UPSC ISS STATISTICS PAPER 3 SYLLABUS: UPSC conducts Indian Economic Service/ Indian statistical service Exam every year. A candidate may compete for any one of the services only. UPSC IES/ISS exam consists of two stages. Stage I (Written examination) carrying a maximum of 1000 marks. UPSC ISS Statistics III & IV papers of Descriptive Type having Short Answer/Small Problems Questions (50%) and Long Answer and Comprehension problem questions (50%) with maximum marks of 200 in each paper to be attempted in 180 minutes. UPSC ISS Statistics paper3 syllabus mainly focused on Sampling Techniques, Design and Analysis of Experiments, Economic Statistics, Econometrics. Here is a detailed syllabus of UPSC ISS STATISTICS PAPER 3
UPSC ISS STATISTICS PAPER 3 SYLLABUS
STATISTICS PAPER 3 SYLLABUS (Descriptive Type)
Concept of population and sample, need for sampling, complete enumeration versus sampling, basic concepts in sampling, sampling and Non-sampling error, Methodologies in sample surveys (questionnaires, sampling design and methods followed in field investigation) by NSSO. Subjective or purposive sampling, probability sampling or random sampling, simple random sampling with and without replacement, estimation of population mean, population proportions and their standard errors. Stratified random sampling, proportional and optimum allocation, comparison with simpler and om sampling for fixed sample size. Covariance and Variance Function. Ratio, product and regression methods of estimation, estimation of population mean, evaluation of Bias and Variance to the first order of approximation, comparison with simpler and om sampling. Systematic sampling (when population size(N) is an integer multiple of sampling size (n)). Estimation of population mean and standard error of this estimate, comparison with simpler and om sampling. Sampling with probability proportional to size (with and without replacement method), Des Raj and Das estimators for n=2,Horvitz-Thomson’s estimator Equal size cluster sampling: estimators of population mean and total and their standard errors, comparison of cluster sampling with SRS in terms of intra-class correlation coefficient. Concept of multi stage sampling and its application, two-stage sampling with equal number of second stage units, estimation of population mean and total. Double sampling in ratio and regression methods of estimation. Concept of Inter penetrating sub-sampling.
Nature of econometrics, the general linear model (GLM) and its extensions, ordinary least squares (OLS)estimation and prediction, generalized least squares (GLS) estimation and prediction, heteroscedastic disturbances, pure and mixed estimation. Auto correlation, its consequences and tests. The il BLUS procedure, estimation and prediction, multi-collinearity problem, its implications and tools for handling the problem, ridge regression. Linear regression and stochastic regression, instrumental variable estimation, errors in variables, auto regressive linear regression, lagged variables, distributed lag models, estimation of lags by OLS method, Koyck’s geo metric lag model. Simultaneous linear equations model and its generalization, identification problem, restrictions on structural parameters, rank and order conditions. Estimation in simultaneous equations model, recursive systems, 2SLS estimators, limited information estimators, k-class estimators, 3SLSestimator, full information maximum likelihood method, prediction and simultaneous confidence intervals.
Index Numbers: Price relatives and quantity or volume relatives, Link and chain relatives composition of index numbers; Laspeyre’s, Paasches’, Marshal Edge worth and Fisher index numbers; chain base index number, tests for index number, Construction of index numbers of wholesale and consumer prices, Income distribution-Pareto and Engelcurves, Concentration curve, Methods of estimating national income, Inter-sectoral flows, Inter-industry table, Role of CSO. Demand Analysis Time Series Analysis: Economic time series, different components, illustration, additive and multiplicative models, determination of trend, seasonal and cyclical fluctuations. Time-series as discrete parameter stochastic process, auto covariance and auto correlation functions and their properties. Exploratory time Series analysis, tests for trend and seasonality, exponential and moving average smoothing. Holt and Winters smoothing, forecasting based on smoothing. Detailed study of the stationary processes:(1)moving average (MA),(2)auto regressive (AR),(3)ARMA and (4)AR integrated MA (ARIMA)models. Box Jenkins models, choice of AR and MA periods. Discussion (without proof) of estimation of mean, auto covariance and auto correlation functions under large sample theory, estimation of ARIMA model parameters. Spectral analysis of weakly stationary process, period gram and correlogram analyses, computations based on Fourier transform
For Descriptive Type exams handwriting should be legible. Improve writing skills. Change in scheme of IES/ISS examination and syllabi of Indian Statistical Service examination with effect from 2016 examination. Above mentioned ISS statistics paper 3 syllabus is as per new scheme of IES/ISS examination. For more details of UPSC IES/ISS exam syllabus you can go through UPSC Official Website: www.upsc.gov.in