Data Analysis in Practice

3.0 credits · Graduate

The goal of this course is to expose students to common data analysis methods used in social science research. Topics covered will include t-tests, one-way ANOVA, factorial ANOVA, regression, mediation, repeated-measures ANOVA, mixed models analysis, non-parametric tests, reliability theory, factor analysis, power, and meta-analysis. Students will learn how to conduct these analyses on statistical computing packages, how to choose the right analysis to answer a practical research question, and how to report the results of the analyses. This course is designed for doctoral students.