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GATE 2021 Statistics Syllabus (Released) – Get (ST) PDF Here

GATE 2021 Syllabus of Statistics has been Released. GATE 2021 is a national level exam organized by IIT Delhi.

The Engineering Graduation Skill Test (GATE 2021) is organized for admission to PG courses in the field of engineering and technology, specifically ME / M.Tech.

The Exam will be held on 1st week of February 2021. See here for complete information about the GATE 2021 Syllabus.

GATE 2021 Statistics Syllabus – PDF Released

New GATE 2021 Statistics Syllabus has been Released. Click Here to Download PDF.

GATE 2021 Statistics Syllabus

Latest Applications For Various UG & PG Courses Open 2020:

    1. Shiv Nadar University, Delhi, NCR | Admission Open 2020. Apply Now
    2. Bennett University (Times Group), Admission Open for 2020. Apply Now
    3. Manav Rachna University, Haryana – 2020 UG & PG Admission Open. Apply Now
    4. Manipal University 2020 Admission Open For UG & PG Courses. Apply Now
    5. UPES, Dehradun Enroll Yourself for the Academic Year 2020. Apply Now
    6. LPU, Punjab Admissions 2020 Open | Secure Your Admission Online‎. Apply Now
    7. Chandigarh University, Punjab 2020 Admission Open for all Courses. Apply Now
    8. Sharda University, Admission Open 2020, Few Days left. Apply Now
    9. MIT World Peace University, Admissions Open for All Courses 2019-20. Apply Now

Calculus: Finite, countable and uncountable sets, Real number system as a complete ordered field, Archimedean property; Sequences and series, convergence; Limits, continuity, uniform continuity, differentiability, mean value theorems; Riemann integration, Improper integrals; Functions of two or three variables, continuity, directional derivatives, partial derivatives, total derivative,

maxima and minima, saddle point, a method of Lagrange’s multipliers; Double and Triple integrals and their applications; Line integrals and Surface
integrals, Green’s theorem, Stokes’ theorem, and Gauss divergence theorem.

Linear Algebra: Finite dimensional vector spaces over real or complex fields; Linear transformations and their matrix representations, rank; systems of linear equations, eigenvalues and eigenvectors, minimal polynomial, Cayley-Hamilton Theorem, diagonalization, Jordan canonical form,

symmetric, skew-symmetric, Hermitian, skew-Hermitian, orthogonal and unitary matrices; Finite dimensional inner product spaces, Gram- Schmidt orthonormalization process, definite forms.

Probability: Classical, relative frequency and axiomatic definitions of probability, conditional probability, Bayes’ theorem, independent events; Random variables and probability distributions, moments and moment generating functions, quantiles; Standard discrete and continuous univariate distributions;

Probability inequalities (Chebyshev, Markov, Jensen); Function of a random variable; Jointly distributed random variables, marginal and conditional distributions, product moments, joint moment generating
functions, independence of random variables; Transformations of random variables, sampling distributions, distribution of order statistics and range; Characteristic functions; Modes of convergence; Weak and strong laws of large numbers; Central limit theorem for I .i.d. random variables with the existence of higher-order moments.

Stochastic Processes: Markov chains with finite and countable state space, classification of states, limiting behavior of n-step transition probabilities, stationary distribution, Poisson and birth-and-death processes.

Inference: Unbiasedness, consistency, sufficiency, completeness, uniformly minimum variance unbiased estimation, method of moments and maximum likelihood estimations; Confidence intervals; Tests of hypotheses, most powerful and uniformly most powerful tests, likelihood ratio tests, large sample test, Sign test, Wilcoxon signed-rank test, Mann- Whitney U test, test for independence and Chi-square test for goodness of fit.

Regression Analysis: Simple and multiple linear regression, polynomial regression, estimation, confidence intervals and testing for regression coefficients; Partial and multiple correlation coefficients.

Multivariate Analysis: Basic properties of the multivariate normal distribution; Multinomial distribution; Wishart distribution; Hotelling’s T2 and related tests; Principal component analysis; Discriminant analysis; Clustering.

Design of Experiments: One and two-way ANOVA, CRD, RBD, LSD, 22 and 23 Factorial Experiments.

Textile Engineering Mathematics

Latest Applications For Various UG & PG Courses Open 2020:

    1. Shiv Nadar University, Delhi, NCR | Admission Open 2020. Apply Now
    2. Bennett University (Times Group), Admission Open for 2020. Apply Now
    3. Manav Rachna University, Haryana – 2020 UG & PG Admission Open. Apply Now
    4. Manipal University 2020 Admission Open For UG & PG Courses. Apply Now
    5. UPES, Dehradun Enroll Yourself for the Academic Year 2020. Apply Now
    6. LPU, Punjab Admissions 2020 Open | Secure Your Admission Online‎. Apply Now
    7. Chandigarh University, Punjab 2020 Admission Open for all Courses. Apply Now
    8. Sharda University, Admission Open 2020, Few Days left. Apply Now
    9. MIT World Peace University, Admissions Open for All Courses 2019-20. Apply Now

Linear Algebra: Matrices and Determinants, Systems of linear equations, Eigenvalues and eigenvectors.

Calculus: Limit, continuity, and differentiability; Partial Derivatives; Maxima and minima; Sequences and series; Test for convergence; Fourier series.

Vector Calculus: Gradient; Divergence and Curl; Line; surface and volume integrals; Stokes, Gauss and Green’s theorems.

Differential Equations: Linear and non-linear first order ODEs; Higher order linear ODEs with constant coefficients; Cauchy’s and Euler’s equations; Laplace transforms; PDEs -Laplace, heat and wave equations.

Probability and Statistics: Mean, median, mode and standard deviation; Random variables; Poisson, normal and binomial distributions; Correlation and regression analysis.

Numerical Methods: Solutions of linear and non-linear algebraic equations; integration of trapezoidal and Simpson’s rule; single and multi-step methods for differential equations.

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