GATE ST 2026 – India’s Most Structured Coaching for Statistics Aspirants
Master the Entire Statistics Syllabus with Sourav Sir’s Scientific Teaching Approach
If your dream is IIT / IISc / PSU Statistics Jobs — your preparation must be scientific, disciplined, and syllabus-oriented.
⭐ Why GATE ST?
Career Opportunities
Statistical Officer in Govt. Departments
GATE ST opens doors to prestigious government roles as Statistical Officer, Data Analyst, and Research Analyst in various ministries and departments.
Data Scientist roles in top companies
Top companies in India and abroad value GATE ST for data science, analytics, and quant roles.
Research institutions
GATE ST qualifies you for research roles in premier institutions like ISI, IISc, and IITs.
PSU statistical divisions
PSUs like ONGC, IOCL, GAIL, and BARC recruit GATE ST candidates for statistical and data analysis roles.
Analyst and Quant-based job profiles
GATE ST is a gateway to high-paying analyst and quant roles in finance, consulting, and tech.
Higher Studies Options
IITs, IISc, ISI joint programs
GATE ST is your ticket to M.Tech/MS in Statistics, Data Science, Computational Statistics, and Applied Mathematics at IITs, IISc, and ISI.
MTech/MS in Statistics, Data Science, Computational Statistics, Applied Mathematics
Pursue advanced studies in top Indian and foreign universities with GATE ST.
PSU Jobs
IOCL, ONGC, HPCL, BARC DRIP Statistical Scientist, DRDO, NIC Scientific Officer
GATE ST is accepted for recruitment in these PSUs for statistical and data science roles.
Research & PhD Pathways
PhD in Probability & Stochastic Processes, Mathematical Statistics, Data Science & Machine Learning
GATE ST is a stepping stone to PhD programs in India and abroad.
Salary & Growth
MTech/MS graduates: ₹15–30 LPA
Graduates from top institutes command high salaries in industry and research.
PSU Packages: ₹12–20 LPA + Perks
PSU jobs offer job security, attractive salaries, and perks.
Data Scientist Roles: ₹20–40 LPA
Data science roles in top companies offer lucrative packages.
📌 About the Exam
Conducting Body
IITs conduct GATE ST every year on a rotational basis.
Eligibility
Bachelor’s degree in Statistics / Mathematics / Science / Engineering. Final-year students can apply.
Exam Frequency
Once every year (February).
Mode & Marks Distribution
- 100 Marks
- 65 Questions
- MCQ + MSQ + NAT
- 30% Mathematics + 70% Statistics
📚 Syllabus Overview
Calculus
1. Finite, countable, uncountable sets
Types of sets, mapping, bijection, cardinality.
2. Real number system as complete ordered field
Completeness property, bounds, supremum/infimum.
3. Archimedean property
4. Sequences
- Convergence
- Bounded + Monotonic sequences
- Cauchy Criterion
5. Series
- Point tests
- Convergence tests: Ratio, Root, Comparison, Alternating series
- Absolute & conditional convergence
- Power series & radius of convergence
6. Functions of one real variable
- Limits & Continuity
- Monotone functions
- Uniform continuity
- Differentiability
- Rolle’s Theorem
- Mean Value Theorems
- Taylor Theorem
- L'Hospital Rule
- Maxima & Minima
- Riemann Integration & properties
- Improper integrals
7. Functions of several variables
- Partial derivatives
- Directional derivatives
- Gradient
- Multivariable Taylor
- Total derivative
- Maxima/minima
- Saddle point
- Lagrange multipliers
- Double/triple Integrals & applications
Matrix Theory
1. Subspaces of ℝⁿ and ℝᵐ
2. Span, linear independence
3. Basis & Dimension
4. Row & Column space
5. Rank & Nullity
6. Row Reduced Echelon Form (RREF)
7. Determinant & Trace
8. Matrix inverse
9. Systems of linear equations
10. Inner products in ℝⁿ
11. Gram-Schmidt
12. Eigenvalues, eigenvectors
13. Characteristic polynomial
14. Cayley-Hamilton theorem
15. Symmetric, skew-symmetric, Hermitian, skew-Hermitian, orthogonal, unitary matrices
16. Change of basis
17. Similarity & equivalence
18. Diagonalization
19. Positive definite & semi-definite matrices
20. Quadratic forms
21. Singular Value Decomposition (SVD)
Probability
1. Axiomatic approach
2. Properties of probability
3. Conditional probability
4. Bayes’ theorem
5. Independence of events
Random Variables
- Distribution functions
- PMF, PDF, CDF
- Moments, MGF
- Quantiles
- Functions of random variables
- Inequalities: Chebyshev, Markov, Jensen
Discrete + Continuous Distributions
- Bernoulli
- Binomial
- Geometric
- Negative Binomial
- Hypergeometric
- Discrete Uniform
- Poisson
- Continuous Uniform
- Exponential
- Gamma
- Beta
- Weibull
- Normal
Joint Distributions
- Joint PDF/PMF
- Marginal & conditional distributions
- Conditional expectation
- Joint moments
- Correlation
- Joint MGF
- Independence
- Order statistics (PDF, CDF)
- Multinomial
- Bivariate normal
- Sampling distributions (Z, χ², t, F)
Modes of Convergence
- In probability
- In distribution
- Almost surely
- In r-th mean
- Relations between them
- Slutsky lemma
- Borel–Cantelli lemma
- Weak & Strong LLN
- Central Limit Theorem
- Delta method
Stochastic Processes
1. Markov chains (finite + countable states)
2. Classification of states
3. n-step transition probabilities
4. Limiting behaviour
5. Stationary distribution
6. Poisson process
7. Birth-death process
8. Pure-birth & pure-death
9. Brownian motion
Estimation
1. Sufficiency
2. Factorization theorem
3. Minimal sufficiency
4. Completeness
5. Exponential families
6. Ancillary statistics
7. Basu’s theorem
8. Unbiased estimation
9. UMVUE
10. Rao-Blackwell
11. Lehmann-Scheffé
12. Cramer-Rao bound
13. Consistency
14. Method of moments
15. Maximum likelihood estimation
16. Interval estimation
17. Pivotal quantity
18. Coverage probability
Testing of Hypotheses
1. Neyman-Pearson Lemma
2. Most powerful tests
3. MLR property
4. UMP tests
5. UMPU tests
6. Likelihood ratio tests
7. Large sample tests
Non-Parametric Statistics
1. Empirical distribution function
2. Chi-square test
3. Kolmogorov-Smirnov test
4. Sign test
5. Wilcoxon signed rank test
6. Mann-Whitney U test
7. Spearman & Kendall rank correlation
Multivariate Analysis
1. Multivariate Normal
2. Conditional & marginal distributions
3. MLE of mean vector & dispersion
4. Hotelling’s T²
5. Wishart distribution
6. Multiple correlation
7. Partial correlation
Regression Analysis
1. Simple regression
2. Multiple regression
3. R² & Adjusted R²
4. Quadratic forms
5. Fisher–Cochran theorem
6. Gauss-Markov theorem
7. Tests for regression coefficients
8. Confidence intervals
🔍 Chapter-wise Study Plan
| Week | Topics |
|---|---|
| Week 1–2 | Calculus full basics, Sequences, Series, Basic probability |
| Week 3–4 | Matrix theory, Distributions (full), Functions of random variables |
| Week 5–6 | Stochastic processes, Convergence concepts, LLN + CLT, Regression basics |
Complete Yearly Roadmap: Months 1–3: Calculus + Probability + Matrices; Months 4–6: Distributions + Estimation + Hypothesis Testing; Months 7–9: Multivariate + Regression + Stochastic Processes; Months 10–12: Revision + Test-series + High-level problem solving
🧪 Mock Test Series (60+ TESTS)
Sourav Sir Classes Provides:
1. Full-Length Tests (20+)
Simulate the real GATE pattern, timing, and interface.
2. Subject Tests (20+)
Focused on specific subjects for in-depth preparation.
3. Topic Tests (20+)
Micro-level tests to focus on individual topics within a subject.
4. Previous Year Simulation
Full-length tests modeled on actual past GATE ST exams.
5. All-India Ranking
Compare performance with peers nationwide.
6. Performance Graph & Re-evaluation
Visual representation of strength, weakness, speed, and accuracy in tests.
🎯 Special Teaching Techniques
Sourav Sir’s GATE ST coaching uses a scientific, multi-layered approach to ensure concept clarity, problem-solving mastery, and high exam performance.
1. Walk-Based Teaching Structure
Concepts → Examples → PYQ → Advanced Questions
This progressive cognitive scaffold moves students from comprehension → application → analysis.
2. Question Immersion Technique
Train students to “think inside the problem” and translate words → model → strategy → execution.
3. Reverse Learning Method
Solve → Learn → Apply. Start with a problem to create curiosity and concrete context, then extract the underlying theory.
4. Mistake Profiling
Track student-specific errors and neutralize them with targeted remediation.
5. Speed + Accuracy Training
Daily 40-question sprints to build automaticity and reduce panic.
6. 3-Level Revision System
Level 1: Class Notes; Level 2: PYQs; Level 3: Mock tests. Revision in layers enforces memory consolidation.
📍 Our Contact Details
🤖 AI Tools & Support
- AI Mock Evaluator
- AI Doubt Solver
- AI Personalized Strategy Generator
🎮 Gamified Learning
- Weekly Leaderboards
- Badges
- Competitions
- Topper-level challenges
🧾 Important Downloads
❓ FAQ Section
1. What is the GATE ST exam?
GATE ST is the Graduate Aptitude Test in Engineering — Statistics (ST) paper. It is a national-level, computer-based exam used for admission to M.Tech/M.Stat/M.S./Ph.D. programs (IITs, IISc, many NITs) and for screening by several PSUs.
2. What is the eligibility?
Bachelor’s degree in Engineering, Science, or equivalent (B.E./B.Tech/B.Sc/B.Math/B.Stat/Biotech etc.). Final-year students are also allowed to apply.
3. Can a BSc Statistics student apply?
Yes — absolutely. BSc (Hons) Statistics, BSc Mathematics, BStat, and related degrees are commonly eligible.
4. Does Smart Alpha Academy cover the full syllabus?
Yes. Our GATE ST program is complete and mapped to the official syllabus.
5. How many mock tests are provided?
We provide 60+ mock tests as part of the course: a mix of full-length, subject-wise, topic-wise and PYQ-simulation tests.
6. Is the class online or offline?
Smart Alpha Academy runs a hybrid model: both online and offline batches are available.