Our Courses

Scheme of Selection:

Selection will be through Online/ Written Examination (WE) and interview. There are 3 papers for the Examination. Paper I Objective Type (on Statistics) with maximum marks of 100 to be attempted in 120 minutes, Paper-II Descriptive Type (on Statistics) (Question paper displayed on computer, answers to be written on paper) with maximum marks of 100 to be attempted in 180 minutes and Paper-III English – Descriptive (To be typed with help of keyboard) with maximum marks of 100 to be attempted in 90 minutes.

Candidates have to secure minimum marks as may be prescribed by the Board. Candidates, who secureminimum aggregate marks in Paper I, as prescribed, will be shortlisted for Paper-II/ Paper III of the examination based on the aggregate marks obtained in Paper-I. The minimum aggregate cut-off marks for being shortlisted for Paper II and Paper III of the examination will be decided by the Board in relation to the number of vacancies. Roll No. of the candidates shortlisted for Paper II and Paper III examination will be published on RBI web-site, tentatively within a week after Paper -I examination.

Syllabus:-

Standard of papers would be that of Master's Degree examination of any Central University in India.

Paper-I: Questions would cover Probability: Definition of Probability, Standard distribution, Large and small sample theory, Analysis of Variance, Estimation, Testing of Hypotheses, Multivariate analysis and Stochastic Processes.

Paper-II:Questions would cover (i) Probability and Sampling, (ii) Linear Models and Economic Statistics, (iii) Statistical Inference: Estimation, Testing of hypothesis and Nonparametric Test, (iv) Stochastic Processes, (v) Multivariate analysis and (vi) Numerical Analysis and Basic Computer Techniques.
There will be sufficient choice for candidates to attempt the required number of questions from any three or more of the above six groups.

Paper-III: English: Essay, Précis writing, Comprehension and Business/Office Correspondence.

Educational Qualification

• A candidate must have completed his/her bachelor's degree in any discipline.
• Candidates must have secured minimum 55% marks or 5.5 CGPA (for General/ OBC-NCL category candidates) at the graduation level.
• Candidates belonging to the SC/ ST/ PwD category need to have a minimum 50% marks or 5.0 CGPA.
• Candidates appearing in the final year of their graduation can also apply for the examination.

Exam Pattern

The exam paper for JAM is divided into three sections containing 30, 10 and 20 questions respectively. Negative marking will be applicable only for section A. As for the negative marking, for each wrong answer in the 1 mark question, 1/3 of marks will be deducted and for 2 marks questions, 2/3 marks will be deducted. No marks will be deducted for un-attempted questions. Each paper will have 60 question for a total of 100 marks.

Syllabus:-

The Mathematical Statistics (MS) test paper comprises of Mathematics (40% weightage) and Statistics (60%weightage).

Mathematics: Sequences and Series, Differential Calculus, Integral Calculus, Matrices.

Statistics: Probability, Random Variables, Standard Distributions, Joint Distributions, Sampling distributions,Limit Theorems, Estimation, Testing of Hypotheses.

• Candidates enrolled for M.Sc. or having completed 10+2+3 years of the above qualifying examination as on the closing date of online submission of application form, are also eligible to apply in the above subject under the Result Awaited (RA) category on the condition that they complete the qualifying degree with requisite percentage of marks within the validity period of two years to avail the fellowship from the effective date of award.
• Such candidates will have to submit the attestation form duly certified by the Head of the Department/Institute from where the candidate is appearing or has appeared.
• B.Sc. (Hons) or equivalent degree holders or students enrolled in Integrated MS-PhD program with at least 55% marks for General (UR) and OBC candidates; 50% marks for SC/ST, Persons with Disability (PwD) candidates are also eligible to apply. Candidates with bachelor’s degree will be eligible for CSIR fellowship only after getting registered/ enrolled for PhD/Integrated PhD program within the validity period of two years.
• Candidates possessing only Bachelor’s degree are eligible to apply only for Junior Research Fellowship (JRF) and not for Lectureship (LS).
• The eligibility for lectureship of NET qualified candidates will be subject to fulfilling the criteria laid down by UGC. PhD degree holders who have passed Master’s degree prior to 19th September, 1991 with at least 50% marks are eligible to apply for Lectureship only.

Syllabus:-

UNIT – 1: Analysis, Linear, Algebra.

UNIT – 2: Complex Analysis, Algebra, Topology.

UNIT – 3: Ordinary Differential Equations (ODEs), Partial Differential Equations (PDEs), Numerical Analysis, Calculus of Variations, Linear Integral Equations, Classical Mechanics.

UNIT – 4: Descriptive statistics, exploratory data analysis Sample space, discrete probability, independent events, Bayes theorem. Random variables and distribution functions (univariate and multivariate); expectation and moments.Independent random variables, marginal and conditional distributions. Characteristic functions. Probability inequalities (Tchebyshef, Markov, Jensen).Modes of convergence, weak and strong laws of large numbers, Central Limit theorems (i.i.d. case). 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. Standard discrete and continuous univariate distributions.sampling distributions, standard errors and asymptotic distributions, distribution of order statistics and range. Methods of estimation, properties of estimators, confidence intervals. Tests of hypotheses: most powerful and uniformly most powerful tests, likelihood ratio tests. Analysis of discrete data and chi-square test of goodness of fit.Large sample tests. Simple nonparametric tests for one and two sample problems, rank correlation and test for independence. Elementary Bayesian inference. Gauss-Markov models, estimability of parameters, best linear unbiased estimators, confidence intervals, tests for linear hypotheses. Analysis of variance and covariance. Fixed, random and mixed effects models. Simple and multiple linear regression. Elementary regression diagnostics.Logistic regression.Multivariate normal distribution, Wishart distribution and their properties.Distribution of quadratic forms.Inference for parameters, partial and multiple correlation coefficients and related tests. Data reduction techniques: Principle component analysis, Discriminant analysis, Cluster analysis, Canonical correlation. Simple random sampling, stratified sampling and systematic sampling. Probability proportional to size sampling. Ratio and regression methods.Completely randomized designs, randomized block designs and Latin-square designs.Connectedness and orthogonality of block designs, BIBD. 2K factorial experiments: confounding and construction. Hazard function and failure rates, censoring and life testing, series and parallel systems.Linear programming problem, simplex methods, duality.Elementary queuing and inventory models. Steady-state solutions of Markovian queuing models: M/M/1, M/M/1 with limited waiting space, M/M/C, M/M/C with limited waiting space, M/G/1. All students are expected to answer questions from Unit I. Students in mathematics are expected to answer additional question from Unit II and III. Students with in statistics are expected to answer additional question from Unit IV.