Minor in Statistics

This minor is for students with some prior experience with statistics, mathematics, and computing who would like a deeper understanding of data and statistics.  The minor requirements are purposely flexible to allow students to tailor their choice of courses to complement their other academic interests.  Upon completion students will have a solid understanding of where, when, and why different statistical methods are appropriate for different types of data. 

Note: Courses applied to minor requirements may not also be used to fulfill requirements for a major or another minor. (Double counting is not allowed.)

Prerequisites : To declare the Minor in Statistics, students need credit for each the following:

1) Calculus 1: One of the following

  • MATH 1210: A Survey of Calculus I
  • MATH 1310: Calculus I
  • APMA 1090: Single Variable Calculus I

2) Introduction to Data Analysis and Computing: One of

  • STAT 1601: Introduction to Data Science with R
  • STAT 1602: Introduction to Data Science with Python

(This requirement also can be met with one of STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, ANTH 4840, PLAD 2222, PSYC 2005, SOC 3130 AND one of CS 1110, CS 1111, CS 1112, CS 1113, PHYS 2660)

 Required Courses :

1) One of

  • STAT 3220: Introduction to Regression Analysis

2) One of

  • STAT 3080: From Data to Knowledge
  • STAT 3250: Data Analysis with Python
  • STAT 3280: Data Visualization and Management
  • STAT 3430: Statistical Computing SAS/R
  • STAT 4210: Big Data Tools
  • STAT 4260: Databases
  • STAT 4310: Data Visualization and Presentation

3) Three electives total, selected from the Computational Electives list and the Data Analysis list below, with at least one course from each list.
Computational Electives

  • STAT 3080: From Data to Knowledge
  • STAT 3240: Programming in Matlab/Mathematica
  • STAT 3250: Data Analysis with Python
  • STAT 3280: Data Visualization and Management
  • STAT 3430: Statistical Computing SAS/R
  • STAT 4210: Big Data Tools
  • STAT 4260: Databases
  • STAT 4310: Data Visualization and Presentation

Data Analysis Electives

  • STAT 3120: Mathematical Statistics
  • STAT 3130: Sample Surveys
  • STAT 3480: Nonparametric and Rank-Based Statistics
  • STAT 4160: Experimental Design
  • STAT 4170: Financial Times Series and Forecasting
  • STAT 4220: Applied Analytics for Business
  • STAT 4630: Statistical Machine Learning
  • STAT 4996: Capstone

 

Prerequisites for Selected Courses

 

Note: “Introductory statistics course” means credit for any of STAT 1100, STAT 1120, STAT 2020, STAT 2120, or STAT 3120.  “Introductory programming course” means credit for any of the CS 1110, CS 1111, CS 1112, or CS 1113. (Transfer and AP credit are allowed.)

 

STAT 1601:    No prerequisite.

STAT 1602:    No prerequisite.

STAT 2020:    No prerequisite.

STAT 2120:    MATH 1210 or MATH 1310.
STAT 3080:  STAT 1601 or STAT 1602.  (Can also be fulfilled with a combination of an introductory statistics course and an introductory programming course.)
STAT 3110:    MATH 1220 or MATH 1320.
STAT 3120:    STAT 3110 or MATH 3100 or APMA 3100.
STAT 3130:    An introductory statistics course.
STAT 3220:    An introductory statistics course.
STAT 3250:  STAT 1601 or STAT 1602.  (Can also be fulfilled with a combination of an introductory statistics course and an introductory programming course.)
STAT 3480:    An introductory statistics course.
STAT 4630:    STAT 3220, ECON 3720, or STAT 5120; also previous experience with R.
STAT 5120:    STAT 3120 and one of MATH 3350, MATH 3351, APMA 3080.
STAT 5170:    STAT 3120 (also suggested: one of STAT 3220, ECON 3720, STAT 5120)

 

updated July 23, 2020