About the course
Medical Statistics I is the first in a three-course statistics series. Medical Statistics I covers the foundations of data analysis, programming in either R or SAS (students may use either program), descriptive statistics, visualizing data, study design, and measures of disease frequency and association. The course uses real examples from the medical literature and popular press. Participants will learn how to critically evaluate the statistics in medical studies. The course also prepares participants to be able to analyze their own data.
Prerequisites: There are no prerequisites for this course. Students will need to be familiar with a few basic math tools: summation sign, factorial, natural log, exponential, and the equation of a line; a brief tutorial is available on the course website for students who need a refresher on these topics.
What you will learn
- Basic programming in either SAS or R.
- How to visualize and describe data.
- How to calculate and interpret measures of disease frequency and association.
Kristin Sainani (née Cobb) is an associate professor at Stanford University and also a health and science writer. After receiving an MS in statistics and a PhD in epidemiology from Stanford University, she studied science writing at the University of California, Santa Cruz. She has taught statist...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.