Graduate Aptitude Test in Engineering — Statistics 2027
IIT Madras (organising institute for GATE 2027) · Online (CBT) · Annual (February)
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GATE ST 2027 — Quick Answer
Graduate Aptitude Test in Engineering — Statistics (GATE ST) 2027 is conducted by IIT Madras (organising institute for GATE 2027) in online (cbt) mode. The next GATE ST exam is scheduled for 6, 7, 13, 14, 20 & 21 Feb 2027, with registration 2 Sep - 5 Oct 2026 (late fee until 12 Oct 2026). The paper has 65 questions for 100 marks in 180 minutes (Probability, Stochastic Processes, Statistical Inference, Regression Analysis, Multivariate Analysis, Design of Experiments, General Aptitude), with +1/-0.33 (1m); +2/-0.66 (2m); +1/+2/0 (nat). In 2026, the qualifying cutoff for the top category was 30.4. HenceProve offers free GATE ST mock tests, previous year papers, syllabus and cutoff analysis on this page.
Facts on this page last reviewed October 2026 against the sources cited below.
GATE ST Next Exam Date & Registration
| Next Exam Date | 6, 7, 13, 14, 20 & 21 Feb 2027 |
| Registration Window | 2 Sep - 5 Oct 2026 (late fee until 12 Oct 2026) |
| Conducting Body | IIT Madras (organising institute for GATE 2027) |
Exam Pattern
| Subject | Questions | Marks |
|---|---|---|
| Probability | 9 | 14 |
| Stochastic Processes | 9 | 14 |
| Statistical Inference | 9 | 14 |
| Regression Analysis | 9 | 14 |
| Multivariate Analysis | 9 | 14 |
| Design of Experiments | 9 | 14 |
| General Aptitude | 9 | 14 |
| Total | 65 | 100 |
Syllabus Highlights
2026 Cutoff Snapshot
| Category | Marks | Rank |
|---|---|---|
| General | 30.4 | — |
| OBC-NCL/EWS | 27.3 | — |
| SC/ST/PwD | 20.2 | — |
Table of Contents
About Graduate Aptitude Test in Engineering — Statistics (GATE ST) 2027
The Graduate Aptitude Test in Engineering — Statistics (GATE ST) is one of the most competitive entrance exams, conducted by the IIT Madras (organising institute for GATE 2027). Preparing for the GATE ST requires systematic practice, conceptual clarity, and regular self-evaluation. Our platform offers dynamic mock tests, previous years' resolved papers, and AI-enabled analysis to help you secure a top rank.
Frequently Asked Questions
What careers does GATE ST open?
GATE ST qualifies you for MTech in Statistics and Data Science at IITs, researcher positions at ISI (Indian Statistical Institute), CSIR, RBI, and data science roles at central government organisations and PSUs.
Is GATE ST the same as ISI entrance?
No, they are different exams. GATE ST qualifies you for IIT/NIT MTech admission and PSU statistical positions. ISI entrance exam is for MStat and MTech (CS) programmes at ISI Kolkata, Delhi, and Bangalore — generally harder.
What is GATE ST 2027 expected cutoff?
GATE ST qualifying cutoff for General category is typically 25-35 out of 100. It is a relatively newer GATE paper with fewer aspirants — around 8,000-10,000 per year — making ranks more accessible.
What is the scope of GATE ST for data science?
GATE ST is valuable for data scientist roles in government organisations (NSSO, RBI, NABARD). For private sector data science, IIT MTech through GATE ST provides industry-relevant training through project work and placements.
Which IITs offer MTech in Statistics through GATE ST?
IIT Bombay, IIT Kanpur, IIT Kharagpur, and IIT Delhi offer MTech/MS in Statistics, Applied Statistics, or related programmes. These are excellent programmes for quantitative finance, actuarial science, and research careers.
What is the GATE ST qualifying cutoff?
General category qualifying marks: 30.4 (2026), 30.2 (2025) and 26.6 (2024) — very consistent. RBI/NSSO-style recruitment and IIT MTech (Statistics/Data Science) shortlists typically need 50+ raw marks.
How should I start preparing for this GATE paper?
Begin with the official syllabus — GATE questions rarely go outside it. Then work subject-wise with previous year questions (10+ years), and finish with 8-10 full-length CBT mocks. Remember: This paper has no separate Engineering Mathematics section — General Aptitude is 15 marks and the core subject carries the remaining 85.
How to Prepare for GATE ST
Probability Theory (Distributions, Limit Theorems, Generating Functions) is the foundation — start here before other topics
Statistical Inference (Estimation, Hypothesis Testing, Confidence Intervals) carries the highest weightage — solve Casella & Berger exercises
Stochastic Processes (Markov Chains, Poisson Process) is increasingly important in the data science era — master it
Linear Regression and Design of Experiments are relatively formula-based — create a cheat sheet and practice numerical problems
Practise distribution identification drills — recognising the underlying distribution is half the answer in GATE ST
Work through Casella-Berger exercises for inference and Mukhopadhyay for probability; past ST papers map to them closely