AMS 394: Statistical Laboratory

Teaching connection: Graduate instructor in Fall 2022 and Fall 2023.

This page is part of my personal academic record, not an official course website.

Course description

Designed for students interested in statistics and its applications. Basic statistical techniques including sampling, design, regression, and analysis of variance are introduced. Includes the use of statistical packages such as SAS and R. Students translate realistic research problems into a statistical context and perform the analysis.

Textbooks and resources

Supplementary textbooks

• Introductory Statistics with R by Peter Dalgaard, 2nd edition, 2008, Springer
• The Little SAS^® Book: A Primer by Lora D. Delwiche and Susan J. Slaughter, 6th edition, 2019, SAS Institute
• Applied Statistics and the SAS^® Programming Language by Ronald P. Cody and Jeffrey K. Smith, 5th edition, 2005, Pearson

Learning outcomes

Upon successful completion of this course, students should be able to:

1. Understand basic concepts and operations in R and SAS.
2. Know how to read and work with data in R and SAS.
3. Conduct \(t\) tests and nonparametric tests (one-sided, two-sided, one-sample, two-sample) in R and SAS.
4. Conduct linear regression and variable selection in R and SAS.
5. Conduct ANOVA (one-way and two-way) in R and SAS.
6. Conduct \(\chi^2\) tests in R and SAS.

Fall 2023 syllabus · Back to Teaching & Mentoring · Back to Graduate Studies