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ISS stand for Indian Statistical Service is the combined competitive examination which conducted by UPSC for recruitment to Grade IV officers of the services of Indian Economic and Indian Statistic.
ISS exam consists two parts; part I and part II, Part I is written exam and Part II is Viva- Voce. ISS written exam contains maximum marks 1000. Statistics I & II are of Objective Type Questions (80 questions with maximum marks of 200 in each paper) to be attempted in 120 minutes. Statistics III & IV are of Descriptive Type having Short Answer/Small Problems Questions (50%) and Long Answer and Comprehension problem questions (50%).
A students for the Indian Statistical Service should have obtained a Bachelor's Degree with Statistics/Mathematical Statistics/Applied Statistic as one of the subject or a Master's degree in Statistics/Mathematical Statistics/Applied Statistic from a University incorporated by an Act of the Central or State Legislature in India or other Educational Institutes established by an Act of Parliament or declared to be deemed as University under Section 3 of the University Grants Commission Act, 1956 or a Foreign University approved by the Central Government from time to time
Aspirants for the Indian Economic Service must have obtained a Post-Graduate Degree in Economics/Applied Economics/Business Economics/Econometrics from a University incorporated by of an Act of the Central or State Legislature in India or other Educational Institutes.Age limit:
Students could be required to jot down an essay in English. Other query may be designed to test their expertise of English and workmanlike use of words. Passages will usually be set for summary.General studies:
General expertise together with know-how of modern-day events and of such matters of every day statement in their medical aspects as can be anticipated of an educated man or woman who has not made a unique examine of any scientific challenge. The paper can even encompass query of Indian polity including the political gadget and the constitution of India, records of India and geography of a nature which the candidate must be capable of solution without unique look at.
Elements of measure theory, Classical definitions and axiomatic approach, Sample space, Class of events and Probability measure Probability of m events out of n. Conditional in probability, Laws of large numbers and central limit theorems for independent variables, Conditional expectation and Martingales.Statistic Methods-
(a) Frequency distribution, Measures of location, dispersion, and kurtosis. Curve fitting and orthogonal polynomials of the correlation coefficient, compilation and presentation of data, Charts, diagrams and histogram.
(b) Rank order statistics-minimum, maximum, range and median, Non-parametric tests-Goodness of fit, sign, median, run, Concept of Asymptotic relative efficiencyNumerical Analysis-
Interpolation formulae (with remainder terms) due to Lagrange, Newton-Gregory, Newton Divided different, , Inverse interpolation Numerical integration and differentiation Difference equations of the first order, Linear difference equations with constant coefficients
Theory of linear estimation, Gauss-Mark off setup, Least square estimators, Use of g-inverse, analysis of one-way and two way classified data-fixed, mixed and random effect models.Estimation-
Characteristics of good estimator, Estimation methods of maximum likelihood, minimum chi-square, moments and least squares optimal properties of maximum likelihood estimators, Complete statistics, Confidence interval estimation Optimum confidence bounds.Hypotheses testing and statistical quality control-
(a) Hypotheses testing - Power function, Most powerful and uniformly most powerful tests, Simple and composite hypothesis. Different types of critical regions and similar regions.
(b)Statistical quality control: Control Charts for variable and attributes. Acceptance Sampling by attributes-Single, double, multiple and sequential Sampling plans; Concepts of AOQL and ATI; Acceptance Sampling by variables-use of Dodge-Romig and other tables
Simple random sampling with and without replacement, Stratified sampling and sample allocation, Ratio and Regression methods of estimation, Sampling with probability proportional to size etcDesign and Analysis of Experiments-
Construction and analysis of balanced and partially balanced incomplete block designs, Layout and analysis of completely Factorial experiments and confounding in 2n and 3n experiments, Analysis of covariance etc>/p> Economic Statistics-
Autoregressive models of first and second order. Concentration curve, Methods of estimating national income, Components of time series, Methods of their determination difference method, Inter-industry tableEconomic-
Multi-co linearity, errors in variable model, Simultaneous equation models-Identification, rank and other conditions. Indirect least squares and two stage least squares, Short-term economic forecasting etc.
Random walk and Gambler's ruin problem. Poisson process, Birth and death process; applications to Queues-M/M/I and M/M/C models, Branching Process etcOperations Research-
Elements of linear programming, Simple procedure, Principle of duality, Transport and assignment problems, Single and multi-period inventory control models, ABC analysis, General simulation problems etc.Computer Application and Data Processing-
(A) Computer Application-Computer System Concepts-
The Central Processing unit, Main memory, Bit, Byte, Word, Input/output Devices, Computer system components and functions, Speeds and memory Capacities in computer systems etcSoftware concepts-
Overview of Operating Systems, Types and Functions of Operating System, application Software, Software for multi-tasking, Concept of System Support Programme, Overview of Existing Software packages on Word Processing and Spreadsheets.Overview of An Application Specific Programme- Flow charts, Basics of Algorithm, Fundamental of design and analysis of Algorithm; Basics of data structure, Queue, Stack Data Processing- Digital Number System, Number conversions, Binary representation of integers, records, files, Fundamentals of data transmission and processing including error control and error processing. Data Base Management-
Data Resource management, Data base and file organization and processing.(a) Direct, (b) Sequential, (c) Indexed Sequential file. Concepts of Client Server architecture, Data Base Administrator, An overview of DBMS software
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