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STAT Statistics and Probability( Computer, Mathematical and Physical Sciences) STAT100 Elementary Statistics and Probability; (3 credits) Grade Method: REG/P-F/AUD. CORE Mathematics or Formal Reasoning (MS) Course.Prerequisite: permission of Math Department based on satisfactory score on MATHEMATICS PLACEMENT EXAM; or MATH110, MATH112, MATH113, or MATH115. Not open to students who have completed MATH111 or any MATH or STAT course with a prerequisite of MATH141. Credit will be granted for only one of the following: MATH111 or STAT100. Simplest tests of statistical hypotheses; applications to before-and-after and matched pair studies. Events, probability, combinations, independence. Binomial probabilities, confidence limits. Random variables, expected values, median, variance. Tests based on ranks. Law of large numbers, normal approximation. Estimates of mean and variance. STAT400 Applied Probability and Statistics I; (3 credits) Grade Method: REG/P-F/AUD. Prerequisite: MATH141. Not acceptable toward graduate degrees in STAT, AMSC, or MATH. Credit will be granted for only one of the following: BMGT231, ENEE324 or STAT400. These courses are not interchangeable. Consult your program requirements or advisor for what is acceptable toward your program of study. Random variables, standard distributions, moments, law of large numbers and central limit theorem. Sampling methods, estimation of parameters, testing of hypotheses. STAT401 Applied Probability and Statistics II; (3 credits) Grade Method: REG/P-F/AUD. Prerequisite: STAT400 (Not acceptable toward graduate degrees in STAT, AMSC, or MATH). Point estimation - unbiased and consistent estimators. Interval estimation. Minimum variance and maximum likelihood estimators. Testing of hypotheses. Regression, correlation and analysis of variance. Sampling distributions. Elements of non-parametric methods. STAT410 Introduction to Probability Theory; (3 credits) Grade Method: REG/P-F/AUD. Prerequisite: MATH240 and MATH241. Also offered as SURV410. Credit will be granted for only one of the following: STAT410 or SURV410. Probability and its properties. Random variables and distribution functions in one and several dimensions. Moments. Characteristic functions. Limit theorems. STAT430 Introduction to Statistical Computing with SAS; (3 credits) Grade Method: REG/P-F/AUD. Prerequisite: STAT400 or permission of instructor. Descriptive and inferential statistics. SAS software: numerical and graphical data summaries; merging, sorting and splitting data sets. Least squares, regression, graphics and informal diagnostics, interpreting results. Categorical data, lifetime data, time series. Applications to engineering, life science, business and social science. STAT440 Sampling Theory; (3 credits) Grade Method: REG/P-F/AUD. Prerequisite: STAT401 or STAT420. Also offered as SURV440. Credit will be granted for only one of the following: STAT440 or SURV440. Simple random sampling. Sampling for proportions. Estimation of sample size. Sampling with varying probabilities. Sampling: stratified, systematic, cluster, double, sequential, incomplete. STAT464 Introduction to Biostatistics; (3 credits) Grade Method: REG/P-F/AUD. Prerequisite: One semester of calculus. Not acceptable for credit towards degrees in mathematics or statistics. Junior standing. Probabilistic models. Sampling. Some applications of probability in genetics. Experimental designs. Estimation of effects of treatments. Comparative experiments. Fisher-Irwin test. Wilcoxon tests for paired comparisons. STAT498A (PermReq) Selected Topics in Statistics; (1-6 credits) Grade Method: REG/P-F/AUD. Individual Instruction course: contact department or instructor to obtain section number. STAT600 Probability Theory I; (3 credits) Grade Method: REG/AUD. Prerequisite: STAT 410. Probability space, classes of events, construction of probability measures. Random variables, convergence theorems, images of measures. Independence. Expectation and moments, Lebesque integration, spaces, Radon-Nikodym and LP theorem, singular and absolutely continuous measures. Conditional expectations, existence of regular distributions, applications. Probabilities on product spaces, Fubini theorem, Kolmogorov extension theorem, Tulcea product theorem. STAT687 Minicourse Series in the Mathematical Sciences; (1 credit) Grade Method: REG/AUD. Also offered as AMSC687 and MATH687. Credit will be granted for only one of the following: AMSC687, MATH687 or STAT687. This series will consist of up to sixteen 3-lecture presentations covering a broad range of topics in the mathematical sciences. Each minicourse is intended to be self-contained and accessible to first year graduate students and advanced undergraduates. The goal of each minicourse is to present an active research area or significant result and the necessary vocabulary and perspective for students to appreciate it. The goal of the Minicourse Series is to broaden a student's awareness of the mathematical sciences and to inform them of research directions. STAT689 (PermReq) Research Interactions in Statistics; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. STAT698A Selected Topics in Probability; (1-4 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. STAT700 Mathematical Statistics I; (3 credits) Grade Method: REG/AUD. Prerequisite: STAT 410 or equivalent. Sampling distributions including noncentral chi-squared, t, F. Exponential families, completeness. Sufficiency, factorization, likelihood ratio. Decision theory, Bayesian methods, minimax principle. Point estimation. Lehmann-Scheffe and Cramer-Rao theorems. Set estimation. Offered fall only. STAT710 Advanced Statistics I; (3 credits) Grade Method: REG/AUD. Prerequisite: STAT 421. Recommended corequisite: STAT 600. Statistical decision theory. Neyman-Pearson lemma and its extensions. Uniformly most powerful test. Monotone likelihood ratio. Exponential families of distributions, concepts of similiarity, and tests with Neyman structure. Unbiased tests and applications to normal families. STAT740 Linear Statistical Models I; (3 credits) Grade Method: REG/AUD. Prerequisite: STAT 420 or STAT 700. Least squares, general linear models, estimability and Gauss-Markov theorem. Simple and multiple linear regression, analysis of residuals and diagnostics, polynomial models, variable selection. Qualitative predictors, one and two way analysis of variance, multiple comparisons, analysis of covariance. Nonlinear least squares. High-level statistical computer software will be used for data analysis throughout the course. STAT770 Analysis of Categorical Data; (3 credits) Grade Method: REG/AUD. Prerequisite: STAT 420 and STAT 430 or permission of department. Loglinear and logistic models. Single classification, two-way classification; contingency tables; tests of homogeneity and independence models, measures of association, distribution theory. Bayesian methods. Incomplete contingency tables. Square contingency tables - symmetry. Extensions to higher dimensional contingency tables. STAT798A Selected Topics in Statistics; (1-4 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. STAT799 Master's Thesis Research; (1-6 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number. STAT898 Pre-Candidacy Research; (1-8 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number. STAT899 (PermReq) Doctoral Dissertation Research; (6 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number.
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