Biostatistics Course Descriptions

COURSE IN BIOSTATISTICS

 

STA 550 Introduction to Computing (1) 
An introduction to the use of micro and main-frame computers. Communications between computers and the use of statistical and word processing soft-ware packages will be included. Prerequisites: None

STA 552 Principles of Statistical Inference I (3)
An introduction to descriptive statistics, measures of central tendency and variability, probability distributions, sampling, estimation, confidence intervals and hypothesis testing. Computing is introduced and used throughout the course. STA 552 and STA 553 satisfies the core requirement in statistics for programs in the School of Public Health.
Prerequisites: None

STA 553 Principles of Statistical Inference II (3)
Continuation of STA 552. Topics includes correlation, regression, analysis of variance, analysis of contingency tables and non-parametric statistics. Computing is used throughout the course. STA 552 and STA 553 satisfies the core requirement in statistics for programs in the School of Public Health. Prerequisites: STA 552 or equivalent

STA 554 Introduction to Theory of Statistics I (3)
A mathematical treatment of principles of statistical inference. Topics include probability, random vari-ables and random vectors, univariate and multi-variate distributions and an introduction to estimation. Appropriate for graduate students in other discip-lines and for preparation for the second actuarial examination. Prerequisites: Calculus and Linear Algebra. Equivalent to Mat 554. Students may not receive credit for Mat 554 and STA 554.

STA 555 Introduction to Theory of Statistics II (3)
Continuation of STA 554. Topics include methods of estimation, theory of hypothesis testing, sufficient statistics, efficiency and linear models. Appropriate for graduate students in other disciplines and for preparation for the second actuarial examination. Prerequisites: STA 554, Mat 554 or equivalent.

 
STA 556 Introduction to Bayesian Inference I (3)
Topics include subjective probability, axiomatic development and applications of utility, basic concepts of decision theory, conjugate and locally uniform prior distributions.
Prerequisites: STA 552 or equivalent. Equivalent to Mat 556. Students may not receive credit for Mat 556 and STA 556.

STA 557 Introduction to Bayesian Inference II  
Continuation of STA 556.  Topics include limiting posterior distributions, estimation and hypothesis testing, preposterior distributions and their application to the design of statistical investigations. Prerequisites: STA 556 or equivalent. Equivalent to Mat 557. Students may not receive credit for STA 557 and Mat 557.

STA 558 Methods of Data Analysis I (3)
Statistical methodology emphasizing exploratory approaches to data. Elementary notions of modeling and robustness. Overview of inferential techniques in current use. Criteria for selection and application of methods.  Use of computing facilities to illustrate and implement methods. Regression and  analysis of variance are the primary topics. Prerequisites: STA 552 or  equivalent. Equivalent to Mat 558. Students may not receive credit for STA 558 and Mat 558.

STA 559 Methods of Data Analysis II (3)
Continuation of STA 558. Topics include clustering, multi-variate analyses, sequential and non-parametric methods.  Prerequisites: STA 558 or  equivalent. Equivalent to Mat 558. Students may not receive credit for STA 559 and Mat 558.

STA 560 Introduction to Stochastic Processes I (3)
An introduction to applied stochastic processes. Topics include Markov chains, queuing theory, renewal theory, Poisson processes and extensions, epidemic and disease models. Prerequisites: STA 552 or an introductory probability course. Equivalent to Mat 560. Students may not receive credit for STA 560 and Mat 560.
 
STA 561 Introduction to Stochastic Processes II (3)
Continuation of STA 560. More advanced topics in Markov chains, queuing theory, renewal theory, Poisson processes and extensions, epidemic and disease models. Prerequisites: STA 560 or permission of the instructor.

STA 562 Design of Experiments I (3)
Principles in the design and analysis of controlled experiments. Topics include general linear hypotheses, multiple classifications, Latin squares and factorial designs.
Prerequisites: STA 552 or equivalent. Equivalent to Mat 562. Students may not receive credit for STA 562 and Mat 562.

STA 564 Sample Survey Methodology I (3)
Principles of survey sampling and analysis. Topics include simple random sampling, stratified sampling, cluster sampling and multistage sampling.
Prerequisites: STA 553 or equivalent. Equivalent to Mat 564. Students may not receive credit for STA 564 and Mat 564.

STA 566 Analysis of Categorical Data I (3)
Introduction to the analysis of categorical data. Topics include rates, ratios and proportions, relative risk, Cochran Mantel Haenszel procedures, linear and log linear models for categorical data, maximum likelihood estimation and tests of hypotheses. Prerequisites: STA 552 or equivalent. Equivalent of Mat 566. Students may not receive credit for STA 566 and Mat 566.

STA 567 Analysis of Categorical Data II (3)
Continuation of STA 566. Topics include more complex linear and log- linear models for categorical data, goodness of fit measures and tests of hypotheses.
 Prerequisites: STA 566 or equivalent.

STA571 Topics in Informatics
Selected topics in informatics, information systems, wide area networks, storing, retrieving and analyzing of medical and public health information.

STA 654 Probability and Theory of Statistical Inference I (3)
Univariate and multi-variate distribution theory, properties of estimators, large sample theory, confidence intervals and theory of tests. Prerequisites: STA 555 or equivalent.

STA 655 Probability and Theory of Statistical Inference II (3)
Continuation of STA 654. Advanced theory of tests, decision theory and other topics. Prerequisites: STA 654 or equivalent.

STA 656 Design of Clinical Trials (3)
Introduction to topics in the design and analysis of clinical trials and related experiments.
Prerequisites: STA 555 or equivalent.

 
STA 658 Mathematical Models in Biometry I (3)
Topics in the mathematical and statistical methods required to model deterministic and stochastic models for phenomenon found in the different areas of biostatistics and the health sciences.
Prerequisites: STA 555 or equivalent.

STA 660 Linear Models I (3)
Topics include the theory of least squares, distribution of quadratic forms, G inverse, general Gauss Markov model, estimation, hypothesis tests, confidence intervals for unrestricted and restricted models, regression models and analysis of variance. Prerequisites: STA 555 or equivalent. Students may not receive credit for STA 661 and Mat 660.

STA 661 Linear Models II (3)  
Continuation of STA 660. Topics include advanced analysis of variance and analysis of covariance, repeated measures, mixed and random models.
Prerequisites: STA 660 or equivalent.

STA 662 Multivariate Analysis I (3)
Topics include the basic properties of multi-variate normal distributions and other related distributions, inference in multi-variate cases and principle component analysis.
Prerequisites: STA 555 or the consent of the instructor.

STA 663 Multivariate Analysis II (3)
Continuation of STA 662. Topics include discrim-inate analysis, canonical correlation analysis and factor analysis.
Prerequisites: STA 662 or the consent of the instructor.

STA 664 Time Series Analysis I (3)
Topics include the study of inference, estimation, prediction, parsimonious description for univariate time ordered data, various models including Box Jenkins and classical stationary processes with rational spectral densities.
Prerequisites: STA 555 and STA 559 or consent of the instructor. Equivalent to Mat 664. Students may not receive credit for STA 664 and Mat 664.

STA 665 Time Series Analysis II (3)
Continuation of STA 664. Advanced topics include the study of univariate and multi-variate time ordered data, various models including Box Jenkins and classical stationary processes with rational spectral densities.
Prerequisites: STA 664 or consent of the instructor.

STA 666 Survivorship Analysis I (3) 
Topics in survival func-tions, hazard rates, life tables, estimation of survival functions from complete and censored data, fitting parametric models, tests of hypotheses, and covariate models.
Prerequisites: STA 555 or consent of instructor.
          
STA 667 Survivorship Analysis II (3) 
Continuation of STA 666. Advanced topics in the theory of survival functions for complete and censored data, tests of hypotheses, and time
dependent covariate models.
Prerequisites: STA 666 or consent of instructor.

STA 668 Independent Study in Biometry and Statistics (3)
Selected study of a topic in Biometry and Statistics.
Prerequisites: Consent of the instructor.

STA 669 Master's Seminar in Biometry and Statistics (3)
Selected topics in statistics. A report is written on the subject studied. Required of all candidates for a master's degree in Biostatistics, except those who write a master's thesis. Prerequisites: Consent of the instructor.

STA 868 Independent Study and Research in Biometry and Statistics (2 5)
Independent study at the doctoral level under the direction of a member of the Biometry and Statistics faculty. May be repeated for credit. Prerequisite: Consent of instructor.

STA 899 Doctoral Dissertation (3-12 L.U.E.)
May be repeated for credit. Load equivalent only. Prerequisite: Consent of dissertation director.