Age Age Limit (As on May 01, 2023): a) A candidate must have attained the age of 21 years and must not have attained the age of 30 years on May 01, 2023 i.e., he/she must have been born not earlier than May 02, 1993 and not later than May 01, 2002. b) The upper age-limit prescribed above will be relaxed: i. up to a maximum of five years for candidates belonging to a Scheduled Caste or a Scheduled Tribe if the posts are reserved for them; i. up toa maximum of three years in the case of candidates belonging to Other Backward Classes who are eligible to avail of reservation applicable to such candidates if the posts
PATTERN
| Name of Paper | Duration | Maximum Marks |
|---|---|---|
| Paper-I Objective Type (on Statistics) | 120 | 100 |
| Paper-II Descriptive Type (on Statistics) | 180 | 100 |
| Paper-III English — Descriptive | 90 | 100 |
Paper-I(Objective type on Statistics) will be conducted online and comprise multiple choice questions.
Paper-II(on Statistics) will be a descriptive type pen/paper based examination where the questions will be displayed on computer screen, answers to be written on paper.
Paper-III(English) will be of descriptive type where the candidates will be expected to type out answers on a computer.
Suggested Reading Materials
For PaperI and Paper II
Theory of Probability and Probability Distributions * Rohatgi, V. K. and Saleh, AK. Md. E. (2005). An Introduction to Probability and Statistics . Goon, A.M., Gupta, M.K. and Dasgupta. B. (1985). An Outline of Statistical Theory Vol-1&1 . Sukhatme, P.V., Sukhatme, B.V., Sukhatme, S. and Asok, C. (1984). Sampling Theory of Surveys with Applications S. C. Gupta, V. K. Kapoor (2000). Fundamentals of Mathematical Statistics W.G. Cochran (1977). Sampling TechniquesLinear Models and Economic Statistics
P.G. Hoel, S.C. Port and C.J. Stone (1971). Introduction to Statistical Theory A.M. Mood, F.A. Graybill and D.C. Boes (1974). Introduction to Theory of Statistics R.G.D. Allen (1975). Index Numbers in Theory and Practice Statistical Inference Kale, B.K. (1999). A First Course on Parametric Inference Rao, C.R. (1973). Linear Statistical Inference and Its Applications Bartoszynski, R. and Bugaj, M.N. (2007). Probability and Statistical Inference Gibbons, J.D. and Chakraborti, S. (1992). Nonparametric Statistical Inference Stochastic Processes Bhat, B.R. (2000). Stochastic Models- Analysis and Applications Prabhu, N.U. (2007). Stochastic Processes: Basic Theory and its Applications J. Medhi (2009). Stochastic Process Multivariate Analysis Anderson, T.W. (2003). An Introduction to Multivariate Statistical Analysis Arnold, Steven F. (1981). The Theory of Linear Models and Multivariate Analysis Giri, N.C. (1977). Multivariate Statistical Inference, Academic Press Alvin C. Rencher (2012). Methods of Multivariate Analysis Econometrics and Time Series Johnston, J. (1984). Econometric Methods James H. Stock and Mark W. Watson (2019). Introduction to Econometrics J.D. Hamilton (1994). Time Series Analysis William H. Greene (2018). Econometric Analysis
Statistical Computing and Data Science, Artificial Intelligence and Machine Learning Techniques Sheldon M. Ross (2012). Simulation Trevor Hastie, Robert Tibshirani, Jerome Friedman (2009). The Elements of Statistical Learning, Data Mining, Inference, and Prediction, Second Edition Charu C. Aggarwal (2018). Neural Networks and Deep Learning