BMI Course Information
BMI 515 Advanced Biostatistical Methods (3)
Instructor Information |
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Fall 2009 |
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Spring 2009 |
Course not offered |
Catalog Description
Biomedical data, statistical methods and software, basic probability and statistics, confidence interval, hypothesis tests, analysis of variance, binary data.
Prerequisites
Admission to any SCI graduate program
Textbook and Other Materials
Pattern Classification, 2nd Ed., Wiley-Interscience, New York (R.O. Duda, P.E. Hart, D.G. Stork).
The Nature of Statistical Learning Theory, 2nd Ed., 1999, Springer-Verlag (Vladimir N. Vapnik)
Course Learning Outcomes
Students will understand the use of quantitative and qualitative tools for decision support and data analysis including:
- Clinical study design, study proposal development, and experimental design and statistics (including sampling, survey design, and analysis and population and demographic data for clinical trials).
- Statistics methods
- Guideline development and application/evidence based medicine
- Clinical decision making/application of quantitative and qualitative tools
- Students will be able to understand biomedical data
- Students will be able to design, conduct biomedical studies
- Students will be able to correctly use the quantitative and qualitative statistics for biomedical data analysis
- Students will be able to use statistical software analyzing biomedical data
- Students will be able to apply tools to guidelines development and clinical decision making
Major Topics and Time Covered
- Randomized trials, observational studies, and organizing biomedical data
- Descriptive Statistics for biomedical data
- Probability and Random Variables
- Useful distributions for Biomedical data
- Estimation, Confidence Interval, and Hypothesis Testing for biomedical studies
- Analysis of Variance
- Introduction to binary data analysis
- Categorical data analysis
- Logistic Regression
- Linear Regression