Evaluating The Effectiveness Of A Training Program: A Data-Driven Approach

Abstract

The analysis of various statistical tests and data analytics evaluations reveals significant insights into training pro- gram effectiveness and other domains. Paired t-tests, two-sample tests, and chi-square tests are employed to assess improvements in performance, customer satisfaction, and employee turnover, while predictive modeling techniques like regression analysis and ma- chine learning classify outcomes based on demographic factors. Feature reduction methods such as PCA and LDA streamline variables for clearer insights, enhancing model interpretability across studies in training effectiveness, marketing strategies, and employee performance. These methodologies collectively underscore the importance of data-driven decision-making in optimizing organizational outcomes.