2025-26 CATALOG YEAR

Introduction

Data empowers us to make informed decisions. Through the study of data science and statistics, students learn the skills necessary to extract meaningful insights from data. In addition to core courses in statistics, computer science, and mathematics, the program provides opportunities for students to gain hands-on experience analyzing data in fields of interest to them, through interdisciplinary coursework and research experiences. 

The data science and statistics major prepares students to acquire, analyze, and draw insights from data. Students learn the mathematical and statistical reasoning necessary to build models and the computational skills needed to implement them. They also learn to ask the right questions to understand the context of their data and make ethical data-driven decisions. Students take a mix of applied, computational, and theoretical courses in statistics, computer science, mathematics, and other disciplines. Students take at least one course in a domain area of interest to them, as well as a course emphasizing data ethics and the role of data in society. The major culminates with a capstone experience in which students engage in hands-on analysis of real data, often collaborating with a community organization. 

The data science and statistics minor is applied and interdisciplinary in nature. It can be paired with a wide range of majors, equipping students with skills to analyze data in areas of interest to them. 

Required for the Major in Data Science and Statistics

The major requires the following courses: 

Four Core Data Science & Statistics Courses

1. One introductory data science course chosen from: 

  • DASC 110: Data Science I
  • ANTH 207: Understanding Humans Through Data Science
  • BIOL 280: Experimental Design and Statistics (BIOL prerequisite)

2. DASC 210: Data Science II 

3. STAT 255: Statistical Modeling (previously called Statistics for Data Science) 

4. DASC 420: Advanced Predictive Modeling

Two Core Computer Science Courses

5. One introductory computer science course chosen from:

  • CMSC 140: Introduction to Programming with Python
  • CMSC 150: Introduction to Computer Science 

6. CMSC 225: Database Techniques and Modeling 

Two Core Mathematics Courses

7. MATH 140: Calculus 

8. A linear algebra course chosen from:

  • MATH 205: Applied Linear Algebra
  • MATH 250: Linear Algebra (MATH prerequisite)

Domain Area and Ethics Courses

9. One Advanced Data Analysis in a Domain course chosen from:

  • ANTH 329: Patterns in the Landscape: Archaeology and Spatial Data Science
  • BIOL 360: Introduction to Bioinformatics (BIOL prerequisite)         
  • BIOL 380: Ecological Modeling (BIOL prerequisite)
  • ECON 380: Econometrics 

10. One Course on Data, Ethics, and Society chosen from:

  • PHIL 330: Science vs Pseudoscience (prereq: junior standing)
  • PHIL 380: Ethics of Technology (prereq: junior standing)
  • CMSC 415: Ethics of Modern Computing

Electives

11. One 400-level STAT or DASC elective

12. One additional elective chosen from:

  • 400-level STAT or DASC courses
  • Advanced Data Analysis in a Domain Area courses
  • Data, Ethics, and Society courses
  • Any course chosen from the following list: (check prerequisites)   

BIOL 335: Plant Ecology, BIOL 345: Terrestrial Wildlife Ecology, CMSC 490: Neural Networks, ECON 223: Quantitative Decision Making, ECON 226: Sports Economics and Analytics, ECON 481: Advanced Econometrics & Modeling, GOVT 538: Outside the Margin of Error: Polling and Quantitative Prediction in Modern Politics, MATH 340: Probability, MATH 355: Advanced Linear Algebra for Data Science

Senior Experience

13. One six-unit senior experience chosen from:

  • DASC 698: Data Science and Statistics Senior Seminar
  • A senior experience in another major involving substantial data analysis and approved by a DASC advisor

Required for the minor in statistics and data science

  1. Two core courses:
    1. CMSC/STAT 205: Data-Scientific Programming
    2. STAT 255: Statistics for Data Science
  2. Two statistics and data science electives from the list of:
    • CMSC/STAT 208: Machine Learning
    • CMSC/STAT 405: Advanced Data Computing
    • STAT 450: Bayesian Statistics
    • STAT 455: Advanced Statistical Modeling
  3. Two courses from the following list. (Students may substitute other classes involving data analysis with approval from the department of mathematics, statistics, and computer science).
    • ANTH 207: Quantitative Analysis in Anthropology
    • BIOL 280: Integrative Biology: Experimental Design and Statistics
    • BIOL 360: Introduction to Bioinformatics
    • BIOL 375: Biostatistics
    • BIOL 380: Ecological Modeling
    • CHEM 210 / CHEM 211 Analytical Chemistry and Statistical Methods in Analytical Chemistry
    • CMSC 140: Introduction to Programming with Python
    • CMSC 210: Introduction to Scientific Programming
    • CMSC 470: Artificial Intelligence
    • ECON 223: Quantitative Decision Making
    • ECON 226: Sports Econometrics and Analytics
    • ECON 380: Econometrics
    • ECON 481: Advanced Econometrics & Modeling
    • ENST 235 / GEOS 214: Climate and Climate Change
    • ETST 302: Research Methods in Ethnic Studies
    • GOVT 271: Research Methods in Political Science
    • GOVT 538: Outside the Margin of Error: Polling and Quantitative Prediction in Modern Politics
    • MATH 340: Probability
    • PSYCH 280: Research Methods I
    • PSYCH 281: Research Methods II
    • PSYC 284: Research Methods in Psychology
    • PSYC 340: Cognitive Psychology (with Laboratory)
    • PSYC 342: Cognitive Psychology
    • PSYC 343: Cognitive Neuroscience with Laboratory
    • STAT 445: Mathematical Statistics
    • STAT 450: Bayesian Statistics

Additional Stipulations:

  1. No more than one of ANTH 207 and BIOL 280 may count toward the minor.
  2. The minor requires a total of six distinct courses. Thus, courses that are listed twice above (such as STAT 450) may count toward one, but not both requirements.
  3. No more than three courses, counting toward any one major or other minor, may be counted toward the minor.
  4. Students who complete the Statistics track of the Mathematics major may not also minor in statistics and data science.

Loading...