IIT-JAM STATISTICS ENROLLMENT
4-Step Admission Process
Step 1
Free Counseling & Demo
Step 2
Diagnostic Test / Roadmap
Step 3
Scholarship & Batch Seat
Step 4
Classroom / Live Classes
IIT-JAM Mathematical Statistics (MS)
IIT-JAM Mathematical Statistics (Test Paper Code: MS) is the premier gateway for admission into flagship M.Sc. Statistics, Applied Statistics & Informatics, and Data Science programs across top IITs (IIT Bombay, IIT Kanpur, IIT Kharagpur, IIT Tirupati).
The examination tests candidates rigorously in Mathematics (Calculus & Matrix Algebra — 30% weightage) and Mathematical Statistics (Probability, Distributions, Estimation, Testing & Sampling — 70% weightage).
At Alpha Plus, under the direct guidance of Manish Malik Sir, students achieve deep conceptual command over every proof, formulation, and problem-solving technique needed to secure All India Top Ranks.
Target Institutes
- IIT Bombay — M.Sc. Applied Statistics & Informatics
- IIT Kanpur — M.Sc. Statistics
- IIT Kharagpur — Joint M.Sc.-Ph.D.
- IIT Tirupati — M.Sc. Statistics & Data Science
- IISc Bangalore & NITs (via CCMN)
IIT-JAM Statistics Exam Pattern
| Section | Type of Questions | No. of Questions | Marking Scheme | Negative Marking | Section Marks |
|---|---|---|---|---|---|
| Section A | Multiple Choice Questions (MCQ) | 30 (10 Q × 1M + 20 Q × 2M) | 1 or 2 Marks | −1/3 (for 1M), −2/3 (for 2M) | 50 Marks |
| Section B | Multiple Select Questions (MSQ) | 10 (10 Q × 2M) | 2 Marks | No Negative Marking | 20 Marks |
| Section C | Numerical Answer Type (NAT) | 20 (10 Q × 1M + 10 Q × 2M) | 1 or 2 Marks | No Negative Marking | 30 Marks |
| Grand Total | 60 Questions | — | 100 Marks | ||
Mathematical Statistics Topic Modules
Probability & Distributions
Sample space, axioms of probability, conditional probability, Bayes' theorem, independence, random variables, cumulative distribution functions.
Standard Distributions
Bernoulli, Binomial, Poisson, Geometric, Negative Binomial, Uniform, Exponential, Normal, Gamma, Beta, Cauchy distributions and MGFs.
Joint Distributions
Joint, marginal and conditional distributions, covariance, correlation coefficient, transformation of random variables, bivariate normal distribution.
Sampling Distributions
Chi-square, t, and F distributions, law of large numbers (WLLN), central limit theorem (CLT), order statistics and sample quantiles.
Estimation Theory
Unbiasedness, consistency, sufficiency, Cramer-Rao inequality, UMVUE, Method of Moments, Maximum Likelihood Estimator (MLE), confidence intervals.
Mathematics (Calculus & Matrices)
Differential calculus, sequences and series, matrices, rank, eigenvalues, eigenvectors, determinants, and systems of linear equations.
Secure Your IIT-JAM Statistics Rank
Join the dedicated batch mentored personally by Manish Malik Sir. Comprehensive study modules, 15+ years solved past papers, and national test series.