Criteria of a good estimator, unbiasedness, consistency, efficiency, sufficiency, Rao-Cramer inequality, Rao-Blackwell theorem, Point estimation using maximum likelihood method, method of moments, etc. Interval estimation using large sample method, pivotal method, etc. Point and interval estimators of the parameters of commonly used probability distributions, population mean, variance, proportion, etc. Confidence intervals for the difference between two population means, difference between two population proportions and ratio of two population variances. Estimation of sample size. Basic concepts and properties of tests of hypothesis, different types of hypothesis, type I and type II errors, Critical region, Size and power of a test, Neyman Pearson lemma, Tests of hypothesis concerning a population mean, proportion and variance. Tests comparing two population means, proportions, and variances. Chi-square tests, multinomial experiments, contingency tables, goodness of fit tests. Predictions about the populations based on samples. Likelihood ratio tests. Computer implementations using appropriate statistical software and calculators.
Contact hours:
Four lectures/tutorials and one computer lab per week.Assessment:
Two tests (25%), approximately four assignments (15%) and final exam (60%).Prerequisite: 1.30811
Text:
Rohatgi, V. K., 1984, Statistical Inference, John Wiley, New York