## BA in Statistics Requirements

**These requirements apply to all students in the Class of 2024 and later.** Students in earlier classes may follow the old requirements.

For any questions relating to the major, please contact Professor Ciminelli. You should talk with an advisor before declaring your major. If you are ready to declare your major, complete the online major declaration form.

### Prerequisite Courses (Three Courses)

The following courses, or their equivalents are required:

- MATH 161: Calculus Ia*
- MATH 162: Calculus IIa*
- STAT 212: Applied Statistics I **

*MATH 171 and 172, or MATH 141, 142, and 143 can be taken in place of MATH 161 and 162.

**STAT 213, or STAT 214, or STAT 262, or equivalent with advisor permission can be taken in place of STAT 212

### Core Courses (Three Courses)

The following courses, or their equivalents are required:

- STAT/MATH 201: Introduction to Probability
- STAT/MATH 203: Introduction to Mathematical Statistics
- STAT 216: Applied Statistical Methods I*

**Double majors with economics may substitute ECON 231W: Econometrics for STAT 216.*

### Computational Courses (Two Courses)

Choose two of the following:

- STAT 275(W): R Programming
- STAT 276(W): Statistical Computation in R
- STAT 277: Introduction to Statistical Software and Exploratory Data Analysis
- CSC 171: Introduction to Computer Science
- CSC 172: Data Structures and Algorithms

It is highly recommended to have at least one STAT-listed computing course for the major.

### Methods Courses (Two Courses)

Choose two of the following:

- STAT 219: Nonparametric Inference
- STAT 221W: Sampling Techniques
- STAT 223: Introduction to Bayesian Inference
- STAT 226W: Introduction to Linear Models

### Applications Courses (Two Courses)

Choose two of the following:

- STAT 215: Design and Analysis of Experiments
- STAT 217: Applied Statistical Methods II
- STAT 218: Introduction to Categorical Data Analysis
- STAT 219: Nonparametric Inference (for students in the Class of 2026 and previous)
- DSCC 265: Intermediate Statistical Methods

### Upper-Level Elective Courses (Two Courses)

Choose two of the following courses:

- Any non-introductory 200-level STAT course
- MATH 202: Introduction to Stochastic Processes
- MATH 208: Operations Research I
- MATH 209: Operations Research II
- MATH 217: Mathematical Modeling in Political Science
- MATH 218: Introduction to Mathematical Modeling in the Life Sciences
- PSCI 205: Data Analysis II
- PSCI 281: Formal Models in Political Science
- PSCI 288: Game Theory
- ECON 223: Labor Markets
- ECON 224: Sports Economics
- ECON 225: Freakonomics
- ECON 233: Financial Econometrics
- ECON 237: Economics of Education
- ECON 253: Economics of Discrimination
- BCSC 236: Machine Vision
- BCSC 247: Topics in Computational Neuroscience
- CSC 242: Introduction to Artificial Intelligence
- CSC 246: Machine Learning
- CSC 249: Machine Vision
- CSC 264: Computer Audition
- CSC 282: Design and Analysis of Efficient Algorithms
- CSC 284: Advanced Algorithms
- CSC 286: Computational Complexity
- DSCC 201: Tools for Data Science
- DSCC 265: Intermediate Statistics and Computational Methods
- DSCC 275: Time Series Analysis and Forecasting in Data Science
- PHIL 212: Probability, Inference, and Decision
- PHIL 215: Intermediate Logic
- PHIL 216: Mathematical Logic
- PHIL 217: Uncertain Inference
- FIN 205: Financial Management (FIN 204 cannot be used in place of FIN 205)
- FIN 206: Investments
- MKT 212: Market Research and Analytics
- LING 250: Data Science for Linguistics
- LING 281: Statistical and Neural Computational Linguistics

The upper-level writing requirement is satisfied any two of the following courses: STAT 221W, STAT 226W, STAT 275W, or STAT 276W.

### Overlap

Double and triple majors with statistics and biology, economics, engineering, mathematics, political science, psychology or other areas are possible. Only three courses may overlap between any two majors.