RS 930 Statistics for Health and Rehabilitation Sciences I

Course Overview

This course provides an introduction to univariate statistical analyses used in health sciences research. During weekly seminars, students will gain firsthand experience analyzing data in R. The overarching goal of the course will be to learn how to analyze, interpret, and communicate the results of statistical analyses. Emphasis will be on the practical application of statistical methods to address research hypotheses. We will also interpret and critique the statistical methods present in research articles in the health sciences. At the end of the course, students will have a statistical foundation they can apply to their own research, or build upon to learn more advanced statistical techniques.

Course Objectives

At the conclusion of this course, students will be able to:

• Formulate testable hypotheses based on given research questions
• Determine the independent and dependent variables and the levels of measurement of variables in a research study
• Select, justify, and perform the appropriate statistical analyses for a given a research question using R
• Correctly interpret the results of statistical analyses
• Create visual displays of data (i.e., tables and figures) appropriate for publication in a peer-reviewed journal
• Write a data analysis and results section in APA format suitable for publication in a peer-reviewed journal
• Critically evaluate the data analytic procedures and methods in published scientific research

Course Texts

• Field, A., Miles, J., & Field, Z. (2013). Discovering statistics using R. Los Angeles, Calif: Sage.

• Cumming, G. (2012). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. Routledge.

• Navarro, D. Learning Statistics with R. https://compcogscisydney.org/lsr/lsr-0.6.pdf This is a free, open-source statistics textbook that has a nice introduction to using R.

Other books/online resources that may be useful to you:

• Wickham, H., & Grolemund, G. (2017). R for Data Science: Visualize, model, transform, and import data.. Available for free at: https://r4ds.had.co.nz/introduction.html . If you want to have a hard copy, you can purchase through Amazon.

• Chang, W. (2012). R Graphics Cookbook. Available on Amazon. You can also access a pared-down version online for free: http://www.cookbook-r.com/Graphs/

• Because R is free and open-source, there are hundreds (if not thousands) of online resources available. Dr. Google will be your best friend this semester.