On successful completion of this Course, students will be able to: Distinguish the concept of unbiased point estimators, confidence interval, relative efficiency, consistency, sufficiency, elements of a statistical test, relationships between hypothesis-testing procedures and confidence intervals, properties of the least-squares, elements affecting the information in a sample, and analysis of variance procedures; Apply bias and mean square error of point estimators, unbiased point estimators, goodness of a point estimator, Rao–Blackwell theorem and minimum-variance unbiased estimator, estimator of moment and maximum likelihood method, type II error probabilities and sample size for Z tests, power of tests and the Neyman–Pearson lemma, and likelihood ratio tests; Infer concerning linear function of the model parameters, designing experiment and the relationship with accuracy, matched-pairs experiment, and comparison of more than two means for analysis of variance for a one-way layout.
- Properties of Point Estimators and Methods of Estimation;
- Hypothesis Testing;
- Linear Models and Estimation by Least Squares;
- Consideration in Designing Experiments;
- The Analysis of Variance
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