Statistics - Minor in Statistics

Return To: College of Arts & Sciences: Minor Programs

The minor in Statistics is for students with some prior experience with statistics and computing who would like a deeper understanding of data and statistics. This minor assumes prior experience with statistics and computing before declaring, allows more student flexibility for a combination of theory and analytics, and includes only STAT courses.

Requirements for Minor in Statistics

The minor in Statistics requires two core courses and three restricted elective courses. In total the minor in Statistics requires 15 credit hours, plus prerequisite courses. There are two lists of restricted elective courses, those that focus on data analysis and those that are more computational. Of the three restricted elective courses, at least one must be taken from the Data Analysis list. A grade of C- or higher is required for all prerequisite and minor courses.

Prerequisites:

Students must have completed all prerequisite courses to declare the minor. Students may use AP credit to meet the prerequisite requirements.

Calculus

Complete one of the following:
MATH 1210 - A survey of Calculus I Credits: 3
MATH 1310 - Calculus I Credits: 4
APMA 1090 - Single Variable Calculus I Credits: 4
Introduction to data analysis and computing

Complete one of the following:
STAT 1601 - Introduction to Data Science with R Credits: 3
STAT 1602 - Introduction to Data Science with Python Credits: 3
OR

Complete one of the following:
STAT 1100 - Chance: An Introduction to Statistics Credits: 3
STAT 1120 - Introduction to Statistics Credits: 3
STAT 2020 - Statistics for Biologists Credits: 4
STAT 2120 - Introduction to Statistical Analysis Credits: 4
APMA 3110 - Applied Statistics and Probability Credits: 3
APMA 3120 - Statistics Credits: 3
AND

Complete one of the following:
CS 1110 - Introduction to Programming Credits: 3
CS 1111 - Introduction to Programming Credits: 3
CS 1112 - Introduction to Programming Credits: 3
CS 1113 - Introduction to Programming Credits: 3

Core Courses:

Statistical linear modeling

Complete the following:
STAT 3220 - Introduction to Regression Analysis Credits: 3
Statistical Computing

Complete one of the following:
STAT 3080 - From Data to Knowledge Credits: 3
STAT 3250 - Data Analysis with Python Credits: 3

Restricted Electives:

The Data Analysis restricted electives and the Computational restricted electives are listed below. Students must take three restricted electives, with at least one from the Data Analysis list.

Data Analysis Restricted Electives
STAT 3120 - Introduction to Mathematical Statistics Credits: 3
STAT 3130 - Design and Analysis of Sample Surveys Credits: 3
STAT 3480 - Nonparametric and Rank-Based Statistics Credits: 3
STAT 4120 - Applied Linear Models Credits: 3
STAT 4130 - Applied Multivariate Statistics Credits: 3
STAT 4160 - Experimental Design Credits: 3
STAT 4170 - Financial Time Series and Forecasting Credits: 3
STAT 4220 - Applied Analytics for Business Credits: 3
STAT 4630 - Statistical Machine Learning Credits: 3
STAT 4800 - Advanced Sports Analytics I Credits: 3
Computational Restricted Electives
STAT 3080 - From Data to Knowledge Credits: 3
STAT 3250 - Data Analysis with Python Credits: 3
STAT 3280 - Data Visualization and Management Credits: 3