Statistics Paper I 2024
79 questions, booklet ISS-2024-P1.
Section I · Objective (Q1–Q80) · Q1–80
Practise this section →- 1Distribution Theory — density of minimum order statisticDistribution TheoryStatistical MethodsEasy
- 2Distribution Theory — moment generating function of sample varianceDistribution TheoryStatistical MethodsMedium
- 3Distribution Theory — expectation of reciprocal sample varianceDistribution TheoryStatistical MethodsHard
- 4Distribution Theory — mean of a log-transformed uniform sumDistribution TheoryProbabilityEasy
- 5Distribution Theory — variance of a log-transformed uniform sumDistribution TheoryProbabilityEasy
- 6Distribution Theory — MGF of a log-transformed uniform sumDistribution TheoryProbabilityEasy
- 7Distribution Theory — distribution of a ratio of normal combinationsDistribution TheoryProbabilityHard
- 8Distribution Theory — expectation of reciprocal sum of squared normalsDistribution TheoryStatistical MethodsEasy
- 9Distribution Theory — expectation of a ratio of independent normal combinationsDistribution TheoryStatistical MethodsEasy
- 10Distribution Theory — calibrating a ratio to a standard Cauchy lawDistribution TheoryProbabilityHard
- 11Algebra — counting non-orthogonal line-pair quadraticsAlgebraLinear ModelsHard
- 12Distribution Theory — pdf of a linear combination of correlated normalsDistribution TheoryMultivariate AnalysisMedium
- 13Statistical Inference — asymptotic variance of the sample medianStatistical InferenceStatistical MethodsHard
- 14Distribution Theory — reciprocal chi-square ratios and the F-distributionDistribution TheoryProbabilityMedium
- 15Linear Models & Regression — identifying valid regression assignment from two linesLinear Models & RegressionOperations Research and ReliabilityMedium
- 16Distribution Theory — MGF of a chi-square variableDistribution TheoryStatistical MethodsEasy
- 17Distribution Theory — density of the maximum order statisticDistribution TheoryStatistical MethodsEasy
- 18Probability — variance of a scaled sum of independent variablesProbabilityProbabilityEasy
- 19Probability — squared scaled correlation from covariance dataProbabilityStatistical MethodsMedium
- 20Distribution Theory — evaluating the density of a minimum order statisticDistribution TheoryStatistical MethodsMedium
- 21Probability — geometric probability on a unit squareProbabilityProbabilityEasy
- 22Distribution Theory — distribution of the negative log of a uniform variateDistribution TheoryProbabilityEasy
- 23Distribution Theory — CF of a normalized combination of iid normalsDistribution TheoryProbabilityHard
- 24Distribution Theory — CF of a sign-normal productDistribution TheoryProbabilityMedium
- 25Distribution Theory — CF of a product of two standard normalsDistribution TheoryProbabilityMedium
- 26Distribution Theory — mean via a composed moment generating functionDistribution TheoryProbabilityHard
- 27Probability — net winnings under a stop-on-win strategyProbabilityProbabilityMedium
- 28Probability — probability of a negative net winningProbabilityProbabilityMedium
- 29Probability — probability of matching dice on a specific rollProbabilityProbabilityMedium
- 30Probability — expected number of rolls until a matchProbabilityProbabilityMedium
- 31Probability — deriving a union probability from conditional dataProbabilityProbabilityMedium
- 32Distribution Theory — checking normalization, a probability, and independenceDistribution TheoryProbabilityHard
- 33Distribution Theory — marginal and mean of a Poisson-Binomial mixtureDistribution TheoryProbabilityHard
- 34Distribution Theory — moments of a parity-based sign transformDistribution TheoryProbabilityMedium
- 35Distribution Theory — deriving a geometric marginal from a joint pmfDistribution TheoryProbabilityHard
- 36Distribution Theory — conditional and covariance properties in bivariate normalDistribution TheoryStatistical MethodsMedium
- 37Distribution Theory — probability from independent binomial-Poisson MGFsDistribution TheoryProbabilityHard
- 38Probability — Chebyshev bound for the sample mean of exponentialsProbabilityStatistical MethodsMedium
- 39Distribution Theory — pdf of a squared uniform variableDistribution TheoryProbabilityEasy
- 40Distribution Theory — reading off exponential moments from its MGFDistribution TheoryProbabilityEasy
- 41Computer Applications — functions of a program debuggerComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 42Computer Applications — core roles of an operating systemComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 43Computer Applications — identifying tasks performed by utility programsComputer Applications & Data ProcessingComputer application and Data ProcessingMedium
- 44Computer Applications — identifying the non-repudiation security serviceComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 45Computer Applications — TCP/IP layer hosting ICMP and ARPComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 46Computer Applications — computing an 8-bit 2's complement valueComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 47Computer Applications — distinguishing compiler and interpreter behaviourComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 48Computer Applications — properties of a webcam as an input deviceComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 49Computer Applications — identifying the main CPU operationsComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 50Computer Applications — port numbers for SMTP, POP3, and IMAPComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 51Computer Applications — identifying functions performed by the BIOSComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 52Computer Applications — naming IPSEC router-to-router communicationComputer Applications & Data ProcessingComputer application and Data ProcessingMedium
- 53Computer Applications — method for interprocess communication in distributed systemsComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 54Computer Applications — verifying a hex conversion and a decimal complementComputer Applications & Data ProcessingComputer application and Data ProcessingMedium
- 56Computer Applications — identifying hardware network connecting devicesComputer Applications & Data ProcessingComputer application and Data ProcessingMedium
- 57Computer Applications — core responsibilities of a DBMSComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 58Computer Applications — evaluating claims about pointing devicesComputer Applications & Data ProcessingComputer application and Data ProcessingMedium
- 59Computer Applications — distinguishing looping statements from jump statementsComputer Applications & Data ProcessingComputer application and Data ProcessingMedium
- 60Computer Applications — identifying the tree-structured data modelComputer Applications & Data ProcessingComputer application and Data ProcessingEasy
- 61Numerical Analysis — second Picard iterate for a nonlinear IVPNumerical AnalysisNumerical AnalysisHard
- 62Numerical Analysis — comparing orders of Euler and Runge-Kutta methodsNumerical AnalysisNumerical AnalysisMedium
- 63Numerical Analysis — error of Simpson's rule for a quartic integrandNumerical AnalysisNumerical AnalysisMedium
- 64Numerical Analysis — identifying Simpson-rule weights in an RK4 formulaNumerical AnalysisNumerical AnalysisMedium
- 65Numerical Analysis — composite trapezoidal rule for a quadratic functionNumerical AnalysisNumerical AnalysisMedium
- 66Numerical Analysis — converting a difference combination to function valuesNumerical AnalysisNumerical AnalysisMedium
- 67Numerical Analysis — converting a backward difference to a forward differenceNumerical AnalysisNumerical AnalysisMedium
- 68Numerical Analysis — selecting valid quadrature rules for 8 subintervalsNumerical AnalysisNumerical AnalysisMedium
- 69Numerical Analysis — back-solving for a function value from quadrature resultsNumerical AnalysisNumerical AnalysisMedium
- 70Numerical Analysis — behaviour of the third divided difference of a cubicNumerical AnalysisNumerical AnalysisMedium
- 71Numerical Analysis — second difference of an exponential sequenceNumerical AnalysisNumerical AnalysisMedium
- 72Numerical Analysis — applying a difference-shift operator combination to a cubicNumerical AnalysisNumerical AnalysisMedium
- 73Numerical Analysis — decomposing the central difference operatorNumerical AnalysisNumerical AnalysisMedium
- 74Numerical Analysis — selecting a step size for bounded interpolation errorNumerical AnalysisNumerical AnalysisHard
- 75Numerical Analysis — nature of the roots of a fitted quadraticNumerical AnalysisNumerical AnalysisHard
- 76Numerical Analysis — equivalence of Lagrange and Newton linear interpolation errorNumerical AnalysisNumerical AnalysisMedium
- 77Numerical Analysis — coefficients of a three-point quadrature ruleNumerical AnalysisNumerical AnalysisMedium
- 78Numerical Analysis — exactness of standard rules for a cubic polynomialNumerical AnalysisNumerical AnalysisMedium
- 79Numerical Analysis — river cross-section area by Simpson's ruleNumerical AnalysisNumerical AnalysisMedium
- 80Numerical Analysis — stability interval of forward Euler for a decay equationNumerical AnalysisNumerical AnalysisMedium