Introductory Materials
Introduction to the Course
This course builds on the required statistical sequence and focuses on practical application of statistics including understanding clinical research questions. Analyzing data is the major emphasis of the course including examining if assumptions of the statistical analysis are being met and interpreting the findings. Course assignments focus on using statistical software and computing resources to analyze data sets from actual clinical research studies and interpretation of output and literature.
What are your interests? Project/Study Ideas?
Open discussion
Setting up software for the course
Your options for software for this course include:
- SAS (using SAS University - FREE)
- SPSS (Student Versio - Premium Grad Pack edition preferred - Stadard edition will work)
- R/RStudio - FREE
- https://cran.r-project.org/
- https://www.rstudio.com/products/rstudio/download/
- Git
- It is suggested if you plan on using R/RStudio - also install Git on your computer to enable the version tracking software and “link” back to your Github repositories
- https://git-scm.com/downloads - this includes links for both Windows and Mac
- and for Windows https://git-for-windows.github.io/
- Also see “Happy Git and GitHub for the useR” by Jenny Bryan at http://happygitwithr.com/
- Github
- It is also suggested, even if you do not want to use R/RStudio, go ahead and setup an account on Github, since many of the lessons and code examples will be saved and hosted on Github.
- https://github.com/
Setting up R and RStudio
See Pre R Workshop Setup Instructions This online “Book” has information on R, installing R and RStudio, and places to get help.
Youtube Video on Installing R, RStudio and Compiling your first Rmarkdown report.
Rmarkdown reports
In addition to the YouTube video demonstration above, also learn more at:
Karl Broman’s website Knitr in a Knutshell tutorial
Copyright © Melinda Higgins, Ph.D.. All contents under (CC) BY-NC-SA license,
unless otherwise noted.