Indian Economic Service/ Indian Statistical Service Examination, 2012-STATISTICS-II Syllabus

STATISTICS-II

1. Linear Models

Theory of linear estimation. Gauss-Markoff setup. Least square estimators. Use of g-inverse. analysis of one-way and two way classified data-fixed, mixed and random effect models. Tests for regression coefficients.

2. Estimation

Characteristics of good estimator. Estimation methods of maximum likelihood, minimum chisquare, moments and least squares. Optimal properties of maximum likelihood estimators. Minimum variance unbiased estimators. Minimum variance bound estimators. Cramer-Rao inequality. Bhattacharya bounds. Sufficient estimator. factorisation theorem. Complete statistics. Rao-Blackwell theorem. Confidence interval estimation. Optimum confidence bounds. Resampling,

Bootstrap and Jacknife.

3. Hypotheses testing and Statistical Quality Control

(a) Hypothesis testing: Simple and composite hypothesis. Two kinds of error. Critical region. Different types of critical regions and similar regions. Power function. Most powerful and uniformly most powerful tests. Neyman-Pearson fundamental lemma. Unbiased test. Randomised test. Likelihood ratio test. Wald’s SPRT, OC and ASN functions. Elements of decision and game theory.

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.

4. Multivariate Analysis

Multivariate normal distribution. Estimation of mean Vector and covariance matrix. Distribution of Hotelling’s T2-statistic, Mahalanobis’s D2-statistic, and their use in testing. Partial and multiple correlation coefficients in samples from a multivariate normal population. Wishart’s distribution, its reproductive and other properties. Wilk’s criterion. Discriminant function. Principal components. Canonical variates and correlations.