increases the chances of the remaining members of the population to be selected.
The sociologist G. A. Churchill developed the following rule: the sample size should strive to provide at least 100 observations for the primary and 20-50 for the secondary classification component. It should be borne in mind that some of the respondents included in the sample, for various reasons, may not participate in the survey or refuse it at all.
Ways to determine sample size
In sociological research, the following methods are applicable:
1. Arbitrary, that is, the sample size is determined within 5-10% of the composition of the general population.
2. The traditional method of calculation is based on regular studies, for example, once a year with the coverage of 600, 2,000 or 2,500 respondents.
3. Statistical - is to establish the reliability of information. Statistics as a science does not develop in isolation. The subjects and areas of her research are actively involved in other related industries: technical, economic and humanitarian. So, its methods are used in sociology, in preparation for surveys, and, in particular, in determining sample sizes. Statistics as a science has an extensive methodological base.
4. Cost, in which the permissible amount of research costs is established.
5. The sample size may be equal to the number of units of the population, then the study will be continuous. This approach is applicable in small groups. For example, the labor collective, students, etc.
Previously, it was possible to establish that the sample will be considered representative when its characteristics describe the properties of the general population with a minimum error.
The estimation of the sample size precedes the final calculations of the number of units that will be allocated from the general population:
n = Npqt 2 : Nβ 2 p + pqt 2 , in which N is the number of units of the general population, p is the share of the trait being studied (q = 1 - p), t is the coefficient of correspondence of the confidence probability P (determined by a special table), Ξ p - permissible error.
This is just one option for how sample size is calculated. The formula may vary depending on the conditions and selected research criteria (for example, repeated or non-repeated sampling).
Sampling Errors
Sociological surveys of the population are based on the use of one of the types of samples that we examined above. However, in any case, the task of each researcher should be to assess the degree of accuracy of the indicators obtained, that is, it is necessary to determine how much they reflect the characteristics of the general population.
Sampling errors can be divided into random and nonrandom. The first type implies the deviation of the sample indicator from the general one, which can be expressed by the difference in their shares (average) and which is caused only by a non-continuous type of examination. And it is completely natural if this indicator decreases against the background of an increase in the number of respondents surveyed.
A systematic error is a deviation from the general indicator, also found as a result of subtracting the sample and general share and arising from the inconsistency of the sampling methodology with the established rules.
These types of errors are included in the general sampling error. In the study, only one sample can be extracted from the population. The calculation of the maximum possible deviation of the sample indicator can be performed using a special formula. It is called marginal sampling error. There is also such a thing as average sampling error. This is the standard deviation of the sample from the total shares.
The posterior (post-experimental) type of error is also distinguished. By it is meant the deviation of the selective indicators from the general share (average). It is calculated by comparing the general indicator, information about which came from reliable sources, and the sample one that was established during the survey. Reliable human resources departments and state statistics bodies often act as reliable sources of information.
There is also an a priori error, which is also a deviation of the sample and general indicators, which can be expressed by the difference in their shares and which can be calculated using a special formula.
In educational research, the following errors are most often made related to the selection of respondents for the survey:
1. Selected sets of groups belonging to different general ones. When using them, statistical conclusions are developed that apply to the entire sample. Obviously, this may not be acceptable.
2. The organizational and financial capabilities of the researcher are not taken into account when the types of samples are considered, and one of them is preferred.
3. The statistical criteria of the structure of the population are not fully used to prevent sampling errors.
4. The requirements of representativeness of the selection of respondents in the course of comparative studies are not taken into account.
5. The instructions for the interviewer should be adapted taking into account the specifics of the type of selection adopted.
The nature of respondent participation in the study may be open or anonymous. This should be taken into account when forming the sample, because, disagreeing with the conditions, participants may retire.