A quietly elite quantitative major — strong ROI, modest debt, unusually broad exit optionality
Statistics is one of the cleaner ROI stories in the catalog. Census PSEO puts the 10-year median at $99,842 with the 75th percentile at $138,511, and College Scorecard shows bachelor's graduates earning $58,491 in year 1 against a $19,743 institution-level debt average — a 0.338 debt-to-income ratio well inside the 0.40 healthy threshold. Statisticians (SOC 15-2041) are the canonical destination at +8.5% projected growth and $103,300 median wage, but the advanced-practice tier is where the field's ceiling lives: data scientists (+33.5%, $112,590) and actuaries (+21.8%, $125,770) both hire quantitative undergraduates heavily. The honest caveat: the credential mix is graduate-heavy. Master's completions (3,982) nearly match bachelor's (4,127), and the destination roles that require a master's (statisticians, economists) pay more than the bachelor's-only destinations. A bachelor's alone is a legitimate analyst on-ramp, but the field's headline earnings depend on stacking a master's or landing a data-science/actuarial role.
- ROI A
- Employment A
- Debt burden A
- Projected demand B+
Statistics sits in a quiet sweet spot in the quantitative-majors catalog. The ROI math is clean — Census PSEO reports a $99,842 10-year median with the 75th percentile at $138,511 — and the debt side is equally clean: bachelor's graduates earn $58,491 in year 1 against a $19,743 institution-level debt average, producing a 0.338 debt-to-income ratio squarely inside the 0.40 healthy threshold. The tension most students face isn't whether statistics is worth it. It's whether a bachelor's alone captures the headline earnings — or whether those numbers reflect a master's-heavy cohort.
The primary BLS destination is statisticians (SOC 15-2041) at +8.5% projected growth through 2034 and $103,300 median wage — roughly 2× the +4.0% all-occupations baseline. The ceiling is where statistics starts looking genuinely elite: data scientists at +33.5% growth and actuaries at +21.8% growth are both advanced-practice destinations that hire quantitative undergraduates heavily. Completions land at 9,152 total in 2024, with 4,127 bachelor's and 3,982 master's — a credential mix that's roughly 50/50 and signals an unusually graduate-prone field.
Field-level debt data is sparse (Scorecard's fieldLevelSparse flag fires at every tier), so this analysis leans on institution-level debt averages across the 532 schools producing statistics credentials. The rest of the page breaks down what the bachelor's actually pays, where the master's premium comes from, and which destination roles justify the credential math.
- ✓ Bachelor's debt-to-income ratio is 0.338 ($19,743 debt vs. $58,491 year-1 earnings) — inside the 0.40 healthy threshold.
- ✓ Census PSEO 10-year median is $99,842 with the 75th percentile clearing $138,511 — top-tier long-run earnings among quantitative undergraduate majors.
- ✓ Statisticians (SOC 15-2041) are projected to grow +8.5% through 2034 — roughly 2× the +4.0% all-occupations BLS baseline — with $103,300 median wage.
- ✓ Data scientists (+33.5%, $112,590) and actuaries (+21.8%, $125,770) are advanced-practice destinations with $114,782 weighted median wage — elite exit optionality.
- ✓ Three-year loan default rate across the 532 institutions producing statistics credentials is effectively 0.0% — no repayment distress in the data.
- ! Scorecard publishes null field-level debt at every credential tier; the $19,743 figure is an institution-level fallback across 532 producing schools.
- ! The primary occupation (statistician) requires a master's degree — bachelor's holders typically route to data-analyst or actuarial roles to clear the canonical-statistician pay band.
- ! Statisticians have only ~2,000 annual openings — the role is well-paid but narrow; most graduates land in adjacent data and analyst occupations.
Where statistics graduates actually land
Census Post-Secondary Employment Outcomes (PSEO)
Earnings by credential level
College Scorecard field-level earnings (years 1–4 post-grad, aggregated across institutions)
What it costs, what you earn, what's left over
Field-level debt is not published for statistics at any credential tier — Scorecard's fieldLevelSparse flag is true across all eight categories (undergraduate certificate through graduate certificate). The $19,743 figure used throughout this page is an institution-level median across the 532 schools producing statistics credentials; it does not separate an urban community-college associate's from a Columbia biostatistics master's, and it almost certainly understates borrowing at the graduate tiers where master's and doctoral students concentrate.
What the data can support is the bachelor's-tier ratio. Scorecard field-level year-1 earnings at the bachelor's are $58,491, producing a debt-to-income ratio of 0.338 — well inside the 0.40 healthy threshold and comparable to applied mathematics (0.34) or chemistry. By year 4, Scorecard shows bachelor's earnings at $87,624, suggesting a roughly 50% four-year earnings lift that further compresses the effective debt burden. The master's tier is even healthier: year-1 earnings of $74,216 against the same $19,743 institution-level anchor yields a 0.266 ratio — though realistic master's borrowing at private programs runs higher than the institution-level average. Long-run, Census PSEO reports a 10-year median of $99,842 — more than 5× the debt figure — and the three-year loan default rate across producing institutions is effectively 0.0%, versus the Scorecard-wide average of ~3% for four-year institutions. No repayment distress shows up in the data.
The credential paths that actually produce graduates
Scorecard field-level earnings + completions_by_program (most recent year) aggregated by credential tier
Bachelor's in Statistics (BS/BA)
A four-year quantitative program covering probability, inferential statistics, linear regression, experimental design, computational statistics (R or Python), and at least one applied elective — biostatistics, econometrics, actuarial science, or data science. Produces 4,127 graduates per year across 378 institutions. Scorecard field-level earnings show $58,491 in year 1 climbing to $87,624 at year 4.
- Completions / yr 4,213
- Year-1 earnings $63,285
- Year-4 earnings $95,197
- Median debt $19,259
- % women 38.7%
- Schools 217
The right entry point for students who want quantitative analyst roles (data analyst, biostatistician, risk analyst, junior actuary) or who plan to stack a master's in statistics, biostatistics, data science, or an MBA with a quantitative concentration.
Master's in Statistics (MS)
A one-to-two-year graduate program with deeper coursework in statistical theory, Bayesian methods, survival analysis, machine learning, and an applied concentration. Produces 3,982 graduates per year across 231 institutions — nearly matching the bachelor's volume. Scorecard year-1 earnings at the master's tier are $74,216, rising to $112,483 at year 4 — a clean $16k year-1 premium over the bachelor's cohort.
- Completions / yr 3,551
- Year-1 earnings $94,184
- Year-4 earnings $131,465
- Median debt $42,497
- % women 41.6%
- Schools 180
The practical path for students targeting canonical statistician roles (where Master's is the typical education), biostatistics/pharmaceutical work, quantitative research, or a pivot from a non-quantitative undergraduate degree. Cost-competitive public master's programs or employer-funded options produce the strongest ROI.
Doctoral (PhD) in Statistics
A four-to-six-year research degree producing statisticians for academia, industrial research labs, and methodologically heavy industry roles (Netflix, pharma, hedge funds, federal agencies). Produces 687 graduates per year across 94 institutions.
- Completions / yr 486
- Year-1 earnings —
- Year-4 earnings —
- Median debt $20,562
- % women 34.4%
- Schools 91
A defensible path for students targeting academic research careers, methodology-heavy industry positions, or federal research roles at agencies like the Census Bureau or FDA. The opportunity cost of 4–6 years is real — most industry statistician roles are reachable with a master's.
The bachelor's is a legitimate analyst on-ramp with a healthy debt-to-income profile; the master's is where the canonical statistician pay lives and where most of the field's long-run earnings concentrate. The doctoral tier is genuinely niche — pursue it only if academic research or methodology-specialist work is the actual goal.
Statistics has one of the most balanced credential distributions of any quantitative major profiled here. Bachelor's degrees account for 4,127 completions and master's degrees account for 3,982 — a near-even 45/44 split with the remaining share in doctoral (687, 7.5%) and certificates (318, 3.5%). That balance is unusual. Most undergraduate-focused fields show a bachelor's-dominant pyramid; most graduate-focused fields show an inverted pyramid. Statistics operates as both: a legitimate undergraduate major and a heavy graduate-specialization track. The associate's tier is effectively non-existent at 38 completions across 12 institutions — too thin to defend as a standalone credential.
The earnings story supports the balance. Scorecard bachelor's year-1 is $58,491 rising to $87,624 at year 4; master's year-1 is $74,216 rising to $112,483 at year 4. The year-1 master's premium is roughly $16,000 and the year-4 premium widens to $25,000 — real money, but not the dramatic multi-fold gap you'd see comparing an MS in computer science to a CS bachelor's. What the master's buys isn't a different salary band so much as access to the canonical statistician role (SOC 15-2041, $103,300 median, master's-typical) and specialty work in biostatistics, survey methodology, and actuarial research that bachelor's holders route around through analyst positions.
The gender composition is the most balanced in quantitative-majors territory: 47.2% women overall, with the master's tier at 49.6% women and the bachelor's at 47.3% — well above the ~30% women typical in computer science or mechanical engineering. The completion trend is quietly strong: 9,152 total in 2024 up from 8,571 in 2023, a 6.8% one-year increase that tracks the rising employer demand for quantitative undergraduates across finance, tech, pharma, and federal statistical agencies. The bridge-path reality: statistics bachelor's graduates routinely work 2–4 years as analysts while employer tuition support or part-time master's programs fund the graduate credential — a cleaner on-ramp than most fields offer.
Who completes these degrees
IPEDS completions_by_program, most recent year, first-major only
- 2023 9,000
- 2024 8,677
Where graduates land professionally
BLS 2024–2034 Employment Projections via CIP-to-SOC crosswalk
| SOC | Occupation | Employed '24 | Growth | Openings/yr | Median wage | Entry |
|---|---|---|---|---|---|---|
| 15-2051 | Data scientists | 246k | +33.5% | 23k | $112,590 | Bachelor's degree |
| 11-9121 | Natural sciences managers | 104k | +3.7% | 8.5k | $161,180 | Bachelor's degree |
| 25-1022 | Mathematical science teachers, postsecondary | 59k | +2.3% | 4.4k | $79,350 | Doctoral or professional degree |
| 15-2011 | Actuaries | 34k | +21.8% | 2.4k | $125,770 | Bachelor's degree |
| 15-2041 | Statisticians | 32k | +8.5% | 2.0k | $103,300 | Master's degree |
| 19-3022 | Survey researchers | 8.8k | -5.2% | 0.7k | $63,380 | Master's degree |
| 15-2021 | Mathematicians | 2.4k | -0.7% | 0.1k | $121,680 | Master's degree |
The destination map for statistics is cleanly tiered. The primary baseline is statisticians (SOC 15-2041) — 32.2k currently employed, projected to grow +8.5% through 2034 with ~2,000 annual openings and a $103,300 median wage. That growth rate is roughly 2× the +4.0% BLS all-occupations baseline, which puts statistics in the healthy-above-average band but not the explosive-growth category. The canonical statistician role is prestigious and well-paid, but narrow on openings — ~2k per year across the country. Typical education is a master's degree, which matters: bachelor's holders targeting the statistician title generally need to stack a master's or route through adjacent analyst roles first.
The advanced-practice tier is where the field's ceiling lives. Data scientists (SOC 15-2051) lead at +33.5% projected growth and a $112,590 median wage — the fastest-growing destination in the crosswalk, with 23.4k annual openings and a bachelor's as typical education. Data scientists represent an explicit career path for quantitative statistics graduates who add machine-learning and programming depth. Actuaries (SOC 15-2011) are the second advanced-practice destination at +21.8% growth, $125,770 median wage, and 2.4k annual openings — higher pay than statisticians, also bachelor's-typical, but gated by the SOA/CAS exam sequence. Together the advanced-practice tier produces a weighted $114,782 median wage and ~26k annual openings — materially more volume than the primary statistician role.
Adjacent destinations fill out the map but should be treated as related-career territory rather than headline outcomes. Financial and investment analysts (SOC 13-2051) absorb the largest share of quantitative undergraduates at 368.5k employed, +5.7% growth, $101,350 median, and 25.1k annual openings — a natural destination for statistics grads who specialize in quantitative finance. Economists (SOC 19-3011, $115,440 median) and mathematical science teachers, postsecondary (SOC 25-1022, $79,350 median, doctoral-required) are smaller, more specialized destinations. The typical education requirement for the primary occupation is a master's — realistically that means planning on either graduate school or a lateral route through data-science or actuarial roles if the goal is to clear the statistician pay band.
Where demand is growing
State workforce agencies publish their own 10-year projections for data scientists — growth varies sharply by state, and where you plan to live changes the calculus.
| VI | +100.0% | 0 openings/yr |
| Wyoming | +75.0% | 10 openings/yr |
| Tennessee | +59.2% | 250 openings/yr |
| Utah | +58.1% | 420 openings/yr |
| Texas | +53.2% | 1,690 openings/yr |
| Montana | +50.0% | 10 openings/yr |
| South Carolina | +48.0% | 150 openings/yr |
| Arizona | +48.0% | 360 openings/yr |
| California | 3,440/yr | +32.7% growth |
| Texas | 1,690/yr | +53.2% growth |
| Florida | 1,020/yr | +47.0% growth |
| Illinois | 630/yr | +29.6% growth |
| Georgia | 620/yr | +43.8% growth |
Schools producing the most graduates
Volume, not quality — completion counts across all credentials. See our rankings pages for outcome-weighted school scores.
- 486
- 455
- 375
- 368
- 326
- 273
- 240
- 165
- 164
- 150
Pursue statistics at the bachelor's level if the goal is quantitative analyst work, actuarial science, or a stacked master's in statistics, biostatistics, or data science. The math is clean: $58,491 year-1 earnings against $19,743 institution-level debt, a 0.338 debt-to-income ratio, a 0.0% three-year default rate, and a PSEO 10-year median of $99,842 that places the field alongside applied mathematics and near computer science on long-run earnings. The destination map is unusually broad — data scientists (+33.5%, $112,590), actuaries (+21.8%, $125,770), financial analysts ($101,350), biostatisticians, and data analysts all hire statistics bachelor's graduates heavily. A statistics bachelor's keeps more career doors open than most quantitative credentials, and pairs cleanly with either a graduate credential or a self-directed portfolio path.
The recommendation flips in two cases. First: if the specific goal is the canonical statistician role (SOC 15-2041), plan from day one to stack a master's — the bachelor's alone won't clear the $103,300 pay band for that title, and the thin 2,000-per-year openings mean competition at the entry level is real. Second: if you struggle with calculus through multivariable, probability theory, or mathematical proof — the statistics major doesn't offer an easy route around core mathematical rigor, and graduating with weak fundamentals produces a credential that doesn't translate to the labor market. The destination roles (data science, actuarial, biostatistics, quantitative finance) all demand comfortable fluency in statistical reasoning and at least one programming environment. If you can carry the coursework, statistics is genuinely worth it — arguably the highest-optionality quantitative undergraduate major in the catalog.
Informed inquiries
Is a statistics bachelor's worth it compared to a computer science or data science major?
Yes, but the jobs are different. CS bachelor's grads target software engineering with higher median year-1 pay ($73,000+) and a much deeper entry-level market; statistics bachelor's grads target analyst and quantitative roles — data analyst, biostatistician, risk analyst, junior actuary — with $58,491 Scorecard year-1 earnings and a heavier tilt toward roles that value statistical reasoning over raw coding throughput. The debt math is comparable ($19,743 institution-level average for statistics vs. similar ranges for CS), the default rate is effectively 0% for both, and PSEO 10-year medians are in the same neighborhood ($99,842 for statistics). Pick CS if you want to build systems and data science if you want the data-scientist job explicitly. Pick statistics if you want to do inference, experimental design, or quantitative analysis where the statistical literacy is the differentiator — and know you can reach the same data-scientist market (+33.5% growth, $112,590 median) by stacking a master's or building portfolio evidence.
Do I need a master's to actually work as a statistician?
For the BLS-canonical statistician role (SOC 15-2041, $103,300 median, +8.5% growth), yes — typical education is a master's degree. The bachelor's tier in statistics is real and pays well ($58,491 year 1, $87,624 by year 4 per Scorecard) but the jobs at that tier are data analyst, research assistant, actuarial assistant, and junior biostatistician, not statistician per se. If your target is the canonical role, the practical path is bachelor's → work 1–2 years as an analyst while applying to master's programs (ideally funded or employer-subsidized). Completions data supports this pattern: 3,982 master's graduates per year nearly match the 4,127 bachelor's graduates, meaning roughly one in two statistics bachelor's grads ends up stacking a master's within a decade — which is what the $99,842 10-year PSEO median reflects.
Should I major in statistics or go for actuarial science or biostatistics directly?
Go statistics unless you're certain about the specialty. Actuarial science and biostatistics are narrower credentials that train for specific licensure paths (actuarial exams, biostatistics research roles); statistics is the generalist version that keeps both doors open and adds data science and analyst pathways. If you do pick statistics and later want actuarial work, actuaries (SOC 15-2011) at +21.8% growth and $125,770 median are accessible with the right exam prep (SOA/CAS exam sequence) — the coursework gap is small. Biostatistics is typically a master's specialization anyway, reachable from a statistics bachelor's. The data-science destination (+33.5% growth, $112,590 median) is reachable from any of the three with the right portfolio and at least one machine-learning course. Unless you have clear actuarial or biostat intent going in, statistics is the higher-optionality bachelor's.
Why is the earnings data missing for the doctoral and associate's tiers?
College Scorecard's fieldLevelSparse flag fires for most credential tiers in statistics because small-cohort suppression rules hide statistics where counts are low enough to risk identifying individuals. At the associate's tier (38 annual completions across 12 institutions) the cohort is genuinely too small to publish. At the doctoral tier (687 completions across 94 institutions) the cohort is larger but Scorecard applies suppression to graduate credentials more aggressively, and the sample sizes per-institution stay thin. The same issue affects field-level debt — null at every tier — which is why the $19,743 figure here is an institution-level average across the 532 producing schools rather than a field-specific debt number. Treat the institution-level debt as a rough anchor, not a precise per-credential estimate, and expect actual borrowing at the master's and doctoral tiers to run higher.
Which occupations should statistics graduates actually target?
The BLS destination map is cleanly tiered. The canonical role is statistician (SOC 15-2041, 32.2k employed, +8.5% growth, $103,300 median, ~2k annual openings) — prestigious but narrow, typically a master's-required entry point. The volume tier sits in adjacent roles: financial and investment analysts (SOC 13-2051, 368.5k employed, +5.7%, $101,350 median, 25.1k openings) for quantitative finance, and the broader data-analyst pool (not a single SOC but well-populated). The growth tier is where the ceiling lives: data scientists (SOC 15-2051, +33.5%, $112,590 median) and actuaries (SOC 15-2011, +21.8%, $125,770 median) — both bachelor's-typical, both hire statistics grads heavily. The premium tier includes economists (SOC 19-3011, $115,440) and mathematicians (SOC 15-2021, $121,680), both master's-required and narrow on openings. The strategic pattern: most graduates enter as analysts; the quantitative standouts clear into data science or actuarial; the specialists target statistician or economist after a master's.
How does the debt-to-income ratio compare to other quantitative majors?
Favorably. At the bachelor's tier statistics shows a 0.338 debt-to-income ratio ($19,743 debt, $58,491 year-1 earnings) — inside the 0.40 healthy threshold. At the master's tier the ratio improves to 0.266 ($19,743 debt against $74,216 year-1 earnings), though field-level debt is sparse and master's borrowing realistically runs higher than the institution-level average. By comparison, computer science typically runs a 0.25–0.30 ratio at the bachelor's (higher year-1 earnings offset comparable debt); applied mathematics runs around 0.34 at the bachelor's. Statistics is squarely in the healthy range for quantitative undergraduate majors, and the three-year default rate of effectively 0.0% across the 532 producing institutions confirms no repayment distress in the population. The caveat: the institution-level debt number understates graduate borrowing, so plan conservatively if you're looking at a self-funded private master's program.
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