# IIT JAM Statistics

The Mathematical **Statistics** (MS) test paper of IIT JAM Entrance Examination contains questions from both Maths and Statistics subjects. The question paper comprises of Mathematics (40% weightage) and Statistics (60% weightage). Sample test papers are also available at the institute for everyone to do the practise.

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## Mathematical Statistics Syllabus

**Mathematics:**

IIT JAM Mathematical Statistics Coaching Classes in DelhiSequences and Series: Convergence of sequences of real numbers, Comparison, root and ratio tests for convergence of series of real numbers.

**Differential Calculus:** Limits, continuity and differentiability of functions of one and two variables. Rolle’s theorem, mean value theorems, Taylor’s theorem, indeterminate forms, maxima and minima of functions of one and two variables.IIT JAM Mathematical Statistics Coaching Classes in Delhi

**Integral Calculus:** Fundamental theorems of integral calculus. Double and triple integrals, applications of definite integrals, arc lengths, areas and volumes.IIT JAM Mathematical Statistics Coaching Classes in Delhi

**Matrices:** Rank, inverse of a matrix. systems of linear equations.IIT JAM Mathematical Statistics Coaching Classes in Delhi Linear transformations, eigenvalues and eigenvectors. Cayley-Hamilton theorem, symmetric, skew-symmetric and orthogonal matrices.IIT JAM Mathematical Statistics Coaching Classes in Delhi

**Differential Equations:** Ordinary differential equations of the first order of the form y’ = f(x,y). Linear differential equations of the second order with constant coefficients.IIT JAM Mathematical Statistics Coaching Classes in Delhi

IIT JAM Mathematical Statistics Coaching Classes in Delhi

**Statistics:**

Probability: Axiomatic definition of probability and properties, conditional probability, multiplication rule. Theorem of total probability. Bayes’ theorem and independence of events.IIT JAM Mathematical Statistics Coaching Classes in DelhiIIT JAM Maths Statistics Coaching Classes in Delhi

**Random Variables:** Probability mass function, probability density function and cumulative distribution functions, distribution of a function of a random variable. Mathematical expectation, moments and moment generating function. Chebyshev’s inequality.IIT JAM Maths Stats Coaching Classes in Delhi

**Standard Distributions:** Binomial, negative binomial, geometric, Poisson, hypergeometric, uniform, exponential, gamma, beta and normal distributions. Poisson and normal approximations of a binomial distribution.

**Joint Distributions:** Joint, marginal and conditional distributions. Distribution of functions of random variables. Product moments, correlation, simple linear regression. Independence of random variables.IIT JAM Maths Statistics Coaching Classes in Delhi

**Sampling distributions:** Chi-square, t and F distributions, and their properties.

**Limit Theorems:** Weak law of large numbers. Central limit theorem (i.i.d.with finite variance case only).

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**Estimation:** Unbiasedness, consistency and efficiency of estimators, method of moments and method of maximum likelihood. Sufficiency, factorization theorem. Completeness, Rao-Blackwell and Lehmann-Scheffe theorems, uniformly minimum variance unbiased estimators. Rao-Cramer inequality. Confidence intervals for the parameters of univariate normal, two independent normal, and one parameter exponential distributions.

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**Testing of Hypotheses:** Basic concepts, applications of Neyman-Pearson Lemma for testing simple and composite hypotheses. Likelihood ratio tests for parameters of univariate normal distribution.

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