Using the development of and differences on self-report measures to learn data analysis

Abstract

The purpose of the current study was to collect data from self-report measures (happiness, extraversion, depression, self-image, and self-esteem) created by laboratory students in conjunction with validated measures of state self-esteem, sensation seeking, and demographic variables that would allow for the reasonable application of a variety of descriptive and inferential statistical techniques to learn data analysis. An undergraduate under faculty supervision performed reliability analysis, correlational analysis, independent samples t tests, analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA), and created a multiple regression model to better understand the application and conceptual logic underlying many of the statistical tests used in contemporary psychology. It was predicted this model would further develop critical thinking and provide additional practice conducting research

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