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Course Criteria
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3.00 Credits
Statistics in Research I. (3-0). Credit 3. For graduate students in other disciplines; non-calculus exposition of the concepts, methods and usage of statistical data analysis; T-tests, analysis of variance and linear regression. Prerequisite: MATH 102 or equivalent.
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3.00 Credits
Statistics in Research II. (3-0). Credit 3. Continuation of STAT 651. Concepts of experimental design, individual treatment comparisons, randomized blocks and factorial experiments, multiple regression, Chi-squared tests and a brief introduction to covariance, non-parametric methods and sample surveys. Prerequisite: STAT 651.
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3.00 Credits
Statistics in Research III. (3-0). Credit 3. Advanced topics in ANOVA; analysis of covariance; and regression analysis including analysis of messy data; non-linear regression; logistic and weighted regression; diagnostics and model building; emphasis on concepts; computing and interpretation. Prerequisite: STAT 652.
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3.00 Credits
Forecasting Methods and Applications. (3-0). Credit 3. Development of statistical models for describing business trends and economic fluctuations, generation of forecasts and error limits, evaluation of forecasts; applications to economic data arising in business. Classification 6 students may not enroll in this course. Prerequisite: STAT 652 or equivalent or approval of instructor. Cross-listed with INFO 655.
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3.00 Credits
Applied Analytics Using SAS Enterprise Miner. (3-0). Credit 3. Introduction to data mining and will demonstrate the procedures; Optimal prediction decisions; comparing and deploying predictive models; neural networks; constructing and adjusting tree models; the construction and evaluation of multi-stage models. Prerequisite: STAT 657.
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3.00 Credits
Advanced Programming Using SAS. (3-0). Credit 3. Programming with SAS/IML, programming in SAS Data step, advanced use of various SAS procedures. Prerequisites: STAT 604 and 642.
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3.00 Credits
Transportation Statistics. (3-0). Credit 3. Design of experiments, estimation, hypothesis testing, modeling, and data mining for transportation specialists. Prerequisite: STAT 211 or STAT 651.
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3.00 Credits
Applied Categorical Data Analysis. (3-0). Credit 3. Introduction to analysis and interpretation of categorical data using ANOVA/regression analogs; includes contingency tables, loglinear models, logistic regression; use of computer software such as SAS, GLIM, SPSSX. Prerequisite: STAT 601, 641 or 652 or equivalent.
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3.00 Credits
Statistical Genetics I. (3-0). Credit 3. Basic concepts in human genetics, sampling designs, gene frequency estimation, Hardy-Weinberg equilibrium, linkage disequilibrium, association and transmission disequilibrium test studies, linkage and pedigree analysis, segregation analysis, polygenic models, DNA sequence analysis. Prerequisites: STAT 610 and 611.
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3.00 Credits
Advanced Statistical Genetics. (3-0). Credit 3. This course is a continuation of the course, STAT 661 Statistical Genetics. A strong background in statistics, genetics, and mathematics is required. Topics include counting methods, EM algorithm, Newton's method, scoring in genetics, genetic identity coefficients, descent graphs, molecular phylogeny, models of recombination, sequence analysis, diffusion processes, and linkage disequilibrium mappings. Prerequisites: STAT 610, 611, 661.
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