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Indian Statistical Service - ISS Exam Syllabus (General Economics)

Section-II

Standard and Syllabi for ISS Exam

Thestandard of papers in General English and General Studies will be suchas may be expected of a graduate of an Indian University.

Thestandard of papers in the other subjects will be that of the Master'sdegree examination of an Indian University in the relevant disciplines.The candidates will be expected to illustrate theory by facts, and toanalyse problems with the help of theory.

They will be expected to be particularly conversant with Indian problems in the field of Economic/Statistics.

General English

Candidateswill be required to write an essay in English. Other questions will bedesigned to test their understanding of English and workmanlike use ofwords. Passages will usually be set for summary or precis.

General Studies

GeneralKnowledge including knowledge of current events and of such matters ofevery day observation and experience in their scientific aspects as maybe expected of an educated person who has not made a special study ofany scientific subject.

The paper willalso include questions on Indian Polity including the political systemand the Constitution of India, History of India and Geography of anature which the candidate should be able to answer without specialstudy.

General Economics-I

General Economics-II

General Economics-III

Standard and Syllabi

Indian Economics

Statistics-I

(i) Probaility

Elementsof measure theory, Classical definitions and axiomatic approach. Samplespace. Class of events and Probability measure. Laws of total andcompound probability. Probability of m events out of n. Conditionalprobability, Bayes' theorem. Random variables - discrete andcontinuous. Distribution function.

Standardprobability distributions - Bernoulli, uniform, binomial, Poisson,geometric, rectangular, exponential, normal, Cauchy, hypergeometric,multinomial, Laplace, negative binomial, beta, gamma, lognormal andcompound. Poisson distribution. Joint distributions, conditionaldistributions, Distributions of functions of random variables.

Convergencein distribution, in probability, with probability one and in meansquare. Moments and cumulants. Mathematical expectation and conditionalexpectation. Characteristic function and moment and probabilitygenerating functions Inversion uniqueness and continuity theorems.Borel 0-1 law: Kolmogorov's 0-1 law.

Tchebycheff'sand Kolmogorov's inequalities. Laws of large numbers and central limittheorems for independent variables. Conditional expectation andMartingales.

(ii) Statistical Methods

iii) Numerical Analysis

Interpolationformulae (with remainder terms) due to Lagrange, Newton-Gregory, NewtonDivided different, Gauss and Striling. Euler-Maclaurin's summationformula. Inverse interpolation. Numerical integration anddifferentiation. Difference equations of the first order. Lineardifference equations with constant coefficients.

Statistics II

i) Linear Models

Theoryof linear estimation. Gauss-Markoff setup. Least square estimators. Useof g-inverse. analysis of one-way and two way classified data-fixed,mixed and random effect models. Tests for regression coefficients.

ii) Estimation

Characteristicsof good estimator. Estimation methods of maximum likelihood, minimumchi-square, moments and least squares. Optimal properties of maximumlikelihood estimators. Minimum variance unbiased estimators. Minimumvariance bound estimators. Cramer-Rao inequality. Bhattacharya bounds.Sufficient estimator. factorisation theorem. Complete statistics.

Rao-Blackwell theorem. Confidence interval estimation. Optimum confidence bounds. Resampling, Bootstrap and Jacknife.

iii) Hypotheses testing and Statistical Quality Control

iv) Multivariate Analysis

Multivariatenormal distribution. Estimation of mean Vector and covariance matrix.Distribution of Hotelling's T2-statistic, Mahalanobis's D2-statistic,and their use in testing. Partial and multiple correlation coefficientsin samples from a multivariate normal population. Wishart'sdistribution, its reproductive and other properties. Wilk's criterion.Discriminant function. Principal components. Canonical variates andcorrelations.

Statistics III

i) Sampling Techniques

Censusversus sample survey. Pilot and large scale sample surveys. Role of NSSorganisation. Simple random sampling with and without replacement.Stratified sampling and sample allocations. Cos and Variance functions.Ratio and Regression methods of estimation. Sampling with probabilityproportional to size. Cluster, double, multiphase, multistage andsystematic sampling. Interpenetrating sub-sampling. Non-sampling errors.

ii) Design and Analysis of Experiments

Principlesof design of experiments. Layout and analysis of completely randomised,randomised block and Latin square designs. Factorial experiments andconfounding in 2n and 3n experiments. Split-plot and strip-plotdesigns. Construction and analysis of balanced and partially balancedincomplete block designs. Analysis of covariance. Analysis ofnon-orthogonal data. analysis of missing and mixed plot data.

iii) Economic Statistics

Componentsof time series. Methods of their determination-variate differencemethod. Yule-Slutsky effect. Correlogram. Autoregressive models offirst and second order. Periodogram analysis. Index numbers of pricesand quantities and their relative merits. Construction of index numbersof 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.

iv) Econometrics

Theoryand analysis of consumer demand-specification and estimation of demandfunctions. Demand elasticities. Structure and model. Estimation ofparameters in single equation model-classical least squares,generalised least-square, heteroscedasticity, serial correlation,multi-collinearity, errors in variable model. Simultaneous equationmodels-Identification, rank and other conditions. Indirect leastsquares and two stage least squares. Short-term economic forecasting.

Statistics-IV

(i) Stochastic Processes

Specificationsof a Stochastic Process, Markov chains, classification of states,limiting probabilities; stationary distribution; Random walk andGambler's ruin problem. Poisson process, Birth and death process;applications to Queues-M/M/I and M/M/C models. Branching Process.

(ii) Operations Research

Elementsof linear programming. Simplex procedure. Pirnciple of duality.Transport and assignment problems. Single and multi-period inventorycontrol models. ABC analysis. General simulation problems. Replacemnetmodels for items that fail and or items that deteriorate.

(iii) Demography and Vital Statistics

Thelife table, its constitution and properties. Makehams and Gompertzcurves. National life tables. UN model life tables. Abridged lifetables. Stable and stationary populations. Different birth rates. Totalfertility rate. Gross and net reproduction rates. Different mortalityrates. Standardised death rate. Internal and international migration:net migration.

International andpostcensal estimates. Projection method including logistic curvefitting. Decennial population census in India.

(iv) Computer Application and Data Processing

(a) Computer Application

Computersystem concepts: Computer system components and functions. The CentralProcessing unit, Main memory, Bit, Byte, Word, Input/Output Devices,Speeds and memory Capacities in computer systems.

Softwareconcepts: Overview of Operating Systems, Types and Functions ofOperating System, application Software, Software for multi-tasking,multi-programming, Batch Processign Mode, Time sharing mode, Concept ofSystem Support Programme, Overview of Existing Software packages onWord Processing and Spreadsheets.

Overviewof an application Specific Programme: Flow charts, Basics of Algorithm,Fundamental of design and analysis of Algorithm; Basics of datastructure, Queue, Stack.

(b) Data Processing

Data processing:Digital Number System, Number conversions, Binary representation ofintegers, Binary representation of real numbers, Logical Data elementlike cjharacter, fields, records, files, Fundamentals of datatransmission and processing incluidng error contro and error processing.

Data base management:Data Resource management. Data base and file organisation andprocesing. (a) Direct, (b) Sequantial, (c) Indexed Sequential file.Concepts of Client Server architecture, Data Base Administrator. Anoverview of DBMS software.