PROCESSING STATISTICAL DATA OF PEDAGOGICAL RESEARCH USING THE R LANGUAGE

Abstract

In pedagogical research, statistical analysis plays a special role, since it allows you to assess the effectiveness of methodological approaches, identify correlations between educational factors, and confirm or refute hypotheses. The use of modern data analysis tools helps to increase the accuracy of research, automates computational processes, and improves the visualization of results. One of the powerful tools for processing statistical data in scientific research is the R programming language, which offers a wide range of functions for mathematical modeling, data processing, hypothesis testing, and graphing.The article examines the features of using the R language to process statistical data in pedagogical research. The main R packages and functions that provide processing, visualization, and interpretation of results are analyzed. Methods of descriptive statistics, correlation, and regression analysis are described, as well as their role in confirming scientific hypotheses. Examples of the use of R in the pedagogical field are given, demonstrating the effectiveness and accessibility of this tool for researchers. The study developed a methodology for analyzing the results of pedagogical research in the RStudio environment, and demonstrated the main methods of data processing, visualization and interpretation of the obtained results.The work analyzed in detail the methods of data preprocessing, normalization, descriptive statistics, correlation and regression analysis, as well as statistical hypothesis testing, in particular the t-test, χ²-test and analysis of variance (ANOVA).The proposed approach can be used by researchers in the field of pedagogy who work with empirical data and seek to use modern analysis tools. The use of R provides high flexibility, automation of computational processes and reproducibility of results, which is relevant for scientific research.