COURSE NUMBER AND TITLE: MATH 4252 Probability and Statistics II

CREDIT HOURS: 3

CATALOG DESCRIPTION: A study of game theory and decision criteria, point and interval estimation, theory and applications of hypothesis testing, non-parametric tests, regression and correlation, analysis of variance and a general introduction to experimental design.

PREREQUISITE(S): MATH 4251 (grade of C or better)

SUGGESTED TEXT(S): Probability and Statistics, by Degroot and Schervish, Third Edition, Addison Wesley, 2002.

COURSE OUTLINE:

• Sampling Distributions of Estimators – Chi-square and t-distributions, joint distribution of mean and variance, confidence intervals for mean, proportion and variance from one and two populations.
• Testing of Hypothesis – F-distribution, Testing of hypotheses about one and two population parameters.
• Categorical Data – Contingency tables, test of homogeneity and independence, test of goodness- of- fit for Binomial, Poisson, Normal, Exponential and Multinomial distributions.
• Nonparametric Methods - Sign test for matched-pair samples, signed-rank test, rank-sum test, Kruskal-Wallis test, Friedman test and Spearman rank correlation.
• Linear Statistical Models – One-way analysis of variance, two-way analysis of variance with and without interaction effect, simple and multiple linear regression models, Model Diagnostics, exponential and power regression models.