College of Natural and Health Sciences
School of Mathematical Sciences
Prerequisite: MATH 023 with a grade of "C" or better (C- is not acceptable), or a full year of high school modern second year algebra with a grade of "C" or better (C- is not acceptable), or consent of instructor. Study techniques used in organizing data, including frequency distributions, histograms, measures of central tendency, measures of dispersion, probability distributions, point estimation, interval estimation and testing hypotheses. (LAC, gtP)
Prerequisite: STAT 150 or equivalent. Study of inferential techniques including nonparametric methods, ANOVA models, experiemental design, multiple regression, sampling methods and control charts.
Prerequisite: MATH 350 with the grade of "C" or better (C- is not acceptable). Topics in multiple linear regression, estimation of model parameters, inferences, diagnostics, model assumptions, ANOVA formulation.
Prerequisite: MATH 350 with the grade of "C" or better (C- is not acceptable). Introduction to elementary sampling concepts. Includes random sampling, stratified sampling, cluster sampling and systematic sampling. Inferences and assumptions are presented for all sampling methods.
Individualized investigation under the direct supervision of a faculty member. (Minimum of 37.5 clock hours required per credit hour.) Repeatable, maximum concurrent enrollment is two times.