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IIT JAM Mathematical Statistics Syllabus 2025: Detailed Overview & PDF Download

Pallavi Pradeep Purbey
Pallavi Pradeep Purbey

Updated on - Jul 14, 2025

The IIT JAM Mathematical Statistics Syllabus 2025 is designed to evaluate candidates’ proficiency in both Mathematics and Statistics for admission into postgraduate programs such as M.Sc., Joint M.Sc.-Ph.D., and other integrated courses offered by IITs and IISc.

The IIT JAM syllabus for Mathematical Statistics is divided into two sections: Mathematics (Section A) and Statistics (Section B), covering topics like calculus, linear algebra, probability, and inference. A clear understanding of the syllabus is essential for effective preparation and achieving a competitive edge in the IIT JAM 2025.

The IIT JAM Mathematical Statistics Syllabus 2025 provides a comprehensive overview of the topics you need to master, ranging from calculus and linear algebra to probability theory, estimation, and hypothesis testing. This thoughtfully structured syllabus ensures aspirants cover both foundational mathematics and core statistical concepts. You can download the detailed official PDF here.

Subject PDF Link
IIT JAM Mathematical Statistics Syllabus 2025  Download Here

IIT JAM Mathematical Statistics Syllabus 2025

The IIT JAM syllabus of Mathematics Statistics is divided into two sections, Mathematics and Statistics, you can check the section-wise chapter details in the table given below to understand the syllabus better.

IIT JAM Mathematical Statistics Syllabus 2025
Chapter Details
Section A: Mathematics  
Sequences and Series of Real Numbers
  • Convergence and divergence
  • Behavior of geometric and arithmetic series
  • Limit of a sequence
  • Tests for convergence (comparison, ratio, root, etc.)
Differential Calculus
  • Limit and continuity
  • Differentiability
  • Mean value theorems
  • Taylor and Maclaurin series
  • Maxima and minima
  • Partial derivatives and applications
Integral Calculus
  • Definite and indefinite integrals
  • Properties of definite integrals
  • Improper integrals
  • Double and triple integrals
Matrices and Determinants
  • Basic operations, types of matrices
  • Determinant and inverse of a matrix
  • Rank and solution of linear equations
  • Eigenvalues and eigenvectors
  • Cayley-Hamilton theorem
Vector Calculus
  • Scalar and vector fields
  • Gradient, divergence, and curl
  • Line, surface, and volume integrals
  • Green’s theorem, Stokes’ theorem, and Gauss divergence theorem
Section B: Statistics
Probability
  • Basic definitions and theorems
  • Conditional probability and Bayes’ theorem
  • Random variables (discrete and continuous)
  • Probability mass function (PMF), probability density function (PDF)
  • Cumulative distribution function (CDF)
  • Expectation, variance, and moments
  • Moment generating functions
  • Standard distributions: Binomial, Poisson, Geometric, Exponential, Normal, Uniform
Standard Distributions
  • Properties and applications of:
    • Bernoulli
    • Binomial
    • Poisson
    • Geometric
    • Hypergeometric
    • Exponential
    • Normal
    • Uniform
    • Gamma and Beta distributions
Joint Distributions
  • Joint, marginal, and conditional distribution
  • Independence of random variables
  • Covariance and correlation
  • Distribution of sums and differences of random variables
Sampling Distributions
  • Sample mean and varianc
  • Chi-square, t, and F distributions
  • Central Limit Theorem
Estimation and Testing of Hypotheses
  • Point and interval estimation
  • Properties of estimators: unbiasedness, consistency, efficiency
  • Maximum Likelihood Estimation (MLE)
  • Hypothesis testing: Neyman-Pearson lemma
  • Tests based on normal, t, chi-square, and F-distributions
Linear Models and Regression
  • Simple and multiple linear regression
  • Least squares estimation
  • Properties of estimators in linear models
  • Gauss-Markov theorem
  • Correlation and coefficient of determination
Multivariate Analysis (Basics)
  • Mean vector and covariance matrix
  • Multivariate normal distribution
  • Principal Component Analysis (PCA)

IIT JAM Mathematical Statistics Overview

You can check the table given below to get an overview of the IIT JAM exam pattern, it will help you to understand the trend and prepare better for the exam

IIT JAM Mathematical Statistics Overview
Particulars Details
Paper Code MS
Mode of Exam Computer-Based Test (CBT)
Duration 3 Hours
Total Marks 100
Total Number of Questions 60
Medium of Question Paper English only

Structure of the IIT JAM Mathematical Statistics Paper

The IIT JAM Mathematical Statistics Paper follows a structure that should be understood well to prepare accordingly and in a better way. 

Structure of the IIT JAM Mathematical Statistics Paper
Section Number of Questions  Marking Scheme 
A 30 (Multiple Choice Questions - MCQ) +1 or +2 for correct answers, negative marking for wrong ones
B 10 (Multiple Select Questions - MSQ) No negative marking
C 20 (Numerical Answer Type - NAT) No negative marking

Preparation Tips for IIT JAM MS 2025

The IIT JAM Mathematical Statistics examination is an important test. Understanding the syllabus and preparing strategically can help you achieve the success you desire. There are a few preparation tips given below that can add to your IIT JAM preparation

  • Understand the Concepts Thoroughly: Instead of rote learning, focus on conceptual clarity—especially in probability and distributions.
  • Solve Previous Year Papers: Analyze the type of questions and their difficulty level.
  • Work on Both Math and Statistics Equally: Balance your preparation across both sections to avoid scoring asymmetry.
  • Practice Numerical Answer Type Questions: These require precision and are often scoring since there’s no negative marking.
  • Revise Important Theorems and Properties: Especially in linear algebra, calculus, and probability.

For IIT JAM Mathematical Statistics 2025, aspirants should refer to "Introduction to Probability" by Sheldon Ross and "Fundamentals of Mathematical Statistics" by S.C. Gupta & V.K. Kapoor. These recommended IIT JAM books cover core concepts in probability, inference, and statistical theory essential for the exam.

Books Recommended for IIT JAM Mathematical Statistics 2025
Books Description
H.C. Verma (Physics)  A highly recommended book for conceptual clarity and problem-solving in physics, ideal for JEE and other competitive exams.
O.P. Tandon (Chemistry) A comprehensive guide covering physical, inorganic, and organic chemistry with theory and practice problems suitable for advanced level preparation.
Morrison & Boyd (Chemistry) An in-depth textbook focused on organic chemistry concepts with detailed mechanisms and real-life applications, perfect for building strong fundamentals.
G. Tewani (Mathematics)  A JEE-focused mathematics book known for its clear explanations and a wide range of practice questions across all topics.
P. Bahadur (Chemistry) Best suited for mastering physical chemistry with numerous numerical problems and theory explanations tailored for entrance exams.
S.L. Loney (Mathematics)  A classic book for trigonometry and coordinate geometry that builds a deep understanding through elegant methods and challenging problems.

Conclusion

The IIT JAM Mathematical Statistics Syllabus 2025 is comprehensive and well-structured, aiming to test both theoretical understanding and practical application. While preparing a strategy for the examination, you must focus on developing a strong mathematical base and statistical reasoning skills. With regular practice and a focused study plan, cracking the IIT JAM MS paper is well within reach. 

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