A representative sample is usually several hundred, sometimes a thousand, respondents. Therefore, the starting point for calculating the selection becomes the question of determining the size of the sample population. The larger the sample sizes, i.e., the closer they are to the general population’s extent, the more reliable and reliable the data obtained. However, the main problem of the representative sample is the practical impossibility of continuous surveys in those cases when they are carried out at objects, the number of which exceeds tens, hundreds of thousands.
The sampling error may depend not only on its size but also on the degree of differences between individual units within the general population being studied. Thus, the sample size depends on the level of homogeneity or heterogeneity of the studied objects (Woiceshyn & Daellenbach, 2018). The more homogeneous they are, the smaller the number can provide statistically reliable conclusions. The survey technique for solving these problems is to analyze and structure the entire complex of the problem (subject area).
Deductive reasoning is reasoning to which a criterion of validity or logical correctness can be applied. Thus, in this case, the formulation of the problem and the development of the research methodology (formation and approval of the technical task) will become a deductive argument (Hayes et al., 2018). Developing and coordinating with the customer the primary methods of collecting information, including questionnaires, registration forms, and sampling principles, is also a reasoned argument.
The probability of inference is the main characteristic of inductive arguments; therefore, in this case, to improve the methodology, a more significant number of respondents can be taken. Thus, deductive and inductive arguments are justified since, otherwise, developing a new process and agreement on the basic methods of collecting foreign exchange will lead to more personal data (Stephens et al., 2018). In the case of the inductive method, validity lies in the greater likelihood of obtaining more accurate results by increasing the number of respondents.
References
Hayes, B. K., Stephens, R. G., Ngo, J., & Dunn, J. C. (2018). The dimensionality of reasoning: Inductive and deductive inference can be explained by a single process. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(9), 1333–1351. Web.
Stephens, R. G., Dunn, J. C., & Hayes, B. K. (2018). Are there two processes in reasoning? The dimensionality of inductive and deductive inferences. Psychological Review, 125(2), 218–244. Web.
Woiceshyn, J. & Daellenbach, U. (2018). Evaluating inductive vs deductive research in management studies: Implications for authors, editors, and reviewers. Qualitative Research in Organizations and Management, 13(2), 183-195. Web.