Graduate
Aptitude Test in Engineering (GATE) is a examination on the
comprehensive of the candidates in various undergraduate subjects in
Engineering/ Technology/ Architecture and post-graduate level subjects
in Science. The GATE 2019 examination will be conducted for 24
subjects and it would be distributed over 2nd, 3rd, 9th and 10th of
February 2019. The GATE examination centres are in different cities
across India, as well as, in six cities outside india. The examination
would be purely a Computer Based Test (CBT). This is a new paper with
subject name statistics (ST) were going to introduced. GATE Online
Application Processing System (GOAPS) Website Opens from 01.09.2018
onwards and the GATE 2019 Examination Results will be announce on
16.03.2019.
| GATE Online Application Processing System (GOAPS) Website Opens | Saturday | 01.09.2018 |
| Closing Date for Submission of (Online) Application | Friday | 21.09.2018 |
| Extended Closing Date for Submission of (Online) Application | Monday | 01.10.2018 |
| Last Date for Requesting Change of Examination City (an additional fee will be applicable) | Friday | 16.11.2018 |
| Admit Card will be available in the Online Application Portal (for printing) | Friday | 04.01.2019 |
| GATE 2019 Examination Forenoon: 9:00 AM to 12:00 Noon (Tentative) Afternoon: 2:00 PM to 5:00 PM (Tentative) | Saturday Sunday Saturday Sunday |
02.03.2019 03.03.2019 09.03.2019 10.03.2019 |
| Announcement of the Results in the Online Application Portal | Saturday | 16.03.2019 |
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, 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 existence of higher order moments
Stochastic Processes:
Markov
chains with finite and countable state space, classification of states,
limiting behaviour 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 multivariate normal distribution; Multinomial
distribution; Wishart distribution; Hotellings 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.
For more details : http://gate.iitm.ac.in/