Algorithm for verification of data from an empirical study of the economic behaviour of students
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Abstract
The aim of the article is to provide a rationale for the sequence of actions to verify the results of an empirical study of the direction of economic behaviour of young people.
Methods. The algorithm includes the following steps: calculation and analysis of statistical characteristics of the variables under study (to establish homogeneity/heterogeneity of the sample; its correspondence to the normal distribution law and the possibility of further using parametric/non-parametric methods of mathematical data processing); determination of the size of the general population to which the conclusions drawn from the analysis of the survey data can be applied; visualization of statistical indicators using a radar chart (to simplify the identification of a change vector based on the analysis of the content of indicators with scores above average); calculation of the intercorrelation matrix based on the average values of the assessments of students’ economic perceptions and practices (to identify indicators with the highest number of significant correlations and analyse their content, which confirms (or refutes) the assumption made at the stage of radar chart analysis); clustering the data set using the least squares method (to identify the most significant clusters and analyse the content of the indicators that form them, followed by confirmation (refutation) of the assumption made in the previous verification step); building a correlation-factor-cluster model using the R software with the calculation of a number of coefficients (based on the analysis of the model, the final conclusion is made regarding the reliability of the data obtained and their suitability for building a prognostic model).
Results. By applying the described algorithm to verify the data set of the study of youth economic behaviour, the author confirmed the reliability of the data and identified the vector of changes in the economic behaviour of young people.
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References
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