The Carleton Department of Mathematics and Statistics offers a minor in Statistics and Data Science (SDS). Statistics and data science both equip students with skills to become informed citizens in an increasingly data-centric world. With vast amounts of data generated across disciplines and industries each day, the analysis and interpretation of these data have become essential. The statistics and data science minor will equip students with skills to think critically with and about data, engage in data-driven problem solving, foster creative thinking, and hone data-driven communication. Questions and petitions to add the minor should be directed to Katie St. Clair, SDS minor coordinator.

Who can earn an SDS minor?

The SDS minor is designed to complement many disciplines, embracing the inherent interdisciplinary nature of the fields of statistics and data science. To that end, there are many pathways to complete the SDS minor which makes it accessible to students majoring in many different disciplines, not solely majors within STEM departments. 

Note that there are special restrictions on Math and CS major elective choices (see the minor requirements). Statistics majors cannot earn this minor.

Basic structure of the SDS minor

Every SDS minor will complete foundational courses in statistics and computation, tailoring their experience toward the domain areas of their choice through electives. All minors will take courses from a minimum of three departments, an intentional feature of the SDS minor to embrace the inherently interdisciplinary nature of statistics and data science. 

Limits of an SDS minor

The SDS minor alone is not meant to equip students with the skills necessary to succeed in all highly technical careers in areas like data science, statistical consulting, and data analytics.  This minor should supplement a student’s major or other work or educational experiences, and enhance their ability to address data-driven problems that are common across fields of study and in our daily lives. 

Statistics or Data Science?

Statistics is a discipline that develops methodology to help give meaning to data by understanding randomness in data and quantifying the uncertainty of any data-driven conclusion. Statisticians are often involved in the design of studies or experiments, data analysis and communication of results to a broad audience, including limitations of their findings. Data Science is an interdisciplinary field that develops domain-specific processes for the full “data cycle”, including data collection, wrangling, analysis and communication. Professional data scientists need strong foundations in computation, statistics, and mathematics.

Can I count a course not on the approved list as an elective?

You can petition the SDS minor coordinator to request that a course count as a minor elective if it is not currently on the approved list of courses. SDS minor elective should satisfy at least one of the following criteria:

  1. The course will teach statistical, mathematical, or computational methods relevant to the acquisition, manipulation, management, or analysis of data.
  2. The course will show how statistical, mathematical, or computational ideas are used to analyze data in a field outside of MAST/CS. 
  3. The course will have a significant focus on ethical or philosophical aspects of decision-making or modeling uncertain behavior.

Current SDS minors should fill out submit a petition to count a non-approved course as an elective. 

Requirements for the Statistics and Data Science Minor

The Statistics and Data Science minor requires 42 credits. Courses must be taken from the approved list of Carleton courses and must satisfy the following requirements:

A. STAT requirement: (18 credits)

A student may choose to replace STAT 120 with any STAT course from the list of approved elective courses.

B. CS Requirement: (6 credits)

One computer science course (6 credits) taken at Carleton numbered CS 111 or higher.

C. Electives: (18 credits)

Three additional 6 credit courses taken at Carleton from the approved list of courses shown below. At least one of these courses must be taken outside the departments of Mathematics and Statistics and Computer Science. At least two of these courses must be 200-level or above.

Courses from the Mathematics and Statistics Department:

  • MATH 240: Probability
  • MATH 271: Optimization
  • STAT 250: Introduction to Statistical Inference
  • STAT 260: Introduction to Sampling Techniques · not offered in 2024-25
  • STAT 270: Statistical Learning
  • STAT 310: Spatial Statistics · not offered in 2024-25
  • STAT 320: Time Series Analysis
  • STAT 330: Advanced Statistical Modeling
  • STAT 340: Bayesian Statistics · not offered in 2024-25

Courses from the Computer Science Department:

  • CS 252: Algorithms
  • CS 257: Software Design
  • CS 314: Data Visualization
  • CS 320: Machine Learning
  • CS 321: Making Decisions with Artificial Intelligence
  • CS 322: Natural Language Processing
  • CS 334: Database Systems · not offered in 2024-25
  • CS 344: Human-Computer Interaction
  • CS 348: Parallel and Distributed Computing
  • CS 352: Advanced Algorithms · not offered in 2024-25
  • CS 362: Computational Biology · not offered in 2024-25

Courses from other departments:

  • ARCN 246: Archaeological Methods & Lab
  • BIOL 224: Landscape Ecology · not offered in 2024-25
  • BIOL 321: Ecosystem Ecology · not offered in 2024-25
  • BIOL 338: Genomics and Bioinformatics
  • BIOL 352: Population Ecology
  • CHEM 348: Introduction to Computational Chemistry
  • DGAH 210: Spatial Humanities · not offered in 2024-25
  • ECON 241: Growth and Development · not offered in 2024-25
  • ECON 285: Computational Economics
  • ECON 329: Econometrics
  • ENTS 120: Introduction to Geospatial Analysis & Lab
  • ENTS 254: Topics in Landscape Ecology · not offered in 2024-25
  • GEOL 135: Introduction to Climate Science & Lab · not offered in 2024-25
  • GEOL 340: Hydrogeology: Groundwater & Lab · not offered in 2024-25
  • HIST 231: Mapping the World Before Mercator
  • HIST 338: Digital History, Public Heritage & Deep Mapping · not offered in 2024-25
  • LING 318: Laboratory Phonology · not offered in 2024-25
  • MUSC 204: Theory II: Musical Structures
  • MUSC 227: Perception and Cognition of Music
  • MUSC 228: Perception and Cognition of Music Lab
  • PHIL 213: Ethics
  • PHYS 234: Computer Simulations in Complex Physical Systems
  • POSC 230: Methods of Political Research
  • PSYC 200: Measurement and Data Analysis in Psychology
  • RELG 121: Introduction to Christianity · not offered in 2024-25
  • RELG 155: Hinduism: An Introduction
  • RELG 274: Religion and Biomedical Ethics · not offered in 2024-25
  • SOAN 240: Methods of Social Research

The presence of a course on this list does not guarantee that it will be offered while you are completing your minor. Please check each department’s website for course descriptions and to determine when the course will be offered. A minor may petition for a course not on the approved list to count towards the required electives. See the minor website for more information about this process.

For computer science majors: A maximum of one elective can be a CS course.

For mathematics majors: A maximum of one elective can be a MATH course.

For majors outside computer science and mathematics: At most three courses (18 credits) may overlap with major requirements.

Statistics majors cannot earn this minor.