|Course Archives Statistical Quality Control & Operations Research Unit|
Course: Statistics for Decision Making II
Time: Currently not offered
| Syllabus |
Syllabus: Introduction: Principles of Statistical Inference. Formulation of the problems with examples.
Estimation: Point estimation, Estimator and Estimate, Criteria for good estimates Unbiasedness, Consistency, Efficiency and Sufficiency, Illustrations. Methods of estimation of Parameters of standard distributions. Interval estimation by examples Confidence internals of the parameters of the standard distributions. Estimation using Statistical Software.
Testing hypothesis: Formulation of the problem and concepts for evaluation of tests, Illustrations. Statistic, Sampling distributions of statistic and its Standard Error. Large sample tests in one and two sample problems of standard probability distributions, Statement of central limit theorem, Determination of sample size. Simple linear regression and correlation and corresponding confidence intervals. Transformation of statistics to stabilize the residual plots. Assessment of the model. Fitting of nonlinear regression using transformation. Analysis of categorical data. Pearsonian chisquare and its applications. Test of hypothesis using Statistical Software.
Linear Statistical Models: Definition of linear model, interactions with illustrations. One way and two way analysis of variance. ANOVA using Statistical Software.
Nonparametric Inference: Comparison with parametric inference, Use of order statistics. Sign test, Wilcoxon signed rank test, Mann Whitney test, Run test, Kolmogorov Smirnov test. Spearmans and Kendalls test.
Usage of statistical software
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[Indian Statistical Institute]