STAT 271 Introduction to Computations in Statistics

This course introduces modern computational techniques used in Statistics, which will prepare students for future courses in statistics and other quantitative disciplines. In this course, students learn to apply sampling-based simulation methods which include random number generation, Monte Carlo estimation, permutation tests, Bootstrap techniques to explore statistical models. R, a widely used statistical language for research and industry, will be used throughout the course for statistical computations. Specifically, students learn the R basic syntax that is necessary to write code to access information from a variety of data sources; combine, transform, and manipulate data sets; summarize and interpret data; create informative graphs and analyze data using both modern and classical statistical techniques.

Credit 3 hrs May not be repeated for additional credit
Grade Mode Normal (A-F) Course Rotation Winter

Prerequisites - STAT 170, STAT 360, DS 265, or ECON 310
Other Restrictions -
Restriction by Major -
Restriction by Class - Undergraduate standing

Additional Information - A student who previously completed an elementary statistics course may request permission to enroll in this course.

Keywords: statistics, mathematics
Updates: New course 3/2019, effective Fall 2019

Winter 2025 Course Sections

Summer 2025 Course Sections

Fall 2025 Course Sections