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Course Criteria
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1.00 - 9.00 Credits
Readings, lecture, discussions, or labs (or any combination of these) in special topics in statistics or biostatistics. Prerequisites: Depends on the topic.
Prerequisite:
Prerequisites: Depends on the topic.
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3.00 Credits
Project-oriented overview of major statistical techniques commonly used in problems encountered in health professions. Students will learn to use a major statistical computing package. Hypothesis testing, t-tests, regression, analysis of variance, analysis of covariance, categorical data analysis, nonparametric statistics. Offered fall, winter, and spring/summer semesters.
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3.00 Credits
Application-oriented overview of designed experiments commonly encountered in engineering. Students will learn about planning and conducting experiments and about analyzing the resulting data using a major statistical package. Simple comparative experiments concerning means and variances, experiments with single or multiple factors, factorial designs, Taguchi designs, and response surface methodology. Offered fall semesters on sufficient demand. Prerequisites: Graduate standing.
Prerequisite:
Prerequisites: Graduate standing.
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3.00 Credits
Provides intensive instruction in the use of SAS to prepare data for statistical analysis. Topics include importing/exporting data in various formats; character and numeric manipulation; merging, setting and combining datasets; effective programming skills using arrays, loops and macros; creating graphs; and producing reports. Offered winter semester. Prerequisite: STA 610 or STA 631.
Prerequisite:
Prerequisite: STA 610 or STA 631.
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3.00 Credits
An applications-oriented overview of statistical methods commonly used in multivariate analyses of health care data. Students will develop skill in understanding published reports of multivariate analyses. Techniques include canonical correlation analysis, multivariate analysis of variance, covariance and repeated measures, principle components analysis, factor analysis, discriminant analysis, and cluster analysis. Offered fall semester. Prerequisite: STA 610 or STA 622.
Prerequisite:
Prerequisite: STA 610 or STA 622.
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4.00 Credits
Design and analysis of single and multiple-factor experiments. Includes block designs, repeated measures, factorial and fractional factorial experiments, and response surface experimentation. Techniques include simple and multiple linear regression, repeated measures, generalized linear models, correlation, and model building diagnosis. Applications in biological and biomedical problems. A computer package will be used. Offered fall semester. Prerequisite: STA 616.
Prerequisite:
Prerequisite: STA 616.
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3.00 Credits
Design of experiments and application of statistical techniques commonly used by biologists. Emphasis on techniques for count data, correlation and regression, analysis of variance, multivariate analysis, and nonparametric methods using biological data. A computing package will be utilized throughout the course. Offered fall semesters.
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3.00 Credits
Study of the methodology and application of statistical techniques for categorical data. Methods include binomial and multinomial models, Poisson and logistic regression and contingency tables. Additional topics which may be covered include repeated measures and random effect models. Model interpretation and the application of statistical software will be emphasized. Offered winter semester. Prerequisites: STA 616 (may be taken concurrently).
Prerequisite:
Prerequisites: STA 616 (may be taken concurrently).
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2.00 Credits
This course is designed for individuals with a quantitative background who are interested in the scientific, policy, design and management aspects of clinical trials. Topics include types of treatment allocation and randomization, patient recruitment and adherence, power and sample size, interacting with monitoring committees, administering multicenter trials, and study closeout. Offered winter semesters. Prerequisites: STA 610 and one of the following (PSM 650, BIO 610, BMS 601, or NUR 690).
Prerequisite:
Prerequisites: STA 610 and one of the following (PSM 650, BIO 610, BMS 601, or NUR 690).
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3.00 Credits
An applied introduction to analyzing time to event data with emphasis on data analysis and corresponding interpretations. Topics include survivor and hazard functions, censoring, Kaplan-Meier estimation, log-rank and related tests, Cox proportional hazards model, time-dependent covariates, and parametric models. SAS will be used. Offered winter semester of odd-numbered years. Prerequisite: STA 616 (prerequisite or corequisite).
Prerequisite:
Prerequisite: STA 616 (prerequisite or corequisite).
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