Course EE 5373

Data Modeling Using R

 

Course Description:

Do you want an introduction to the R programming language?
Do you want an introduction to data modeling?
Do you need just one more credit?

Then this course is for you.

Learning about the broad field of data modeling really consists of learning a range of statistical tools and techniques. Regression modeling is one of those fundamental techniques and the R programming language is one of the fundamental tools. R is widely used by statisticians, scientists, and engineers for a broad range of statistical analyses. An understanding of R is a useful skill for anyone who is interested in performing most types of data analysis. In this course, you will obtain hands-on experience using R to develop regression models from large data sets. Enrollment will be limited to facilitate in-class interactions.

In this one-credit, lab-focused course, you will:

  • Learn how to develop multifactor linear regression models using a standard statistical approach.
  • Learn how to train and test regression models.
  • Learn how to predict responses from regression models.
  • Learn how to use the interactive R computing environment.
  • Learn the fundamentals of R programming.

 

Prerequisite:

You should have basic programming skills in some high-level language, such as C/C++, Java, Fortran, etc. and basic knowledge of probability and statistics.

 

Instructor:

David J. Lilja
- Office: 6-131 Keller Hall
- Email: lilja@umn.edu

 

Textbook

Linear Regression Using R: An Introduction to Data Modeling, by David J. Lilja, University of Minnesota Libraries Publishing, 2016.