Introduction to Advanced Statistics

CLI RS701 - Introduction to Advanced Statistics

Credits: 2

This course is divided into two main topic areas. The first half of the course is designed to review concepts covered in RS526-Statistics and to provide opportunity for students to gain mastery over running these tests and writing up results in APA style. Students will have opportunities to work with datasets provided by the instructor that are reflective of what students can expect in the real world (i.e., incomplete responses, missing data, invalid participant responses, etc). Students will learn how to work with these datasets to develop their analytic sample and to run basic descriptive statistics and inferential statistical tests. Students will gain expertise reporting results of these tests in APA style results sections. The primary goal of this half of the semester is to enhance student abilities to complete dissertation analyses.

The second half of the course is designed to introduce students to advanced statistics topics that are becoming more commonplace in psychological research. These topics largely center around structural equation modeling (SEM), but also cover topics such as mediation, hierarchical linear modeling, and machine/deep learning and artificial intelligence. The goal of this course is not to provide students with the knowledge or expertise needed to run any of these statistics, but instead to provide students with an introduction to these topics so they can appropriately critique and summarize scientific literature that employs these methods. As the methods used by our field become increasingly sophisticated, it will become increasingly important for students to understand these methods in order to stay current with empirical research.

Pre-requisite: RS526 - Statistics