STATISTICS (STAT)

All STAT/MATH/OPRS courses offered by the Department of Mathematics and Statistics are approved to satisfy requirements for the Problem Solving (P) Goal of UNC Charlotte Education.

STAT 1220. Elements of Statistics I (BUSN). (3) Prerequisite: MATH 1100 or placement by the Department. Non-calculus based introduction to data summarization, discrete and continuous random variables (e.g., binomial, normal), sampling, central limit theorem, estimation, testing hypotheses, and linear regression. Applications of theory will be drawn from areas related to business. May not be taken for credit if credit has been received for STAT 1221 or 1222. (Fall, Spring, Summer) (Evenings)

STAT 1221. Elements of Statistics I. (3) Prerequisite: MATH 1100 or placement by the Department. Same topics as STAT 1220 with special emphasis on applications to the life sciences. May not be taken for credit if credit has been received for STAT 1220 or 1222. (Fall, Spring)

STAT 1222. Introduction to Statistics. (3) Prerequisite: MATH 1100 or placement by the Department. Same topics as STAT 1220 with special emphasis on applications to the social and behavioral sciences. May not be taken for credit if credit has been received for STAT 1220 or 1221. (Fall, Spring, Summer) (Evenings)

STAT 2122. Introduction to Probability and Statistics. (3) Prerequisite: MATH 1242 or permission of the department. A study of probability models, discrete and continuous random variables, inference about Bernoulli probability, inference about population mean, inference about population variance, the maximum likelihood principle, the minimax principle, Bayes procedures, and linear models. (Fall, Spring, Summer) (Evenings)

STAT 2223. Elements of Statistics II. (3) Prerequisite: Either STAT 1220, STAT 1221, STAT 1222, STAT 2122 or permission of the department. Topics include contingency analysis, design of experiments, more on simple linear regression, and multiple regression. Computers will be used to solve some of the problems. (Fall)

STAT 3110. Applied Regression. (3) (W) Prerequisite: STAT 2122 or permission of the department. Ordinary regression models, logistic regression models, Poisson regression models. (Spring)

STAT 3122. Probability and Statistics I. (3) Crosslisted as MATH 3122. (Fall) (Evenings)

STAT 3123. Probability and Statistics II. (3) Crosslisted as MATH 3123. (Spring) (Evenings)

STAT 3126. Applied Statistical Methods. (3) Prerequisites: MATH 3123 or permission of the department. Regression analysis, time series analysis, and forecasting. Survival models and their estimation. (On demand)

STAT 3128. Probability and Statistics for Engineers. (3) Prerequisite: MATH 2241. An introduction to: probability theory; discrete and continuous random variables and their probability distributions; joint probability distributions; functions of random variables and their probability distributions; descriptive statistics; point and interval estimation; one and two sample hypothesis testing; quality control; one and two factor ANOVA; and regression. Credit will not be given for both STAT 3128 and any of these courses: STAT 2122, MATH 3125, MATH/STAT 3122/3123.

STAT 3140. Design of Experiments. (3) Prerequisite: STAT 2122 or permission of the department. Randomization and blocking with paired comparisons, Significance tests and confidence intervals, experiments to compare k treatment means, randomized blocks and two-way factorial designs, designs with more than one blocking variable, empirical modeling, factorial designs at two levels. (Fall) (Alternate years)

STAT 3150. Time Series Analysis. (3) Prerequisites: STAT 2223 or permission of the department. Stationary time series models, ARMA processes, modeling and forecasting with ARMA processes, ARIMA models for nonstationary time series models, spectral densities. (Spring) (Alternate years)

STAT 3160. Applied Multivariate Analysis. (3) Prerequisite: STAT 2223 or permission of the department. Introduction to the fundamental ideas in multivariate analysis using case studies. Descriptive, exploratory, and graphical techniques; introduction to cluster analysis, principal components, factor analysis, discriminant analysis, Hotelling T2 and other methods. (Fall)

STAT 4116. Statistical Computing. (3) Prerequisites: STAT 3123 or permission of the department. Introduction to a variety of computational techniques using various statistics software packages (S-Plus/R or SAS) and symbolic manipulation software packages. Topics include random number generation, density estimation, and re-sampling techniques (bootstrap, jackknife) and Gibbs sample. (Spring)

STAT 4123. Applied Statistics I. (3) Prerequisites: MATH 2164 with a grade of C or better and junior standing, or permission of the department. Review of stochastic variables and probability distributions, methods of estimating a parameter, hypothesis testing, confidence intervals, contingency tables. Linear and multiple regression, time series analysis. (Fall) (Evenings) (Alternate years)

STAT 4124. Applied Statistics II. (3) Prerequisites: STAT 4123 or permission of the department. Single factor analysis of variance. Multi-factor analysis of variance. Randomized complete-block designs, nested or hierarchical designs, Latin squares, factorial experiments. Design of experiments. (Spring) (Evenings) (Alternate years)