About The Course
This course is an applied statistics course focusing on data analysis. The course will begin with an overview of how to organize, perform, and write-up data analyses. Then we will cover some of the most popular and widely used statistical methods like linear regression, principal components analysis, cross-validation, and p-values. Instead of focusing on mathematical details, the lectures will be designed to help you apply these techniques to real data using the R statistical programming language, interpret the results, and diagnose potential problems in your analysis. You will also have the opportunity to critique and assist your fellow classmates with their data analyses.
Frequently Asked Questions
- How is this course different from “Computing for Data Analysis”?
This course will focus on how to plan, carry out, and communicate analyses of real data sets. While we will cover the basics of how to use R to implement these analyses, the course will not cover specific programming skills. Computing for Data Analysiswill cover some statistical programming topics that will be useful for this class, but it is not a prerequisite for the course.
- What resources will I need for this class?
A computer with internet access on which the R software environment can be installed (recent Mac, Windows, or Linux computers are sufficient).
- Do I need to buy a textbook?
There is no standard textbook for data analysis. The course lectures will include pointers to free resources about specific statistical methods, data sources, and other tools for data analysis.