Statistics is one of the fastest-growing undergraduate majors in the United States, driven by the expansion of data-intensive industries across technology, finance, healthcare, government, and the sciences. A statistics degree trains students in probability theory, statistical inference, regression modeling, data analysis, and the computational tools to apply these methods at scale. Graduates are among the most versatile and consistently in-demand professionals in the modern economy. Statisticians, data scientists, quantitative analysts, biostatisticians, actuaries, and applied researchers all draw directly on undergraduate statistics training.
Despite that growth, statistics remains a small academic field in absolute degree terms. Roughly 4,400 statistics bachelor’s degrees are awarded annually in the United States, a small fraction of the volume in mathematics and a far smaller fraction of the volume in computer science. The universe of programs in this ranking includes 133 institutions that awarded at least 10 statistics degrees over the 2022–2024 period, spanning a range from large flagship universities with more than 300 annual statistics graduates to small liberal arts colleges with 15 to 20 per year.
College Transitions has developed a new data-driven ranking of these undergraduate statistics programs. The ranking uses the same five-component methodology applied across the full College Transitions program ranking series, with one field-specific adaptation: the Earnings & ROI component applies the Tier 2 formula for all programs.
How We Built the Ranking
The approach evaluates all 133 institutions across five components.
| Component | Weight | Data Source / Notes |
| Major Emphasis | 12% | IPEDS Degree Completions (CIP 27.05 + 27.06) |
| Program Scale | 13% | IPEDS Degree Completions (log) |
| Academic Rating | 30% | IPEDS / Common Data Set |
| Earnings & ROI (Tier 2) | 25% | Inst. earnings 55% + ROI 20yr 22.5% + ROI 40yr 22.5%. Field earnings excluded: 23.8% coverage, below the 50% Tier 1 threshold |
| PhD Productivity | 20% | NSF Survey of Earned Doctorates: “Statistics” field only |
Why Tier 2 for statistics? The College Scorecard Field of Study file contains statistics-specific earnings for only 40 institutions in the full universe, a coverage rate of 23.8 percent, well below the 50 percent threshold that triggers Tier 1 treatment. That low coverage reflects two structural features of the statistics major. First, many statistics programs are small enough that their graduating cohorts fall below the Scorecard’s disclosure threshold of roughly 30 students per cohort. Second, a substantial share of statistics graduates at elite programs proceed directly to doctoral study, leaving a direct-employment cohort too small for disclosure. Under the Tier 2 formula, the Earnings & ROI component reflects institutional 10-year earnings (55 percent sub-weight) and Georgetown CEW return-on-investment figures (22.5 percent each for 20-year and 40-year ROI), signals available for virtually all programs that capture the economic value of the institution’s degrees.
PhD Productivity (20 percent) uses the NSF Survey of Earned Doctorates field “Statistics” exclusively, rather than the broader “Mathematics and statistics, other” field used in the separate Mathematics ranking. This ensures the PhD signal reflects the doctoral pipeline in statistics specifically rather than a combined mathematical sciences measure.
The Top 25
The top 25 programs are shown below. Statistics’ top tier is dominated by elite private research universities, a pattern that differs from the engineering rankings in this series, where large public programs feature more prominently. This reflects the field’s structure: at most large public universities, statistics is housed in a mathematics department or offered as a concentration rather than a standalone major, and degree volumes concentrate at a handful of institutions with dedicated statistics departments.
| Rank | Institution | State | Type | Score |
| 1 | Carnegie Mellon University | PA | Private | 94.1 |
| 2 | Harvard University | MA | Private | 93.7 |
| 3 | Duke University | NC | Private | 91.3 |
| 4 | Yale University | CT | Private | 88.8 |
| 5 | University of Pennsylvania | PA | Private | 88.4 |
| 6 | University of Chicago | IL | Private | 87.9 |
| 7 | Rice University | TX | Private | 87.5 |
| 8 | Dartmouth College | NH | Private | 86.0 |
| 9 | Columbia University | NY | Private | 85.1 |
| 10 | University of Virginia | VA | Public | 84.5 |
| 11 | University of California-Los Angeles | CA | Public | 83.3 |
| 12 | Northwestern University | IL | Private | 82.0 |
| 13 | University of Michigan-Ann Arbor | MI | Public | 81.6 |
| 14 | University of California-Berkeley | CA | Public | 81.0 |
| 15 | Cornell University | NY | Private | 80.4 |
| 16 | University of Illinois Urbana-Champaign | IL | Public | 79.3 |
| 17 | University of California-Santa Barbara | CA | Public | 77.3 |
| 18 | University of California-Davis | CA | Public | 76.0 |
| 19 | University of Rochester | NY | Private | 75.8 |
| 20 | Williams College | MA | Liberal Arts | 75.2 |
| 21 | Wake Forest University | NC | Private | 74.2 |
| 22 | University of California-San Diego | CA | Public | 73.9 |
| 23 | University of Florida | FL | Public | 73.6 |
| 24 | Purdue University | IN | Public | 73.2 |
| 25 | New York University | NY | Private | 73.1 |
Table 1. Top 25 Undergraduate Statistics Programs, 2026 College Transitions Ranking. All programs use Tier 2 C4 (field earnings unavailable for roughly 76 percent of the universe).
Carnegie Mellon University (#1, 94.1) leads the statistics ranking with a perfect 100.0 on Major Emphasis, the only program in the universe to reach that score, reflecting that statistics accounts for a higher fraction of CMU’s total degrees than at any other institution in the dataset. CMU awarded 349 statistics degrees over three years, placing it at the 96th percentile on Program Scale. Its institutional earnings of $114,862, the highest in the statistics universe, reflect CMU’s pipeline into finance, technology, and AI, and produce the top Earnings & ROI score of 99.7. CMU’s statistics department, housed within its School of Computer Science, is one of the world’s foremost centers for computational statistics, probabilistic machine learning, and statistical theory. For students whose goal is work at the intersection of statistics, machine learning, and technology, CMU is the clear top choice.
Harvard University (#2, 93.7) posts a strong combination of Academic Rating (92.3, second-highest in the dataset), Earnings & ROI (96.7, reflecting institutional earnings of $101,817), and PhD Productivity (97.0, with 22 statistics doctoral recipients at a per-capita rate of 3.1, strong for an institution of Harvard’s size). Harvard’s statistics department, one of the oldest and most distinguished in the country, has deep strengths in Bayesian methods, causal inference, and statistical theory, and its graduates enter doctoral programs, consulting, finance, and technology at high rates.
Duke University (#3, 91.3) achieves the highest Academic Rating in the statistics universe (93.2), reflecting Duke’s institutional quality indicators. Its PhD Productivity score (91.4) reflects 14 statistics doctoral recipients from a program of modest scale (128 degrees over three years), yielding a strong per-capita rate. Duke’s statistics department has particular strengths in Bayesian statistics, biostatistics, and spatial statistics, and its location in the Research Triangle places graduates within direct recruiting range of SAS Institute, biostatistics consulting firms, and the pharmaceutical companies that make North Carolina one of the most active biostatistics labor markets in the country.
Yale (#4, 88.8) and University of Pennsylvania (#5, 88.4) round out the top five. Both benefit from their location within elite urban research environments, Yale in New Haven and Penn in Philadelphia and within commuting range of Wall Street, and from institutional earnings that rank in the 95th and 99th percentiles of the universe respectively. Penn’s Wharton School context gives its statistics graduates direct access to finance and consulting recruiting pipelines that few other statistics programs can match.
University of Chicago (#6, 87.9) leads all programs on PhD Productivity with a score of 99.6, reflecting 36 statistics doctoral recipients over the decade at a per-capita rate of 4.8 per 1,000 undergraduates, the highest rate among major research universities in the dataset. Chicago’s statistics department is one of the most research-intensive undergraduate environments in the discipline, consistent with the university’s broader culture of rigorous quantitative inquiry. For students planning doctoral study in statistics, Chicago’s combination of research depth, faculty access, and per-capita PhD output is the strongest among large programs.
What Separates the Best Programs?
CMU: When Statistics Is the Institution
Carnegie Mellon’s #1 ranking is explicable from a single data point. It awards more statistics degrees as a share of total institutional degrees than any other program in the country, a perfect Major Emphasis score of 100. CMU’s statistics program is not a department within a comprehensive university; it is central to the institution’s identity as a technical research university where data science, machine learning, and statistical computation define the academic culture. The consequence is not just high enrollment in statistics courses but a peer environment, faculty culture, and industry recruiting infrastructure oriented entirely toward quantitative data work. The premium CMU graduates command, reflected in the highest institutional earnings in the statistics universe at $114,862, follows directly from that concentration.
The UC System: Scale Without the Prestige Premium
UC Santa Barbara (#17, 77.3) and UC Davis (#18, 76.0) lead the UC system statistics programs by degree volume and are instructive cases for counselors. UCSB leads all institutions on Program Scale (a perfect 100.0, reflecting 926 statistics degrees over three years, the largest statistics program in the country by volume). UC Davis is second at 510 degrees. Both score in the 65th to 70th percentile on Academic Rating and in the 77th to 85th percentile on Earnings & ROI, reflecting the UC system’s combination of solid academic quality and strong California labor market outcomes for statistics graduates. UIUC (#16, 79.3) is the ranking’s largest program outside the UC system (830 degrees over three years), with a 97.7 Major Emphasis score and strong PhD Productivity (84.0, reflecting 16 statistics doctoral recipients). For students seeking large, well-resourced statistics programs with strong industry recruiting at in-state tuition, UIUC, UCSB, UC Davis, and UCLA are the primary options.
Liberal Arts Colleges: Williams and Carleton
Williams College (#20, 75.2) and Carleton College (#27, 72.6) are the ranking’s two standout liberal arts colleges, and their presence in the top 30 reflects a real academic advantage: per-capita PhD productivity that rivals much larger research universities. Williams produced 7 statistics doctoral recipients over the decade at a per-capita rate of 3.3 per 1,000 undergraduates (fifth-highest in the full dataset); Carleton produced 8 at a rate of 3.9 per 1,000 (second-highest). Both score above the 80th percentile on Academic Rating, consistent with the academic environments typical of highly selective liberal arts colleges. For students who want a mathematically intensive statistics education within a small, discussion-based learning environment rather than a large research university, and who plan to attend graduate school, Williams and Carleton are among the strongest options in the country.
Cornell, Columbia, and the New York Premium
Cornell (#15, 80.4) and Columbia (#9, 85.1) both benefit from the New York metropolitan labor market for statistics and data science graduates, with institutional earnings of $104,043 and $102,491 respectively, among the highest in the universe. Cornell’s statistics program, housed within the College of Arts and Sciences and closely linked to its Operations Research and Industrial Engineering department, has particular strengths in applied statistics, machine learning theory, and interdisciplinary applications. Columbia’s program benefits from proximity to Wall Street quantitative finance recruiting, the major financial data companies, and Columbia’s own connections to the biostatistics and epidemiology research environments at its medical school and the Mailman School of Public Health.
Patterns, Themes, and What They Mean for Your Students
Statistics is one of the most employment-secure quantitative majors. The Bureau of Labor Statistics consistently projects statistician and data scientist employment growth well above the national average. Unlike some technical fields where employment concentrates in a single industry, statistics graduates are absorbed across finance, technology, healthcare, government, consulting, pharmaceutical research, sports analytics, and environmental science. That breadth means geographic flexibility matters somewhat less for statistics graduates than for, say, electrical engineers, though the Bay Area, New York, and Boston still carry a measurable premium in the earnings data.
The distinction between a statistics major and a data science major is increasingly important for counselors to understand. Many institutions have launched standalone data science programs in recent years, typically housed under CIP 30.70 or a similar code. Those programs are not captured in this ranking, which focuses exclusively on CIP 27.05 and 27.06. Students interested in applied data work should compare statistics programs carefully against any data science program at the same institution. The curricula differ in their emphasis on statistical theory versus computational implementation, and both have real value depending on the student’s career goals. Students planning doctoral study in statistics or biostatistics should generally prefer a rigorous statistics major; students planning direct entry into data science roles at technology companies may find data science programs equally or more useful.
Biostatistics is a fast-growing and highly compensated specialization that is invisible in this ranking. Many of the programs here, particularly Duke, Harvard, Columbia, Johns Hopkins, Michigan, Minnesota, and UNC Chapel Hill, have strong connections to biostatistics research and doctoral programs through affiliated schools of public health or medical schools. Students interested in applying statistics to clinical research, epidemiology, or pharmaceutical development should ask specifically about biostatistics coursework, faculty, and advising connections at any program under consideration. The NSF PhD data used here aggregates statistics and biostatistics doctoral production under “Statistics,” so programs with active biostatistics pipelines benefit in the PhD Productivity score, but undergraduate training in biostatistics is not captured by degree completion data alone.
Graduate school in statistics is available from a wide range of institutions, not just the elite top ten. Unlike some fields where doctoral admissions are effectively restricted to graduates of a handful of programs, statistics PhD programs regularly admit strong students from mid-tier public universities, liberal arts colleges, and programs outside the conventional prestige tier. The per-capita PhD production rates of Williams, Carleton, Rice, and Harvard all exceed those of large flagship state universities, but a strong student from Iowa State, Ohio State, or Purdue with a high GPA and research experience is a real candidate for top doctoral programs. Counselors should help students understand that the path to doctoral study in statistics is less prestige-gated than in some other fields.
Statistics sits at the intersection of mathematics, computing, and scientific reasoning. The programs that lead this ranking have built the academic environments, research cultures, and industry connections that best prepare students to work in that intersection. Students who choose carefully, matching their career goals, graduate school ambitions, and institutional preferences to programs where statistics is a real departmental commitment, will find a field with strong career prospects and a landscape of programs broader and more accessible than conventional rankings suggest.
