Compare two majors
Pick any two majors to see courses, skills, and typical career roles side by side. Useful if you're weighing two options that sound similar, like Computer Science vs. Data Science, or Biology vs. Biochemistry.
Physical Sciences & Math
Statistics & Data Analytics
Making sense of data and uncertainty using rigorous methods.
Typical courses
- ✓Probability Theory
- ✓Statistical Inference
- ✓Regression Analysis
- ✓Statistical Computing (R/Python)
- ✓Experimental Design
- ✓Applied Data Analysis
Skills you'll build
Statistical modeling and inferenceProgramming for data analysisExperimental designInterpreting and communicating uncertaintyData visualizationCritical evaluation of studies and claimsWorking with real, messy datasets
Good fit if you...
- ★Enjoys math applied to real, messy data
- ★Curious about evidence, uncertainty, and how conclusions are drawn
- ★Comfortable with both theory and hands-on computing
- ★Interested in research, business analytics, or data-driven fields generally
Roles this could lead to
Computer Science & Technology
Data Science
Turning raw data into insight using statistics and code.
Typical courses
- ✓Intro to Programming (Python/R)
- ✓Probability & Statistics
- ✓Data Structures & Algorithms
- ✓Databases & SQL
- ✓Machine Learning Fundamentals
- ✓Data Visualization
Skills you'll build
Statistical analysis and inferenceProgramming for data manipulation (Python/R, SQL)Building and evaluating predictive modelsData visualization and storytellingIdentifying bias and limitations in dataWorking with large, messy, real-world datasetsTranslating technical findings for non-technical audiences
Good fit if you...
- ★Enjoys both math and coding
- ★Curious about finding patterns in messy information
- ★Comfortable being wrong and revising a hypothesis
- ★Likes explaining findings clearly to others
Roles this could lead to
This comparison covers what each field of study typically includes. It's not a ranking, and it isn't a guarantee of course availability or outcomes at any specific school. See our disclaimer.