Biostatistics - BSTT

The information below lists courses approved in this subject area effective Fall 2015. Not all courses will necessarily be offered these terms. Please consult the Schedule of Classes for a listing of courses offered for a specific term.

500-level courses require graduate standing.

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400 Biostatistics I
4 hours. Descriptive statistics, basic probability concepts, one- and two-sample statistical inference, analysis of variance, and simple linear regression. Introduction to statistical data analysis software. Enrollment restricted to public health students and healthcare administration students; other graduate, professional and advanced undergraduate students admitted by consent as space permits. To obtain consent, see the SPH registrar.

401 Biostatistics II
4 hours. Simple and multiple linear regression, stepwise regression, multifactor analysis of variance and covariance, non-parametric methods, logistic regression, analysis of categorical data; extensive use of computer software. Prerequisite(s): BSTT 400.

494 Introductory Special Topics in Biostatistics
1 TO 4 hours. Special topics in biostatistics. Content varies. May be repeated. Students may register in more than one section per term. Prerequisite(s): Consent of the instructor.

505 Logistic Regression and Survival Analysis
2 hours. Interpretation of logistic regression and survival analysis models. Running logistic and proportional hazards regression models and constructing life-tables using SAS. Previously listed as BSTT 402. Prerequisite(s): BSTT 400 and BSTT 401.

506 Design of Clinical Trials
3 hours. Rationale for clinical trials, blinding, ethical issues, methods of randomization, crossover trials, power and sample size calculations, data management, protocol deviation, data analysis, interim analysis. Previously listed as BSTT 430. Prerequisite(s): BSTT 400 and BSTT 401.

507 Sampling and Estimation Methods Applied to Public Health
3 hours. The purpose of this course is to provide a comprehensive overview of current methods and issues in survey sample design and associated estimation procedures. Previously listed as BSTT 440. Credit is not given for BSTT 507 if the student has credit in STAT 431. Restriction applies only to certification for students pursuing the Interdepartmental Graduate Concentration in Survey Methodology. Prerequisite(s): BSTT 401 or BSTT 502 or consent of the instructor.

521 Applied Multivariate Analysis
3 hours. Analysis of vector of responses; MANOVA, data reduction methods; introduction to cluster analysis, discriminant analysis, and structural equation models. Prerequisite(s): BSTT 537 and consent of the instructor.

523 Biostatistics Methods I
4 hours. Foundations for and introduction to statistical inference, including one- and two-sample problems; regression analysis, including multiple regression and indicator variables. Previously listed as BSTT 502. Prerequisite(s): College calculus, including multivariable calculus, concurrent registration in BSTT 524, and consent of the instructor.

524 Biostatistics Laboratory
2 hours. Use of spreadsheets for statistical investigations; use of statistical software; matrix theory, including methods relevant in biostatistical analysis. Previously listed as BSTT 503. Prerequisite(s): Concurrent registration in BSTT 523 and consent of the instructor.

525 Biostatistics Methods II
4 hours. Analysis of variance and multiple comparisons; model building and diagnostics; generalized linear models; logistic and Poisson regression; introduction to repeated measures and mixed models. Previously listed as BSTT 504. Prerequisite(s): Grade of B or better in BSTT 523 and Grade of B or better in BSTT 524, or consent of the instructor.

535 Categorical Data Analysis
3 hours. Contingency tables and their tests, measures of association, stratified analysis, logistic regression, generalized linear model, Poisson regression, log-linear model, matched data, marginal homogeneity, ordinal data. Previously listed as BSTT 511. Prerequisite(s): Grade of B or better in BSTT 525; and STAT 411, or consent of the instructor.

536 Survival Analysis
3 hours. Concepts of lifetime or survival distributions, especially with censored data; nonparametric estimation of the survival function; rank tests; proportional hazards regression models; parametric models. Previously listed as BSTT 512. Prerequisite(s): Grade of B or better in BSTT 525 and Grade of B or better in STAT 411, or consent of the instructor.

537 Longitudinal Data Analysis
4 hours. Application and theory of models for longitudinal data analysis for both continuous and categorical response data, including use of statistical software for these methods. Previously listed as BSTT 513. Prerequisite(s): Grade of B or better in STAT 411 and Grade of B or better in BSTT 525, or consent of the instructor.

538 Biostatistical Consulting
2 hours. Discussion of techniques required for successful biostatistical consultation; effective communication, problem formulation, data analysis, oral and written reports, supervised consulting experience. Previously listed as BSTT 514. Prerequisite(s): Grade of B or better in BSTT 525 and consent of the instructor. Restricted to students enrolled in the biostatistics major.

550 Biostatistical Investigations
4 hours. Analysis of several large data sets that will require integration of numerous biostatistical tools; written summarization and discussion of results. Previously listed as BSTT 522. Prerequisite(s): Grade of B or better in BSTT 535 and Grade of B or better in BSTT 536 and Grade of B or better in BSTT 537 and Grade of B or better in BSTT 538 and Grade of B or better or concurrent registration in BSTT 521.

560 Large Sample Theory
2 hours. Deriving and applying large sample statistical theories. The primary focus will be in limit theorums and their applications in biostatistical problems. Meets eight weeks of the semester. Previously listed as BSTT 534. Prerequisite(s): Open only to PhD degree students; or consent of the instructor. Adequate training at the level of intermediate mathematical statistics. Masters degree in biostatistics or mathematics.

561 Advanced Statistical Inference
3 hours. An in-depth consideration of some important ideas of statistical inference including large-sample theory, estimation and testing. Specific topics to be covered include asymptotic theory, parameter estimation methods and hypothesis testing. Some computer use in class. Previously listed as BSTT 531. Prerequisite(s): Open only to Ph.D. degree students; and consent of the instructor. Recommended background: MS degree in Biostatistics or the equivalent.

562 Linear Models
4 hours. Generalized inverse matrices; distributions for quadratic forms; estimability and testable hypotheses; constrained linear model; applications to regression, ANOVA, ANCOVA models; variance component models. Previously listed as BSTT 533. Prerequisite(s): Open only to Ph.D. degree students; or consent of the instructor. Recommended background: MS degree in Biostatistics or the equivalent.

563 Generalized Linear Models
4 hours. Teaches students the components of generalized linear models and their extensions. Previously listed as BSTT 541. Prerequisite(s): BSTT 561 and concurrent registration in or prior completion of BSTT 560. Open only to PhD degree students; or consent of the instructor. Adequate training at level of intermediate mathematical statistics. Masters degree in biostatistics, mathematical statistics or methematics.

564 Missing Data
4 hours. Students will learn the statistical methods used for analyzing data with missing values. Previously listed as BSTT 542. Prerequisite(s): BSTT 561 and concurrent registration in or prior completion of BSTT 560. Open only to PhD degree students; or consent of the instructor. Adequate training at level of intermediate mathematical statistics. Masters degree in biostatistics, mathematical statistics or methematics.

565 Computational Statistics
4 hours. Developing a broad and thorough working knowledge of modern statistical computing and computational statistics on a practical, conceptual, philosophical and mathematical level. Previously listed as BSTT 543. Extensive computer use required. Prerequisite(s): Concurrent registration in or prior completion of BSTT 560. Open only to Ph.D. degree students; or consent of the instructor. Adequate training at level of intermediate mathematical statistics. Masters degree in biostatistics, mathematical statistics or mathematics.

566 Bayesian Methods
4 hours. Developing a broad and thorough working knowledge of Bayesian applications on a practical, conceptual, philosophical and mathematical level. Previously listed as BSTT 544. Prerequisite(s): Concurrent registration in or prior completion of BSTT 560. Open only to Ph.D. degree students; or consent of the instructor. Adequate training at level of intermediate mathematical statistics. Masters degree in biostatistics, mathematical statistics or mathematics.

567 Advanced Survival Analysis
4 hours. Methods of analysis for multivariate survival data, including transition models and shared frailty models. Theory behind existing methodology is covered as well as implementation. Prerequisite(s): Grade of B or better or concurrent registration in BSTT 536; and consent of the instructor. Recommended background: Intended for students in the Biostatistics PhD program.

568 Programming and Simulation in R
2 hours. Applications in R on a practical, conceptual, philosophical and mathematical level. The focus is on simulation and computation, not on data analysis. Extensive computer use required. Prerequisite(s): BSTT 400; or both BSTT 523 and BSTT 524; and graduate or professional standing; or consent of the instructor.

594 Special Topics in Biostatistics
1 TO 4 hours. Advanced special topics. Content varies. May be repeated. Students may register in more than one section per term. Prerequisite(s): Consent of the instructor.

595 Biostatistics Research Seminar
1 hours. Current developments in theory and application of biostatistics and epidemiology with presentations by faculty and visiting scientists. Satisfactory/Unsatisfactory grading only. May be repeated.

Information provided by the Office of Programs and Academic Assessment.

This listing is for informational purposes only and does not constitute a contract. Every attempt is made to provide the most current and correct information. Courses listed here are subject to change without advance notice. Courses are not necessarily offered every term or year. Individual departments or units should be consulted for information regarding frequency of course offerings.