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Statistics Optional Syllabus

Here is the official UPSC Statistics Optional syllabus for Paper I and Paper II, arranged paper by paper and unit by unit. Under each unit we give the official text first, then break it into numbered topics, so you can track your preparation and match every previous year question to its topic.

Source. UPSC Civil Services Examination 2026 notification (Examination Notice No. 05/2026-CSE, dated 04.02.2026, pp. 149–152), upsc.gov.in. The Statistics syllabus has been unchanged in recent years.

Scheme. Two papers of 250 marks each (total 500), 3 hours each. Each paper has two sections (A and B) of four questions each; Questions 1 and 5 are compulsory, and three more are attempted with at least one from each section. The syllabus itself is not divided into sections. Paper I has four units (Probability; Statistical Inference; Linear Inference and Multivariate Analysis; Sampling Theory and Design of Experiments); Paper II has four units (Industrial Statistics; Optimization Techniques; Quantitative Economics and Official Statistics; Demography and Psychometry).

Syllabus at a glance

PaperUnitTopics
Paper I1. Probability6
Paper I2. Statistical Inference8
Paper I3. Linear Inference and Multivariate Analysis7
Paper I4. Sampling Theory and Design of Experiments10
Paper II1. Industrial Statistics4
Paper II2. Optimization Techniques9
Paper II3. Quantitative Economics and Official Statistics5
Paper II4. Demography and Psychometry5

Paper I

1. Probability

Official syllabus text

Sample space and events, probability measure and probability space, random variable as a measurable function, distribution function of a random variable, discrete and continuous-type random variable, probability mass function, probability density function, vector-valued random variable, marginal and conditional distributions, stochastic independence of events and of random variables, expectation and moments of a random variable, conditional expectation, convergence of a sequence of random variable in distribution, in probability, in path mean and almost everywhere, their criteria and inter-relations, Chebyshev’s inequality and Khintchine’s weak law of large numbers, strong law of large numbers and Kolmogoroff’s theorems, probability generating function, moment generating function, characteristic function, inversion theorem, Lindeberg and Levy forms of central limit theorem, standard discrete and continuous probability distributions.

1.1 Probability spaces and random variables

  • Sample space, events, probability measure
  • Random variable, distribution function
  • pmf and pdf
  • Vector-valued random variables, marginal and conditional distributions
  • Stochastic independence

1.2 Expectation and moments

  • Expectation and moments
  • Conditional expectation

1.3 Convergence and laws of large numbers

  • Convergence in distribution, probability, mean and almost everywhere
  • Chebyshev’s inequality
  • Weak and strong laws of large numbers
  • Kolmogoroff’s theorems

1.4 Generating and characteristic functions

  • Probability generating function
  • Moment generating function
  • Characteristic function
  • Inversion theorem

1.5 Central limit theorem

  • Lindeberg and Levy forms

1.6 Standard distributions

  • Discrete distributions
  • Continuous distributions

2. Statistical Inference

Official syllabus text

Consistency, unbiasedness, efficiency, sufficiency, completeness, ancillary statistics, factorization theorem, exponential family of distribution and its properties, uniformly minimum variance unbiased (UMVU) estimation, Rao-Blackwell and Lehmann-Scheffe theorems, Cramer-Rao inequality for single parameter. Estimation by methods of moments, maximum likelihood, least squares, minimum chi-square and modified minimum chi-square, properties of maximum likelihood and other estimators, asymptotic efficiency, prior and posterior distributions, loss function, risk function, and minimax estimator. Bayes estimators.

Non-randomised and randomised tests, critical function, MP tests, Neyman-Pearson lemma, UMP tests, monotone likelihood ratio, similar and unbiased tests, UMPU tests for single parameter, likelihood ratio test and its asymptotic distribution. Confidence bounds and its relation with tests.

Kolmogorov’s test for goodness of fit and its consistency, sign test and its optimality. Wilcoxon signed-ranks test and its consistency, Kolmogorov-Smirnov two sample test, run test, Wilcoxon-Mann-Whitney test and median test, their consistency and asymptotic normality.

Wald’s SPRT and its properties, OC and ASN functions for tests regarding parameters for Bernoulli, Poisson, normal and exponential distributions. Wald’s fundamental identity.

2.1 Properties of estimators

  • Consistency, unbiasedness, efficiency
  • Sufficiency, completeness, ancillarity
  • Factorization theorem
  • Exponential family

2.2 UMVU estimation

  • Rao-Blackwell and Lehmann-Scheffe theorems
  • Cramer-Rao inequality

2.3 Methods of estimation

  • Moments
  • Maximum likelihood and its properties
  • Least squares
  • Minimum chi-square
  • Asymptotic efficiency

2.4 Bayes and minimax estimation

  • Prior and posterior distributions
  • Loss and risk functions
  • Minimax and Bayes estimators

2.5 Testing of hypotheses

  • Randomised tests, critical function
  • MP tests and Neyman-Pearson lemma
  • UMP tests and monotone likelihood ratio
  • Similar and unbiased tests, UMPU tests

2.6 Likelihood ratio tests and confidence bounds

  • Likelihood ratio test and its asymptotic distribution
  • Confidence bounds and relation with tests

2.7 Non-parametric tests

  • Kolmogorov goodness of fit
  • Sign test
  • Wilcoxon signed-ranks test
  • Kolmogorov-Smirnov two-sample test
  • Run test
  • Wilcoxon-Mann-Whitney and median tests

2.8 Sequential analysis

  • Wald’s SPRT
  • OC and ASN functions
  • Wald’s fundamental identity

3. Linear Inference and Multivariate Analysis

Official syllabus text

Linear statistical models, theory of least squares and analysis of variance, Gauss-Markoff theory, normal equations, least squares estimates and their precision, test of significance and interval estimates based on least squares theory in one-way, two-way and three-way classified data, regression analysis, linear regression, curvilinear regression and orthogonal polynomials, multiple regression, multiple and partial correlations, estimation of variance and covariance components, multivariate normal distribution, Mahalanobis’s D² and Hotelling’s T² statistics and their applications and properties, discriminant analysis, canonical correlations, principal component analysis.

3.1 Linear models and least squares

  • Linear statistical models
  • Gauss-Markoff theory
  • Normal equations
  • Least squares estimates and their precision

3.2 Analysis of variance

  • Tests and interval estimates in one-way, two-way and three-way classified data
  • Variance and covariance components

3.3 Regression analysis

  • Linear and curvilinear regression
  • Orthogonal polynomials
  • Multiple regression

3.4 Multiple and partial correlation

3.5 Multivariate normal distribution

3.6 Mahalanobis’s D² and Hotelling’s T²

3.7 Multivariate methods

  • Discriminant analysis
  • Canonical correlations
  • Principal component analysis

4. Sampling Theory and Design of Experiments

Official syllabus text

An outline of fixed-population and super-population approaches, distinctive features of finite population sampling, probability sampling designs, simple random sampling with and without replacement, stratified random sampling, systematic sampling and its efficacy, cluster sampling, two-stage and multi-stage sampling, ratio and regression methods of estimation involving one or more auxiliary variables, two-phase sampling, probability proportional to size sampling with and without replacement, the Hansen-Hurwitz and the Horvitz-Thompson estimators, non-negative variance estimation with reference to the Horvitz-Thompson estimator, non-sampling errors.

Fixed effects model (two-way classification) random and mixed effects models (two-way classification with equal observation per cell), CRD, RBD, LSD and their analyses, incomplete block designs, concepts of orthogonality and balance, BIBD, missing plot technique, factorial experiments and 2⁴ and 3², confounding in factorial experiments, split-plot and simple lattice designs, transformation of data, Duncan’s multiple range test.

4.1 Basics of sampling and simple random sampling

  • Fixed-population and super-population approaches
  • Finite population sampling
  • Probability sampling designs
  • SRS with and without replacement

4.2 Stratified and systematic sampling

  • Stratified random sampling
  • Systematic sampling

4.3 Cluster and multi-stage sampling

  • Cluster sampling
  • Two-stage and multi-stage sampling

4.4 Ratio and regression estimation; Two-phase sampling

  • Ratio estimators
  • Regression estimators
  • Two-phase sampling

4.5 PPS sampling

  • PPS with and without replacement
  • Hansen-Hurwitz estimator
  • Horvitz-Thompson estimator and its variance estimation

4.6 Non-sampling errors

4.7 Fixed, random and mixed effects models

4.8 Basic designs

  • CRD, RBD, LSD
  • Missing plot technique
  • Transformation of data
  • Duncan’s multiple range test

4.9 Incomplete block designs

  • Orthogonality and balance
  • BIBD
  • Simple lattice designs

4.10 Factorial experiments

  • 2ⁿ and 3² factorials
  • Confounding
  • Split-plot designs
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Paper II

1. Industrial Statistics

Official syllabus text

Process and product control, general theory of control charts, different types of control charts for variables and attributes, X̄, R, s, p, np and c charts, cumulative sum chart. Single, double, multiple and sequential sampling plans for attributes, OC, ASN, AOQ and ATI curves, concepts of producer’s and consumer’s risks, AQL, LTPD and AOQL, Sampling plans for variables, Use of Dodge-Romig tables.

Concept of reliability, failure rate and reliability functions, reliability of series and parallel systems and other simple configurations, renewal density and renewal function, Failure models: exponential, Weibull, normal, lognormal. Problems in life testing, censored and truncated experiments for exponential models.

1.1 Control charts

  • General theory
  • Charts for variables (X̄, R, s)
  • Charts for attributes (p, np, c)
  • Cumulative sum chart

1.2 Acceptance sampling

  • Single, double, multiple and sequential plans
  • OC, ASN, AOQ and ATI curves
  • Producer’s and consumer’s risks, AQL, LTPD, AOQL
  • Sampling plans for variables
  • Dodge-Romig tables

1.3 Reliability

  • Failure rate and reliability functions
  • Series and parallel systems
  • Renewal density and renewal function

1.4 Failure models and life testing

  • Exponential, Weibull, normal, lognormal models
  • Censored and truncated experiments

2. Optimization Techniques

Official syllabus text

Different types of models in Operations Research, their construction and general methods of solution, simulation and Monte-Carlo methods, formulation of Linear Programming (LP) problem, simple LP model and its graphical solution, the simplex procedure, the two-phase method and the M-technique with artificial variables, the duality theory of LP and its economic interpretation, sensitivity analysis, transportation and assignment problems, rectangular games, two-person zero-sum games, methods of solution (graphical and algebraic).

Replacement of failing or deteriorating items, group and individual replacement policies, concept of scientific inventory management and analytical structure of inventory problems, simple models with deterministic and stochastic demand with and without lead time, storage models with particular reference to dam type.

Homogeneous discrete-time Markov chains, transition probability matrix, classification of states and ergodic theorems, homogeneous continuous-time Markov chains, Poisson process, elements of queuing theory, M/M/1, M/M/K, G/M/1 and M/G/1 queues.

Solution of statistical problems on computers using well-known statistical software packages like SPSS.

2.1 OR models and simulation

  • Types of OR models
  • Simulation and Monte-Carlo methods

2.2 Linear programming

  • Formulation and graphical solution
  • Simplex, two-phase and M-technique
  • Duality
  • Sensitivity analysis

2.3 Transportation and assignment problems

2.4 Game theory

  • Rectangular games
  • Two-person zero-sum games
  • Graphical and algebraic solution

2.5 Replacement problems

  • Failing and deteriorating items
  • Group and individual replacement

2.6 Inventory and storage models

  • Deterministic and stochastic demand
  • Lead time
  • Dam-type storage models

2.7 Markov chains and Poisson process

  • Discrete-time chains, transition matrices, classification of states, ergodic theorems
  • Continuous-time chains
  • Poisson process

2.8 Queueing theory

  • M/M/1, M/M/K, G/M/1, M/G/1

2.9 Statistical software

  • Solving statistical problems with packages such as SPSS

3. Quantitative Economics and Official Statistics

Official syllabus text

Determination of trend, seasonal and cyclical components, Box-Jenkins method, tests for stationary series, ARIMA models and determination of orders of autoregressive and moving average components, forecasting.

Commonly used index numbers – Laspeyre’s, Paasche’s and Fisher’s ideal index numbers, chain-base index number, uses and limitations of index numbers, index number of wholesale prices, consumer price, agricultural production and industrial production, test for index numbers – proportionality, time-reversal, factor-reversal and circular.

General linear model, ordinary least square and generalized least squares methods of estimation, problem of multi-collinearity, consequences and solutions of multi-collinearity, autocorrelation and its consequences, heteroscedasticity of disturbances and its testing, test for independence of disturbances, concept of structure and model for simultaneous equations, problem of identification – rank and order conditions of identifiability, two-stage least square method of estimation.

Present official statistical system in India relating to population, agriculture, industrial production, trade and prices, methods of collection of official statistics, their reliability and limitations, principal publications containing such statistics, various official agencies responsible for data collection and their main functions.

3.1 Time series

  • Trend, seasonal and cyclical components
  • Box-Jenkins method
  • Stationarity tests
  • ARIMA models
  • Forecasting

3.2 Index numbers

  • Laspeyre’s, Paasche’s and Fisher’s indices
  • Chain-base index
  • WPI, CPI, agricultural and industrial production indices
  • Tests for index numbers

3.3 General linear model and its problems

  • OLS and GLS
  • Multicollinearity
  • Autocorrelation
  • Heteroscedasticity

3.4 Simultaneous equations

  • Structure and model
  • Identification: rank and order conditions
  • Two-stage least squares

3.5 Official statistics in India

  • Population, agriculture, industry, trade and prices
  • Methods of collection
  • Publications
  • Official agencies

4. Demography and Psychometry

Official syllabus text

Demographic data from census, registration, NSS other surveys, their limitations and uses, definition, construction and uses of vital rates and ratios, measures of fertility, reproduction rates, morbidity rate, standardized death rate, complete and abridged life tables, construction of life tables from vital statistics and census returns, uses of life tables, logistic and other population growth curves, fitting a logistic curve, population projection, stable population, quasi-stable population, techniques in estimation of demographic parameters, standard classification by cause of death, health surveys and use of hospital statistics.

Methods of standardisation of scales and tests, Z-scores, standard scores, T-scores, percentile scores, intelligence quotient and its measurement and uses, validity and reliability of test scores and its determination, use of factor analysis and path analysis in psychometry.

4.1 Demographic data and vital rates

  • Census, registration, NSS and other surveys
  • Vital rates and ratios
  • Morbidity
  • Standardized death rate
  • Cause-of-death classification
  • Health surveys and hospital statistics

4.2 Fertility and reproduction

  • Measures of fertility
  • Reproduction rates

4.3 Life tables

  • Complete and abridged life tables
  • Construction and uses

4.4 Population growth and projection

  • Logistic and other growth curves
  • Population projection
  • Stable and quasi-stable populations
  • Estimation of demographic parameters

4.5 Psychometry

  • Standardisation of scales and tests
  • Z-, standard, T- and percentile scores
  • Intelligence quotient
  • Validity and reliability
  • Factor and path analysis

Total: 54 numbered topics across 10 units.

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Last updated: 31 October 2026