Statistics Paper II 2023
79 questions, booklet ISS-2023-P2.
Section I · Objective (Q1–Q80) · Q1–80
Practise this section →- 1Statistical Inference — unbiased estimator of circle areaStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 2Statistical Inference — method of moments for a mixtureStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 3Statistical Inference — consistency of method of momentsStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 4Statistical Inference — MLE consistency for a pathological p(theta)Statistical InferenceStatistical Inference and Hypothesis TestingHard
- 5Statistical Inference — MLE for shifted exponential, boundaryStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 6Statistical Inference — UMVUE for a Bernoulli functionStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 7Statistical Inference — correlation of UMVUE with an unbiased estimatorStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 8Statistical Inference — sufficiency and MLE for uniform locationStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 9Statistical Inference — MLE with a discrete parameter spaceStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 10Statistical Inference — CRLB for a log-scale parameterStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 11Statistical Inference — unbiased quadratic estimator for uniformStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 12Statistical Inference — pivotal statistic for exponential meanStatistical InferenceStatistical Inference and Hypothesis TestingEasy
- 13Computer Applications — counting distinct bootstrap samplesComputer Applications & Data ProcessingStatistical Inference and Hypothesis TestingMedium
- 14Statistical Inference — identifying MLR familiesStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 15Statistical Inference — simple versus composite hypothesesStatistical InferenceStatistical Inference and Hypothesis TestingEasy
- 16Statistical Inference — non-unique MLE casesStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 17Statistical Inference — UMP test critical regionStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 18Statistical Inference — invariance and asymptotic normality of MLEStatistical InferenceStatistical MethodsMedium
- 19Non-parametric Inference — mean and variance of runsNon-parametric InferenceStatistical MethodsMedium
- 20Statistical Inference — sufficiency of the sample minimumStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 21Statistical Inference — unbiased estimator of normal sigmaStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 22Statistical Inference — joint sufficiency for normal mean and sdStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 23Statistical Inference — estimating the Cauchy location parameterStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 24Statistical Inference — MVUE of a Poisson probabilityStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 25Statistical Inference — Neyman-Pearson best critical regionStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 26Statistical Inference — locally most powerful testStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 27Statistical Inference — MSE of a variance-type estimatorStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 28Statistical Inference — sufficient statistic for N(theta,theta^2)Statistical InferenceStatistical Inference and Hypothesis TestingMedium
- 29Statistical Inference — LRT and Neyman-Pearson equivalenceStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 30Statistical Inference — OC function of SPRT at H0Statistical InferenceStatistical Inference and Hypothesis TestingMedium
- 31Statistical Inference — size of a test, parametric pmfStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 32Statistical Inference — power and unbiasedness of a testStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 33Statistical Inference — Fisher information via second derivativeStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 35Statistical Inference — expectation of a mixture distributionStatistical InferenceProbabilityMedium
- 36Statistical Inference — method of moments estimate from dataStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 37Statistical Inference — size of a randomized testStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 38Statistical Inference — power of a randomized testStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 39Statistical Inference — size of a randomized test from a tableStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 40Statistical Inference — power of a randomized test from a tableStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 41Statistical Inference — sufficiency of partitioned Poisson statisticsStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 42Statistical Inference — sufficiency of grouped-sum Poisson statisticsStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 43Statistical Inference — properties of a single observation from N(0,theta)Statistical InferenceStatistical Inference and Hypothesis TestingHard
- 44Statistical Inference — completeness and sufficiency of x1 squaredStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 45Statistical Inference — UMPU two-sided critical constantsStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 46Statistical Inference — computing a one-sided t-statisticStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 47Statistical Inference — confidence coefficient for a shifted exponential thresholdStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 48Statistical Inference — MVB estimators, likelihood equation and CauchyStatistical InferenceStatistical Inference and Hypothesis TestingHard
- 49Statistical Inference — sufficient statistics versus the MLEStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 50Statistical Inference — UMP-coincidence and consistency of LRTStatistical InferenceStatistical Inference and Hypothesis TestingMedium
- 51Multivariate Analysis — noncentral chi-square from a normal vectorMultivariate AnalysisMultivariate AnalysisMedium
- 52Design of Experiments — mean sum of squares due to errorDesign of ExperimentsLinear ModelsMedium
- 53Multivariate Analysis — variance of a quadratic form in normal variatesMultivariate AnalysisMultivariate AnalysisHard
- 54Multivariate Analysis — chi-square distribution via an idempotent formMultivariate AnalysisLinear ModelsHard
- 55Multivariate Analysis — independence condition for quadratic formsMultivariate AnalysisLinear ModelsMedium
- 56Linear Models — BLUE of theta1 from combined sumsLinear Models & RegressionLinear ModelsHard
- 57Linear Models — BLUE of theta2 from combined sumsLinear Models & RegressionLinear ModelsHard
- 58Linear Models — variance of the regression interceptLinear Models & RegressionStatistical MethodsEasy
- 59Linear Models — covariance of the regression coefficient estimatorsLinear Models & RegressionStatistical MethodsMedium
- 60Linear Models — variance of the regression slopeLinear Models & RegressionStatistical MethodsEasy
- 61Design of Experiments — error df for two-way classificationDesign of ExperimentsLinear ModelsEasy
- 62Linear Algebra — order of a generalized inverseLinear AlgebraLinear ModelsEasy
- 63Linear Algebra — symmetric generalized inverses of a symmetric matrixLinear AlgebraLinear ModelsMedium
- 64Linear Algebra — rank and transpose properties of a g-inverseLinear AlgebraLinear ModelsMedium
- 65Design of Experiments — reconstructing an ANOVA tableDesign of ExperimentsStatistical Inference and Hypothesis TestingMedium
- 66Official Statistics — identifying a non-fundamental-principleOfficial StatisticsOfficial StatisticsEasy
- 67Official Statistics — Census Act provisions on periodicityOfficial StatisticsOfficial StatisticsMedium
- 68Official Statistics — legislative list classification of health subjectsOfficial StatisticsOfficial StatisticsMedium
- 69Official Statistics — agencies generating labour force dataOfficial StatisticsOfficial StatisticsMedium
- 70Official Statistics — government-published index numbersIndex Numbers & Time SeriesOfficial StatisticsMedium
- 71Official Statistics — scope and exclusions of GDPOfficial StatisticsOfficial StatisticsMedium
- 72Index Numbers — weights in the Marshall-Edgeworth formulaIndex Numbers & Time SeriesApplied StatisticsEasy
- 73Official Statistics — matching NSSO functions to divisionsOfficial StatisticsOfficial StatisticsHard
- 74Official Statistics — agency conducting the PLFSOfficial StatisticsOfficial StatisticsEasy
- 75Official Statistics — tables covered in the Census of IndiaOfficial StatisticsOfficial StatisticsMedium
- 76Official Statistics — identifying international statistical organizationsOfficial StatisticsOfficial StatisticsMedium
- 77Official Statistics — structure of the Global Hunger IndexOfficial StatisticsOfficial StatisticsEasy
- 78Official Statistics — constitutional basis for conducting the censusOfficial StatisticsOfficial StatisticsMedium
- 79Official Statistics — identifying monthly high frequency indicatorsOfficial StatisticsOfficial StatisticsMedium
- 80Official Statistics — goods and services excluded from GDPOfficial StatisticsOfficial StatisticsEasy