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Course Criteria
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2.00 Credits
Topics include basic goodness-of-it measures, such as Pearson's chi-square statistics, Mantel and Haenszel test, contingency tables, log-linear analysis of multidimensional contingency tables, and logistic regression. Techniques for analysis of count data, such as Poisson regression; and analysis of matched case-control studies and clustered categorical data. Prerequisite: STAT 522* (*may be taken concurrently); or equivalent.
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2.00 - 3.00 Credits
Basic data and file manipulation using database-management systems for health research. Uses several applications, with emphasis on Microsoft Access. Topics include: importing, exporting, merging, and linking files for a variety of applications; creating, updating, and querying databases; and basic programming, application development, and data entry. General computer skills expected, but no prior computer programming experience necessary. Prerequisite: (STAT 509 or STAT 521), (STAT 548 or STAT 549); Prerequisite for 3 units: STAT 509 or 521, 548 or 549. For 2-3 units: General computer skills expected, but no prior computer programming experience necessary.
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3.00 Credits
Computer applications to advanced statistical procedures using SAS, SPSS, and other statistical software. Advanced techniques facilitating statistical analysis useful to biostatisticians, epidemiologists, health planners, and others transferring data files between software packages, combining and matching files, modifying data, and creating graphical presentations of data. Prerequisite: (STAT 548 or STAT 549), STAT 521, STAT 522.
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3.00 Credits
Principles and procedures of surveys as applied to the health sciences. Topics covered include: survey and research designs, questionnaire construction, validity techniques, sampling methods, sample-size determination, non-response problems, data collection, coding, processing, evaluation, and presentation of results. Hands-on experience presented as a combination of lecture and laboratory activities. Prerequisite: STAT 509* or STAT 521* (*may be taken concurrently). Cross-listing: STAT 464.
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3.00 Credits
Concepts and applications of the most common data-analysis methods: correlation and regression, contingency tables, ttests, analysis-of-variance, nonparametric methods, and multivariate analyses. Student selects appropriate method of analysis and reporting results. Emphasizes individual analysis of real-data sets. Lecture-demonstrations and laboratory work. All data-analysis assignments to be completed in SPSS. Prerequisite: (STAT 509 or STAT 521), (STAT 548 or STAT 549). Cross-listing: STAT 468.
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3.00 Credits
Brings together other biostatistics courses in a unified, applied approach. Specifically provides practical experience with real-world biostatistical data, using a wide variety of statistical procedures--including general linear models, generalized linear models, and nonparametric alternatives. Includes guidelines for choosing statistical procedures, model building, validation, and written presentation of results. Prerequisite: STAT 522.
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1.00 - 4.00 Credits
Advanced students participate in statistical consultation with senior staff members. Statement of the problem, design of the experiment, definition of response variables, appropriate analysis of data, statistical inferences, and interpretation of data. Prerequisite: Consent of instructor.
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1.00 Credits
Presents and discusses area of interest. Individual research and report.
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1.00 - 8.00 Credits
Individual consultation on project design and data collection, analysis, evaluation, and interpretation. Prerequisite: Consent of instructor.
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1.00 Credits
Independent research. Research program arranged with faculty member(s) involved. Written report and oral presentation required.
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