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Biostatistics Courses

Our Department Courses

BMI 511
Introduction to Biostatistics
  Fall - 3 credits

This course will provide a breadth in biostatistical methods for public health practitioners. Topics will include research design, data collection methods and database management, statistical computing and programming, descriptive statistics in tables and graphics, and biostatistical methods for summary measures, probability and distributions, sampling distributions, statistical inference, hypothesis testing and statistical comparison, nonparametrics, correlation, regression analysis and survey sampling.

BMI 541
Introduction to Biostatistics
  Fall - 3 credits

Course designed for the biomedical researcher. Topics include: descriptive statistics, hypothesis testing, estimation, confidence intervals, t-tests, chi-squared tests, analysis of variance, linear regression, correlation, nonparametric tests, survival analysis and odds ratio. Biomedical applications used for each topic. Prerequisite: Math 221 or equivalent or instructor's consent.

BMI 542
Introduction to Clinical Trials l
  Spring - 3 credits

Intended for biomedical researchers interested in the design and analysis of clinical trials. Topics include definition of hypotheses, measures of effectiveness, sample size, randomization, data collection and monitoring, and issues in statistical analysis. Statistics graduate students should take Stat 641. Prerequisite: Stat 541 or equivalent or instructor's consent.

BMI 544
Introduction to Clinical Trials ll
  Fall - 3 credits

This course will provide practical experience and training in clinical trial research. The course will focus on the design, implementation, and conduct of clinical trials. Topics include: regulatory requirements for cinical trials; data collection strategies, data quality and management; budget development and justification; federal, institutional, and sponsor-defined requirements; establishment of research infrastructures for safety and success; preparation of investigator-INDs; investigator responsibilities in Phase l-IV trials. Development of data collection and data management systems and a budget for the protocol developed in 541 are require components of this course.

BMI 546
Practicum in Clinical Trial Data Analysis and Interpretation
  as needed - 3 credits

This course will provide practice in analysis and interpretation of existing datasets from national and international clinical trials in a variety of diseases. Students will develop a research question, review clinical protocols, and analyze available data to prepare a report. Prerequisites: Stat 541 or Stat 572 and Stat 542 or Stat 641.

BMI 551
Introduction to Biostatistics for Population Health (cross-listed with Population Health Sciences)   Fall - 3 credits

The course provides research-oriented students in the population health program with a thorough grounding in basic probability and statistics. An understanding of the procedures and applications to population health problems are stressed.  The following topics are covered: descriptive statistics and graphical methods, elementary probability, elementary properties of random variables, binomial distribution, Poisson distribution, normal distribution, Central Limit Theorem, normal approximations to the binomial and Poisson, one-sample inference for the normal mean and variance, one-sample inference for the binomial and Poisson, paired t-test, two-sample t-test, two-sample tests for binomial data, measures of effect for binomial data (odds ratio, relative risk, risk difference) and power and sample size calculations.

BMI/Stat 877
Statistical Methods for Molecular Biology - 3 credits (cross-listed with Department of Statistics)   Spring - 3 credits

The course will provide a statistical perspective on some current biological problems, with an introduction to statistical analysis in genomics, phylogenetics, gene regulation, gene expression, gene mapping by linkage or association, and related areas. Statistical concepts will include: stochastic modeling, hierarchical modeling, likelihood methods, Bayesian methods, multivariate analysis methods, model selection, high-dimensional parameters, experimental design strategies, and multiple testing. Biological concepts will include: microarray and related measurement of DNA, RNA, and protein; genomic resources; the relationship between genotype and phenotype; breeding designs; pedigrees; and phylogenies. Prerequisites: Stat 309-310 or 609-610 or 709-710 or equivalent, or consent of instructor, also Genetics 466 or equivalent strongly recommended. The course is team taught- this semester the course leader is Sunduz Keles.

Department of Statistics Courses (some are cross-listed)

Department of Statistics Courses

Uw Madison, Chemistry Lab UW Madison, Class held outside on Bascom Hill