BIOSTAT 200 - Biostatistics I
BIOSTAT 201 - Biostatistics II
BIOSTAT 203 - Computers in Medicine
BIOSTAT 214 - Design & Analysis of Clinical Trials
BIOSTAT 222 - Statistical Consulting
BIOSTAT 230 - Foundations for Biostatistics
BIOSTAT 231 - Statistical Models and Methods I
BIOSTAT 232 - Statistical Models and Methods II
BIOSTAT 233 - Statistical Models and Methods III
BIOSTAT 261 - Statistical Inference I
BIOSTAT 262 - Statistical Inference II
BIOSTAT 264 - Time Series Analysis
BIOSTAT 265 - Nonparametric Studies
BIOSTAT 280 - Applied Probability
BIOSTAT 295 - Readings and Research
BIOSTAT 299 - Master's Thesis
BIOSTAT 311 - Real Analysis
BIOSTAT 313 - Statistical Computing
BIOSTAT 363 - Advanced Statistics I
BIOSTAT 364 - Advanced Statistics II
BIOSTAT 365 - Linear Models I
BIOSTAT 371 - Probability Theory
BIOSTAT 384 - Statistical Genetics
BIOSTAT 385 - Bayesian Analysis
BIOSTAT 386 - Survival Analysis
BIOSTAT 391 - Special Topics in Biostatistics
BIOSTAT 399 - Doctoral Dissertation
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| Course Number Name Hours Location |
Course Description |
| BIOST 200 Biostatistics I 3 semester hours |
This is an introductory course in biostatistical methods for non-biostatistics majors. Topics include elementary probability, sampling, point and interval estimation and hypothesis testing. |
| BIOST 201 Biostatistics II 3 credits, spring MCW |
Prerequisite: This is a second semester
introductory course in biostatistical methods for non-biostatistics majors. Typical Text: Practical Statistics for Medical Research - Altman, CRC Press Topics include xxxxx |
| BIOST
203 Computers in Medicine 3 semester hours |
Programming for small computers and larger workstations. The use of statistical packages is explained. Students are required to perform basic statistical analysis using programs in the statistics packages. Semester hours could be reduced for students with prior experience. |
| BIOST 214 Design & Analysis of Clinical Trials 1-3 credits, fall (alternate years) MCW |
Prerequisite:
At least one
statistics course or consent of instructor. Typical Texts: Clincal Trials: A Methodological Perspective by Piantadosi, Wiley Series, N.Y, 1997. (required), and Fundamentals of Clinical Trials by Friedman, Furburg, and DeMets, Springer-Verlag, N.Y, 1998. (recommended). Description: Explore methods and issues in design, conduct and analysis of clinical trials (focusing on Phase II & III trials); Topics covered include patient selection, treatment allocation, randomization, endpoint definition, protocol development, sample size calculation, p-values, quality data collection, data analysis procedures and interpretation of the results. |
| BIOST 222 Statistical Consulting 1-3 credits, summer MCW |
Prerequisite: Statistical Models and Methods II This course is designed for students to gain experience in statistical consulting by working with the biostatistics faculty members on various consulting projects. |
| BIOST 230 Foundations for Biostatistics 3 credits, summer MCW |
Prerequisite: An introductory statistics course, advanced calculus. Typical Texts: Biostatistics - Fisher and van Belle, John Wiley & Sons Advanced Calculus, Fulks, John Wiley & Sons. In preparation for graduate study in Biostatistics, this course provides a review of basic statistics and advanced calculus. In addition, the student is introduced to the Division's computing facilities. Emphasis is placed on problem solving in the review material and on statistical software packages in the computing introduction. |
| BIOST 231 Statistical Models and Methods I 3 credits, fall MCW |
Prerequisite:
Foundations for Biostatistics Typical Text: Biostatistics - Fisher and van Belle, John Wiley & Sons Description: Models and analyses for count data and contingency tables, basic nonparametric methods including sign, rank-sum and signed-ranks tests, simple linear regression model and inference, checking model assumptions, correlation analysis, one-way and two-way analysis of variance. Emphasis is on models, their application to data and interpretation. |
| BIOST 232 Statistical Models and Methods II 3 credits, spring MCW |
Prerequisite:
Statistical Models and Methods I Typical Text: Biostatistics - Fisher and van Belle, John Wiley & Sons Description: Factorial, nested, split-plot and repeated-measures designs, multiple regression and variable selection, multiple comparisons, logistic regression, discriminant analysis, principal components and factor analysis, rates and proportions, introduction to survival analysis. |
|
BIOST 233
Statistical Models and Methods III 3 credits, fall MCW |
Prerequisite:
Statistical Models and Methods II Typical Texts: Applied Regression Analysis - Rawlings, Wadsworth and Brooks, Categorical Data Analysis - Agresti A, John Wiley & Sons Description: Model diagnostics in regression analysis, influence and leverage, outliers, collinearity, remedies including transformations and ridge regression; Models for discrete data, two-way and multi-way tables, loglinear models, analysis of loglinear models, Mantel-Haenszel test, models for ordinal variables, multinominal response and matched pairs, analysis of repeated response data. |
| BIOST 261
Statistical Inference I 3 credits, fall UWM |
Prerequisite:
Advanced Calculus Typical Texts: Statistical Inference - Casella & Berger, Wadsworth & Brooks Description: Fundamentals of probability, independence, distribution and density functions, random variables, moments and moment generating functions, discrete and continuous distributions, exponential families, location and scale families, marginal and conditional distributions, transformation and change of variables, multivariate distributions, random samples, convergence concepts, sampling from normal distributions, order statistics. |
|
BIOST 262
Statistical Inference II 3 credits, spring UWM |
Prerequisite:
Statistical Inference I Typical Texts: Statistical Inference - Casella & Berger, Wadsworth & Brooks Description: Point estimation, interval estimation, hypothesis testing, minimal sufficiency and completeness, ancillary statistics, likelihood and invariance principle, asymptotic properties of estimators and likelihood ratio tests, LMP tests, union-intersection tests, pivotal quantities, coverage probability, large sample estimation and testing. |
|
BIOST 264
Time Series Analysis 3 credits, alternate fall UWM |
Prerequisite:
Statistical Models and Methods II, Statistical Inference II Typical Texts: Applied Statistical Time Series Analysis - Shumway, Prentice Hall Description: An introduction to univariate and bivariate time series with emphasis on stationary ARIMA processes, Box-Jenkins model building and forecasting, spectral representation of stationary time series, model testing and diagnostic evaluation, piecewise non-linear models, and bivariate ARMA processes. |
|
BIOST 265
Nonparametric Statistics 3 credits, alternate spring UWM |
Prerequisite:
Statistical Models and Methods II, Statistical Inference II Typical Texts: Nonparametric Statistical Inference - Gibbons & Chakraborti, Marcel Dekker Description: Nonparametric statistical methods for estimation and testing as an alternative to the commonly used normal-theory models. Topics include order statistics, goodness of fit tests, tests based on ranks, association analysis, power and efficiency of nonparametric tests. |
| BIOST 280
Applied Probability 3 credits, fall, UWM |
Prerequisite:
Statistical Inference I Typical Texts: An Introduction to Stochastic Modeling - Taylor & Karlin, Academic Press Description: Markov chains in discrete and continuous time, Poisson processes, random walks, branching processes, birth and death processes, queuing systems, applications to survival and other biomedical models. |
|
BIOST 295
Readings and Research 1-9 credits |
Prerequisite:
Permission Description: Readings in recent literature and supervised research project. |
|
BIOST 299
Master's Thesis 6 credits |
Prerequisite: Description: |
| BIOST 299
Master's Thesis 6 credits |
Prerequisite:
Description: |
| BIOST 311 Real Analysis 3 credits |
|
|
BIOST 313
Statistical Computing 3 credits, alternate fall MCW |
Prerequisites:
Statistical Models and Methods II, Statistical Inference II Typical Texts: Elements of Statistical Computing - Thisted, Chapman & Hall Tools for Statistical Inference - Tanner, Springer-Verlag Description: Numerical algorithms useful in biostatistics including likelihood maximization using the Newton-Raphson method, numerical integration using quadrature and Monte Carlo methods, interpolation using splines, random variate generation methods, the data augmentation algorithm, Markov chain Monte Carlo and the Metropolis-Hastings algorithm. |
|
BIOST 363
Advanced Statistics I 3 credits, alternate fall MCW |
Prerequisites:
Statistical Inference II Typical Texts: Theoretical Statistics - Cox & Hinkley, Chapman & Hall Description: Families of models, likelihood, sufficiency, significance tests, composite null and alternative hypotheses, similar regions, invariant test, Interval estimation, point estimation, bias and variance, Cramer-Rao inequality, asymptotic theory, large-sample inference, likelihood ratio test, score test, Wald's test. |
|
BIOST 364
Advanced Statistics II 3 credits, alternate spring MCW |
Prerequisites:
Advanced Statistics I Description: A mathematically rigorous survey of selected topics in the theory of statistical inference such as sequential analysis, robust procedures, resampling plans - jackknife and bootstrap, decision theory, minimax analysis and variance components. |
|
BIOST 365
Linear Models I 3 credits, alternate fall MCW |
Prerequisites:
Statistical Models and Methods II and Statistical Inference II Typical Text: Plane Answers to Complex Questions (The Theory of Linear Models) - Christensen, Springer-Verlag Description: Review of matrix algebra and vector spaces; multivariate normal distribution and quadratic forms, least squares estimation, testing nested models, weighted least squares, one-way ANOVA, testing contrasts, multiple comparison, partial and multiple correlation coefficients, polynomial regression, lack-of-fit test. |
|
BIOST 371
Probability Theory 3 credits, spring UWM |
Prerequisites:
Real Analysis, Statistical Inference I Typical Text: Probability and Measure - Billingsley, John Wiley & Sons Description: Mathematically rigorous definitions of probability space, random variable, random vector, stochastic process, absolute continuity and the Radon-Nikodym derivative; integration and expectation; independence, Borel-Cantelli lemma, zero-one laws; conditional expectation, martingales and submartingales; the martingale convergence theorem, sums of independent random variables, infinitely divisible laws and stable laws, the Central Limit Theorem. |
|
BIOST 384
Statistical Genetics 3 credits, spring MCW |
Prerequisites:
Linear Models I, Statistical Inference II Description: Fundamental elements of mathematical and population genetics, and statistical theory of the methods of human genetic analysis. Topics include Hardy-Weinberg equilibrium, inbreeding, selection, mutation, models for polygenic and multifactorial inheritance, variance components estimation for the genetic analysis of familial aggregation, linkage and segregation analysis, and ascertainment problems. |
|
BIOST 385
Bayesian Analysis 3 credits, spring MCW |
Prerequisites:
Statistical Models and Methods III, Advanced Statistics I and Statistical
Computing Description: A combination of Bayesian principles, tools and methods; emphasis is on models, computations and analysis. Likelihood function; prior, posterior and predictive distributions; Bayes factors, HPD regions; conjugate and noninformative priors in the exponential family, Markov chain Monte Carlo methods for the generalized linear model; hierarchical models, restricted parameter spaces and censored data, examples of Bayesian analyses of complex biomedical models. |
| BIOST 386
Survival Analysis 3 credits, spring MCW |
Prerequisites:
Statistical Inference II, Probability Theory Typical Texts: Statistical Methods in Counting Processes - Anderson, Borgan, Gill and Keiding, Springer-Verlag Description: Analysis of survival data using counting process techniques. Topics include the mathematical theory of counting process, censoring and truncation, estimation of the survival and cumulative hazard functions, extensions of k-sample nonparametric tests to censored and truncated data, proportional hazards and additive hazards regression models. |
|
BIOST 391 Special Topics in Biotatistics 1-3 credits |
Description: This course is designed to cover special topics in Biostatistics that are not covered in regular courses. The topics will depend on the research interests of the instructor and the students. |
|
BIOST 399 Doctoral Dissertation 1-9 credits |
Prerequisites:
Permission Description: Dissertation research and publication of research as necessary for completion of the doctoral dissertation. |