This is the second course in the two-semester sequence of the first year undergraduate studies. The detailed course outlines are presented below: - Estimation and Confidence Intervals: Some properties of point estimators, some common unbiased point estimators, evaluating the goodness of a point estimator, confidence intervals, large sample confidence interval, selecting the sample size, small-sample confidence interval. - Properties of Point Estimators and Method of Estimation: Unbiasedness, relative efficiency, consistency, minimal sufficiency and best linear unbiased estimators (BLUE), the method of moments, the method of maximum likelihood. - Hypothesis Testing: Elements of a statistical test, common large-sample tests, calculation of type-I error, sample size for the Z-test, different ways of reporting the result of a test, attained significance levels or p-values, some comments on the theory of hypothesis testing, two-sample tests based on t-distributions, testing hypothesis concerning variances, power of tests, the Neyman-Pearson lemma. - Linear Models and Estimation by Least Squares: Linear regression and estimation by least squares method.
Estimation and Confidence Intervals Properties of point estimators and methods of estimation Hypothesis testing Linear models and estimation by least squares
Level:
Type:
Undergraduate
(A-)
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