Statistics II (Applied Statistics for Business and Economics)

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.

Objectives

Prerequisites

Syllabus

Estimation and Confidence Intervals Properties of point estimators and methods of estimation Hypothesis testing Linear models and estimation by least squares