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Major Requirements

Requirements for a BA in Statistics

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

Prerequisite courses:
  • MATH 161 and 162 (or MATH 171 and 172, or MATH 141, 142, and 143)
  • STAT 212 (or STAT 213, or STAT 214, or STAT 262, or equivalent with advisor permission)
Core courses (3 required):
  • STAT/MATH 201: Introduction to Probability
  • STAT/MATH 203: Introduction to Mathematical Statistics
  • STAT 216: Applied Statistical Methods I

Note: Double majors with Economics may substitute ECON 231W (Econometrics) for STAT 216.

Computational courses (any 2 from the following list):
  • STAT 276(W): Statistical Computation in R
  • STAT 277: Introduction to Statistical Software and Exploratory Data Analysis
  • CSC 171: Introduction to Computer Science (permission secured)
  • CSC 172: Data Structures and Algorithms (permission secured)
Methods courses (any 2 from the following list):
  • STAT 221W: Sampling Techniques 
  • STAT 223: Introduction to Bayesian Inference
  • STAT 226W: Introduction to Linear Models
Applications courses (any 2 from the following list):
  • STAT 217: Applied Statistical Methods II
  • STAT 218: Introduction to Categorical Data Analysis
  • STAT 219: Nonparametric Inference
  • DSCC 265: Intermediate Statistical Methods
Upper-level elective courses (any 2 from the following list):
  • Any 200-level STAT course
  • MATH 202: Introduction to Stochastic Processes
  • MATH 208: Operations Research I
  • 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, or STAT 276W.

Double Majors—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.

Joint Major—The BA degree with a joint concentration in mathematics and statistics is also offered.

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