IIT JAM 2025 MATHEMATICAL STATISTICS SYLLABUS
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IIT JAM Mathematical Statistics Syllabus 2023: Section-wise Syllabus PDF, Preparation Tips, Books
IIT JAM 2023 Syllabus for Mathematical Statistics is divided into two parts i.e. Mathematics and Statistics.The weightage of the mathematics section is 40% and of the statistics section, it is 60%. Candidates who are planning to appear for Mathematical Statistics can download the complete IIT JAM 2023 Syllabus for Mathematical Statics from PDF link given below. Download IIT JAM Question Papers
Candidates need to analyze section-wise syllabus rigorously before appearing in the exam. Candidates should also note that the question paper will be divided into 3 sections and three types of questions will be asked in the paper i.e. MCQ, MSQ, and NAT. Check IIT JAM 2023 Exam Pattern
| Download IIT JAM 2023 Mathematical Statistics Syllabus PDF |
Read the article to know more about IIT JAM section-wise syllabus of mathematical statistics, exam pattern, best books, and preparation tips. Check IIT JAM Preparation Tips
IIT JAM Syllabus for Mathematical Statistics
There are two sections such as Mathematics and Statistics in IIT JAM Syllabus. Section-wise details for Mathematics and Statistics Syllabus for IIT JAM are tabulated below.
IIT JAM Mathematics Syllabus
| Topics | Subtopics |
|---|---|
| Sequences and Series | All the areas included in this section are Convergence of real numbers sequences, Comparison, root and ratio tests for convergence of series of real numbers. |
| Differential Calculus | In this unit, all the subtopics covered are Limits, continuity and differentiability of functions of one and two variables. indeterminate forms, maxima and minima of functions of one and two variables. Apart from that, there are some theorems such as Rolle's theorem, mean value theorems, Taylor's theorem, etc. |
| Integral Calculus | Under this section all the properties are Fundamental theorems of integral calculus; Double and triple integrals; applications of definite integrals, arc lengths, areas and volumes, etc |
| Matrices | From Rank, inverse of a matrix; Systems of linear equations; Linear transformations, eigenvalues and eigenvectors to Cayley-Hamilton theorem; symmetric; skew-symmetric and orthogonal matrices are explained in this section. |
IIT JAM Statistics Syllabus
| Probability | This section covers the Axiomatic definition of probability and properties, conditional probability, and multiplication rule. It also covers the Theorem of total probability along with Bayes’ theorem and independence of events. |
| Random Variables | There are various sub topics such as Probability mass function, density function and cumulative distribution functions along with distribution of a function of a random variable. Mathematical expectation, moments and moment generating function. Chebyshev's inequality in this unit. |
| Standard Distributions | This section includes Binomial, negative binomial, geometric, Poisson and hypergeometric, uniform, exponential, gamma, beta, and normal distributions. Apart from that, there are Poisson and normal approximations of a binomial distribution. |
| Joint Distributions | In this part, all the areas are Joint, marginal and conditional distributions; Distribution of functions of random variables; Joint moment generating function. It also covers Product moments, correlation, simple linear regression; Independence of random variables. |
| Sampling distributions and Limit Theorems | In the first part, there are Chi-square along with t and F distributions, and their properties. And in the second part, all the areas are the Weak law of large numbers and the Central limit theorem that defines i.i.d. with finite variance case only. |
| Estimation | This section consists of Unbiasedness, consistency, and efficiency of estimators, details of the method of moments as well as the method of maximum likelihood. Besides that, there is Sufficiency, factorization theorem also included. From Completeness, Rao-Blackwell and Lehmann-Scheffe theorems, uniformly minimum variance unbiased estimators to Rao-Cramer inequality; Confidence intervals for the parameters of univariate normal; two independents normal, and one parameter exponential distributions are there. |
| Testing of Hypotheses | Here are some of the primary concepts and applications of Neyman-Pearson Lemma for testing simple and composite hypotheses along with Likelihood ratio tests for parameters of the univariate normal distribution, etc. |
What are the Valuable Tips to Prepare IIT JAM Syllabus for Mathematical Statistics?
Some of the most salient principles for taking preparation for the subject Mathematics and Statistics of IIT JAM Syllabus are given below.
- As the preparation depends on the primary concepts of the syllabus, so, candidate need to well aware of the entire syllabus
- Make a study plan with all the subject matter of the syllabus for some months
- Need to improve problem-solving skills as this section is based on the that
- Centre of attention must be in probability, variable and also in distribution
- Practice all the theorems and formula
- Note down all the formulas one by one and keep practicing daily with the time table
- Make important notes from all the theorems and mark them in bold
- It is a must to solve all the questions from the previous year paper
- Start giving the mock test as many times as possible and do not forget to solve the sample papers
- It is a good practice to revise all the areas from the syllabus to remember
IIT JAM Mathematical Statistics Exam Pattern 2023
IIT JAM Mathematics and Statistics Exam Pattern is listed below in a table format:
| Particulars | Details |
|---|---|
| Total Duration of the Test | 3 hours |
| Total number of questions | 60 |
| Number of Section | 3 (Sec A, B and C) |
| Question Type for the Test | MCQ, MSQ and NAT |
| Marks in Total | 100 |
Section Wise Marks Division
| Section | Number of Questions in Total | Question Wise Marks Distribution | Marks in Total |
|---|---|---|---|
| Section A | 10 | 1 | 10 |
| 20 | 2 | 40 | |
| Section B | 10 | 2 | 20 |
| Section C | 10 | 1 | 10 |
| 10 | 2 | 20 |
Quick Links:
IIT JAM Statistics and Mathematics Books for Preparation 2023
Below are some recommended books in a table for preparation for the examination:
| Section | Book Name | Author |
|---|---|---|
| Mathematical Statistics | IIT-JAM: M.Sc. Mathematical Statistics Joint Admission Test | Anand Kumar |
| Mathematics | A Complete Resource Manual M.Sc Mathematics Entrance examination | Suraj Singh and Reshmi Gupta |
| Mathematical Statistics | Fundamentals of Mathematical Statistics | S.C. Gupta and V K Kapoor |
| Mathematical Statistics | Introduction to Mathematical Statistics | Hogg |
| Statistics | An Introduction to Probability and Statistics | Vijay K. Rohatgi and A.K. Md. Ehsanes Saleh |
Also Check:IIT JAM Paper Analysis
IIT JAM Syllabus for Mathematical Statistics FAQ
Ques. Are there any changes in IIT JAM Syllabus for Mathematics and Statistics?
Ans. No, there are no changes in the Mathematics and Statistics Syllabus for IIT JAM. All the sections will remain the same as the previous year.
Ques. What should I know as the basic mathematical concepts from IIT JAM Mathematics and Statistics Syllabus?
Ans. Many sections fall under this section such as functions, maxima, and minima, vectors, matrices, integrals, determinants, etc.
Ques. Which part is the most difficult part between Statistics and Mathematics in IIT JAM Syllabus?
Ans. If you study in a proper way no part will be difficult for you to score well.
Ques. Which section is the scoring one between Statistics and Mathematics in IIT JAM Syllabus?
Ans. As per the expert advice, you can score maximum from both the section Mathematics and Statistics but the syllabus covers 60% area of Statistics and 40% of Mathematics.
Ques. Can I give less importance to the Central limit theorem from the Statistics and Mathematics Syllabus in IIT JAM?
Ans. No, you cannot avoid this section as this is one of the most important parts of Statistics.
*The article might have information for the previous academic years, which will be updated soon subject to the notification issued by the University/College
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