36 courses, in the order a learner meets them — descriptive statistics before probability, probability before distributions, distributions before inference. Every course stands on its own, so start with the one your exam needs. Where a topic has two courses, the Foundation course comes first and the Advanced course starts where it stops.
Mean, Median, Mode, Dispersion, Moments, Skewness, Kurtosis.
Foundation · 5 units + practicalCurve fitting, correlation, regression, attributes.
Advanced · 4 unitsMetric spaces, compactness and continuity; the Riemann–Stieltjes integral; bounded variation and integrals depending on a parameter; sequences and series of functions. Proved rather than asserted.
Advanced · 4 units + practicalVector spaces, Gram–Schmidt and generalized inverses; characteristic roots and spectral decomposition; quadratic forms; linear models, estimability, Gauss–Markov and Aitken.
Probability axioms, random variables, expectation, generating functions, CLT.
Advanced · 4 unitsMeasure-theoretic probability: sigma-fields, expectation as an integral, modes of convergence, characteristic functions, and the laws of large numbers and CLT proved.
Foundation · 5 units + practicalBernoulli, Binomial, Poisson, Negative Binomial, Geometric, Hyper-geometric.
Foundation · 5 units + practicalUniform, Exponential, Gamma, Beta, Normal, Sampling distributions (t, F, χ²).
Advanced · 4 units + practicalLognormal, Weibull, Pareto, Laplace and Cauchy; transformed, truncated, mixture and compound distributions; chi-square, t and F; quadratic forms and order statistics.
Estimation, hypothesis testing, large & small sample tests, non-parametric tests.
Advanced · 4 units + practicalUMVU estimation, the Cramér–Rao bound, Rao–Blackwell and Lehmann–Scheffé, maximum likelihood, jackknife and bootstrap, interval estimation, and Bayes and minimax rules.
Advanced · 4 unitsRandomized tests and the Neyman–Pearson lemma, UMP tests and Karlin–Rubin, the likelihood ratio test with Wald and score tests, and the SPRT.
SRS, stratified, systematic, cluster sampling; NSO & NSC.
Advanced · 4 units + practicalUnequal probability sampling (Hansen–Hurwitz, Lahiri, Horvitz–Thompson), the exact bias of ratio and regression estimators, cluster and two-stage sampling, randomized response and small area estimation.
Foundation · 5 units + practicalANOVA, CRD, RBD, LSD, missing values, efficiency.
Advanced · 4 units + practicalTwo-way ANOVA with several observations per cell, multiple comparisons, ANCOVA, factorials and Yates’s algorithm, confounding, split-plot and incomplete block designs.
Empirical economic analysis, OLS & Gauss–Markov, heteroscedasticity, multicollinearity, autocorrelation.
Advanced · 4 units + practicalThe multivariate normal, Wishart, Hotelling’s T² and Wilks’ Λ, discriminant analysis, principal components, canonical correlation, clustering and factor analysis.
Time series, index numbers, vital statistics, life tables.
Foundation · 5 units + practicalGrowth curves, index numbers, demand analysis, psychological & educational stats.
Foundation · 5 units + practicalControl charts (variables & attributes), acceptance sampling, single sampling plan.
Foundation · 5 units + practicalLPP, graphical & simplex methods, Big-M, Two-phase, duality.
Foundation · 5 units + practicalTransportation, assignment, sequencing, game theory, CPM/PERT.
Foundation · 5 units + practicalInsurance, premium calculation, life tables, life insurance, annuities.
Advanced · 5 units + practicalFuture lifetime, mortality laws, life insurance, annuities, premiums & reserves.
Foundation · 5 units + practicalPhases, sample size, parallel/cross-over designs, surrogate endpoints, meta-analysis.
Foundation · 5 units + practicalResearch types, surveys, data collection, questionnaire, report writing & project.
Excel functions, charts, descriptive stats, regression, hypothesis testing in Excel.
Advanced · PracticalThe prescribed analyses as SPSS procedure: Variable View settings, the syntax for each analysis, model selection, logistic regression and probit.
Foundation · 5 units + practicalR basics, descriptive stats, visualization, hypothesis testing, regression in R.
Foundation · 5 units + practicalComputer basics, Excel data processing & analysis, R programming, data frames, EDA & visualisation.
Advanced · PracticalOne data set end to end in R: measurement scales, pre-processing, transformations, diagrams, cross-validation and the confusion matrix.
Advanced · PracticalTwelve programs with no statistical package: summary measures, moments, random number generators, distributions fitted and tested, correlation, regression and tests.
Advanced · PracticalOne extract–transform–load pipeline end to end: five formats parsed, anomalies named, the re module, a normalised schema and its queries.
Price determination and market structures, national income and the national accounts, money and banking, public finance, international economics and the Indian economy.
Allied · 6 unitsConcepts and conventions, journal and ledger, subsidiary books, bank reconciliation, trial balance and final accounts, depreciation and incomplete records.
Statistics recruitment papers do not only ask about statistics: the APPSC papers put economics and financial accounting beside central tendency and index numbers, and the Indian Statistical Service asks for national income. The two allied courses are written to the syllabus lines that ask for them, and every exam map that needs them links here.
They carry no current figures, on purpose — no growth rate, repo rate or poverty headcount. Every rupee amount is derived in front of you or labelled as an illustration, the same rule the examinations section applies to marks and exam patterns. For current data, go to the source that publishes it.