Major decision guide
Data Science vs Statistics
Statistics is the older discipline and concentrates on the theory of inference — why a method works and when it fails. Data science spreads its credits more widely, adding programming, data engineering, and machine learning alongside statistical training. Both lead to data scientist and statistician roles in the federal crosswalk.
How each major is officially classified
Both definitions below are the official U.S. Department of Education (NCES) CIP 2020 descriptions — not CampusPin summaries.
CIP 30.7001
Data Science
Official title: Data Science, General · Family: multi/interdisciplinary studies
A program that focuses on the analysis of large scale data sources from the interdisciplinary perspectives of applied statistics, computer science, data storage, data representation, data modeling, mathematics, and statistics. Includes instruction in computer algorithms, computer programming, data management, data mining, information policy, information retrieval, mathematical modeling, quantitative analysis, statistics, trend spotting, and visual analytics.
CIP 27.0501
Statistics
Official title: Statistics, General · Family: mathematics and statistics
A general program that focuses on the relationships between groups of measurements, and similarities and differences, using probability theory and techniques derived from it. Includes instruction in the principles in probability theory, binomial distribution, regression analysis, standard deviation, stochastic processes, Monte Carlo method, Bayesian statistics, non-parametric statistics, sampling theory, and statistical techniques.
What you actually study
Data Science
- Statistics, probability, and statistical modeling
- Linear algebra and calculus for ML foundations
- Programming in Python and R
- Machine learning (supervised, unsupervised, deep learning intro)
- Data engineering and SQL
- Data visualization (matplotlib, ggplot2, Tableau)
- Experimental design and A/B testing
Statistics
- Probability theory and random variables
- Statistical inference: estimation, hypothesis testing, and confidence intervals
- Linear and logistic regression and generalized linear models
- Experimental design and analysis of variance (ANOVA)
- Sampling methods and survey design
- Bayesian methods and computational statistics
- Statistical programming in R, Python, and SAS
Where each major leads
The federal CIP–SOC crosswalk maps each academic program to the occupations it is designed to feed. Comparing the two lists shows where Data Science and Statistics converge and where they part. Every wage below is the BLS 2024 national median for that occupation — not an outcome for the major, and not a starting salary.
Mapped to both (3)
Occupations the federal crosswalk associates with both programs.
$161,180 annual median (2024)
Typically enters with: Bachelor's degree. Employment is projected to grow 3.7% 2024–2034.
$103,300 annual median (2024)
Typically enters with: Master's degree. Employment is projected to grow 8.5% 2024–2034.
$112,590 annual median (2024)
Typically enters with: Bachelor's degree. Employment is projected to grow 33.5% 2024–2034.
Mapped to Data Science only (5)
The crosswalk associates these with Data Science but not with Statistics. Graduates of either major are still hired into many of them.
Computer and Information Systems Managers
$171,200 annual median (2024)
Typically enters with: Bachelor's degree. Employment is projected to grow 15.2% 2024–2034.
Computer and Information Research Scientists
$140,910 annual median (2024)
Typically enters with: Master's degree. Employment is projected to grow 19.7% 2024–2034.
$135,980 annual median (2024)
Typically enters with: Bachelor's degree. Employment is projected to grow 8.7% 2024–2034.
$133,080 annual median (2024)
Typically enters with: Bachelor's degree. Employment is projected to grow 15.8% 2024–2034.
Postsecondary Teachers, All Other
$78,490 annual median (2024)
Typically enters with: Doctoral or professional degree. Employment is projected to grow 1.8% 2024–2034.
Mapped to Statistics only (3)
The crosswalk associates these with Statistics but not with Data Science. Graduates of either major are still hired into many of them.
$125,770 annual median (2024)
Typically enters with: Bachelor's degree. Employment is projected to grow 21.8% 2024–2034.
$63,380 annual median (2024)
Typically enters with: Master's degree. Employment is projected to decline 5.2% 2024–2034.
Mathematical Science Teachers, Postsecondary
$79,350 annual median (2024)
Typically enters with: Doctoral or professional degree. Employment is projected to grow 2.3% 2024–2034.
A major does not restrict you to these occupations, and plenty of graduates work outside them. The mapping describes what each program is built to prepare you for.
Which one tends to suit which student
This part is CampusPin’s judgement, not a measurement. Neither major is better; they suit different temperaments.
Data Science may fit if…
You want to work end to end: pull the data, build the pipeline, fit the model, ship the dashboard. You would rather cover more of that chain than go as deep into inference theory.
Statistics may fit if…
You want to understand the mathematics well enough to know when a standard method is the wrong one — and you are interested in fields like actuarial work or survey research where that rigor is the job.
Commonly misunderstood
Statistics maps to actuarial and survey-research occupations that data science does not, while data science maps to software and systems roles statistics does not. Neither is a subset of the other.
What to ask each department
Curricula vary far more between institutions than between these two majors. These questions surface the differences that actually matter for this choice.
- 1How much mathematical statistics (probability theory, mathematical inference) does each program require?
- 2Does the statistics department offer a computing sequence, or would I need to add programming courses myself?
- 3Which program has stronger consulting or practicum options with real clients?
- 4If I might pursue a graduate degree in statistics or biostatistics, which undergraduate path do those programs prefer?
How this comparison was built
The occupation lists come from the official NCES CIP 2020 → SOC 2018 crosswalk, which maps each academic program to the occupations it prepares students for. CampusPin intersects the two programs’ lists to show the shared and distinct destinations; the grouping is arithmetic on a federal dataset, not an editorial ranking.
Wages, projected employment change, and typical entry-level education come from the U.S. Bureau of Labor Statistics and are attached to the occupation, not to the major. A median is the midpoint for everyone in that occupation nationally, including people with decades of experience, so it is not a starting salary and not a promise.
The “which one tends to suit which student” and “what to ask” sections are editorial judgement, labelled as such. CampusPin does not rank majors and takes no position on which is worth more.
Frequently asked questions
- What is the difference between a Data Science and a Statistics major?
- Statistics is the older discipline and concentrates on the theory of inference — why a method works and when it fails. Data science spreads its credits more widely, adding programming, data engineering, and machine learning alongside statistical training. Both lead to data scientist and statistician roles in the federal crosswalk.
- Do Data Science and Statistics lead to the same jobs?
- Partly. The federal CIP–SOC crosswalk maps both programs to 3 of the same occupations — including Natural Sciences Managers, Statisticians, Data Scientists. It also maps 5 occupations to Data Science that it does not map to Statistics, and 3 to Statistics that it does not map to Data Science. A degree is not a restriction — graduates work outside these lists routinely — but the mapping shows where each program is designed to lead.
- Which pays more, Data Science or Statistics?
- CampusPin does not publish a "higher-paying major" answer, because the data does not support one. BLS reports median wages by OCCUPATION, not by college major, and both of these majors lead to a range of occupations that overlap. The per-occupation medians on this page are the honest version of that question: compare the specific roles you are actually interested in, and remember that pay varies widely by employer, region, and experience.
- Is there anything commonly misunderstood about choosing between Data Science and Statistics?
- Statistics maps to actuarial and survey-research occupations that data science does not, while data science maps to software and systems roles statistics does not. Neither is a subset of the other.
Read the full major guides
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Data sources & methodology
Academic classifications, occupation mappings, and wage figures for Data Science and Statistics come from federal datasets committed to this site.
Sources used across this page
Not every source informs every figure. Each data point draws on the source appropriate to it see the relevant section and the data dictionary for field-level provenance.
NCES Classification of Instructional Programs (CIP 2020)
Official academic program taxonomy: the code, title, and definition shown for each major.
NCES CIP 2020 → SOC 2018 Crosswalk
The federal mapping from academic programs to occupations. Determines which occupations each major is shown as leading to.
U.S. Bureau of Labor Statistics, Occupational Outlook Handbook
Median annual wage, projected employment change, and typical entry-level education for every occupation named.
IPEDS / NCES College Navigator
Federal enrollment, admissions, tuition, retention, and program data. Released annually with a 1–2 year lag.
Where a value is unavailable it is shown as unavailable, never as 0, free, or a negative judgment. Always confirm final details with the institution before applying.
Suggested citation
CampusPin. Data Science vs Statistics: How to Choose a Major. Retrieved from https://campuspin.com/compare-majors/data-science-vs-statistics