PHST 500  Introduction to Biostatistics for Health Sciences I  3 hours 
Introduction to descriptive and inferential statistical methods, including graphics, estimation, confidence intervals, 1 and 2 sample hypothesis testing, oneway analysis of variance and use of statistical software. 

PHST 501  Introduction to Biostatistics for Health Sciences II  3 hours 
Continued introduction to descriptive and inferential statistical methods including ANOVA regression, chisquare analysis of frequencies, survival analysis, and nonparametric methods. 

PHST 602  Biostatistics Seminar  1 hour 
Weekly seminar series with topics covering active areas of research in biostatistics. 

PHST 603  Biostatistics Public Health Practicum I  12 hours 
Practical experience in biostatistical collaboration in which a student works with one or more investigators in the health sciences. 

PHST 604  Biostatistics Public Health Practicum II  12 hours 
Practical experience in biostatistical collaboration in which a student works with one or more investigators in the health sciences. 

PHST 620  Introduction to Statistical Computing  3 hours 
This course addresses fundamentals of statistical computing with special emphasis on software tools employed most often in biostatistics. 

PHST 624  Clinical Trials I: Planning and Design  2 hours 
Phases of trials, experimental designs, inclusion and exclusion criteria, randomization and blinding, the general linear model and mixed and fixed effects repeated measures analysis of variance, intention to treat methods, survival analysis. 

PHST 625  Clinical Trials II  2 hours 
Protocol development; patient recruitment and retention; safety and efficacy; benefit to risk assessment; monitoring and auditing trials; terminating or extending clinical trials; and, regulatory, patent and legal considerations. 

PHST 626  Clinical Trials Statistics Laboratory  1 hour 
Statistical methods described in Clinical Trials I will be demonstrated and taught with handson examples and homework problems. Methods covered include randomization methods, sample size calculations, poststratification, Phase II earlystopping designs, repeated measures analysis, survival analysis, and methods to avoid or reduce multiplicity. 

PHST 630  Applied Statistical Models  3 hours 
Topics will include linear and multiple regression, analysis of variance, analysis of covariance, logistic regression, survival analysis using Cox regression and repeated measures. 

PHST 631  Data Collection for Clinical Research  3 hours 
Design of data collection instruments for clinical research and the psychometric properties of measurement instruments with coverage of REDCap and SPSS. 

PHST 640  Statistical Methods for Research Design in Health Sciences  3 hours 
Statistical methods for clinical research and interpretation for the literature. 

PHST 645  Health Sciences Data Collection Instrumentation  3 hours 
Design of data collection instruments in the health sciences with extensive coverage of psychometric and biometric properties of measurement instruments. Usage of the Epi Info and SPSS software packages for data collection and analysis. 

PHST 650  Advanced Topics in Biostatistics  3 hours 
A treatment of one or more topics in advanced biostatistics not usually covered in a regularly offered course. 

PHST 660  Mathematical Tools  3 hours 
This course focuses on the basic techniques of analytic geometry, differential and integral calculus, and matrix algebra; topics include limits, the chain rule, higherorder derivatives, partial derivatives, integration by parts, improper integrals, multiple integrals, sequences and series, vector and matrix arithmetic, and eigenvalues. 

PHST 661  Probability  3 hours 
This course in introductory probability theory; includes probability spaces, random variables, probability distributions, moments, moment generating functions, mathematical expectation, joint distribution, transformations of random variables, sampling distributions. 

PHST 662  Mathematical Statistics  3 hours 
This course in introductory statistical theory; includes limiting distributions, central limit theorem, point estimation, maximum likelihood estimation, least squares, sufficiency and completeness, confidence intervals, Bayesian estimation, NeymanPearson theory of hypothesis testing, statistical power, uniformly most powerful tests, likelihood ratio tests, noncentral distributions, advanced topics as time permits. 

PHST 666  Master's Thesis Research  16 hours 
Mentored research; M.S. thesis preparation. 

PHST 671  Special Topics in Biostatistics  13 hours 
A treatment of one or more topics in advanced Biostatistics not usually covered in a regularly offered course. May be repeated under different subtitles. 

PHST 675  Independent Study in Biostatistics  13 hours 
Course allows students to pursue advanced study with faculty guidance on a topic related to biostatistics. 

PHST 680  Biostatistical Methods I  3 hours 
A mathematically sophisticated presentation of principles and methods of: exploratory data analysis; statistical graphics; point estimation; interval estimation; hypothesis testing of means, proportions and counts; chisquare analysis; rate ratio; and MantelHaensel analysis. Matrix algebra is required. Data sets will be analyzed using statistical computer packages; examples will be drawn from the biomedical and public health literature. Emphasis will be placed on methods and models most useful in clinical research. 

PHST 681  Biostatistical Methods II  3 hours 
A mathematically sophisticated introduction to: general linear models; regression; correlation; analysis of covariance; one and twoway analysis of variance; and multiple comparisons. Matrix algebra is required. Data sets will be analyzed using statistical computer packages; examples will be drawn from the biomedical and public health literature. Emphasis will be placed on methods and models most useful in clinical research. 

PHST 682  Multivariate Statistical Analysis  3 hours 
Focuses on the multivariate statistical methods; topics include the multivariate normal distribution, inference for mean vectors; inference for covariance and correlation matrices, analysis of covariance structure, analysis of serial measurements, factor analysis, and discriminant analysis. Instruction will also be given in the proper use of software to carry out these analyses. Emphasis will be placed on methods and models most useful in clinical research. 

PHST 683  Survival Analysis  3 hours 
Focuses on statistical methods for analyzing survival data, including both parametric and nonparametric methods. Topics include lifetable analysis, proportional hazard models, logrank tests, parametric survival distributions, graphical methods, and goodness of fit tests. Emphasis will be placed on methods and models most useful in clinical research. 

PHST 684  Categorical Data Analysis  3 hours 
Focuses on statistical methods for analyzing categorical data; topics include inference for twoway contingency tables; models for binary response variables, including logistic and logit models; models for ordinal data; mutinominal response data; and analysis of repeated categorical response data. Emphasis will be placed on methods and models most useful in clinical research. 

PHST 691  Bayesian Analysis  3 hours 
Focus on the use of Bayesian probability and statistics in scientific inference. The frequency and subjective interpretations of probability are explored, as well as probability and decision making. 

PHST 703  Biostatistical Consulting Practicum  13 hours 
Practical experience in biostatistical collaboration in which a student works with one or more investigators in the health sciences. 

PHST 704  Mixed Effect Models and Longitudinal Data Analysis  3 hours 
The course focuses on theory and application of linear and nonlinear mixed effect models, particularly, the application of mixed models to longitudinal data analyses. 

PHST 710  Advanced Statistical Computing I  3 hours 
This course will cover modern/classical statistical/biostatistical methods like smoothing techniques and data summaries, linear models, generalized linear models, modern nonlinear regression techniques, multivariate statistics using SPLUS/R and SAS. Several real data examples will be analyzed following the 4th edition of the book titled Modern Applied Statistics with S by Venables and Ripley. 

PHST 711  Advanced Statistical Computing II  3 hours 
The course covers advanced topics in statistical computing, with an emphasis on biostatistical applications. Topics include matrix factorization, methods, numerical optimization, the EM algorithm, random number generation, Monte Carlo techniques, simulation, randomization and resampling methods, bootstrapping, and recursive partitioning. Computer programming will be conducted using MATLAB,R, and SAS IML. 

PHST 724  Advanced Clinical Trials  3 hours 
Advanced statistical methods for design and analysis of clinical trials. Content includes analysis of complex clinical trial designs, including poststratification, crossover, phases I, II, and III clinical trials. Sample size calculations will be covered. Interim analysis methods and sample size reestimation methods will be developed. 

PHST 725  Design of Experiments  3 hours 
The course introduces experimental design principles and covers specific designs in detail. Topics include the completely randomized design, the randomized complete block design, crossover designs, nested and hierarchical designs, factorial treatment arrangements, incomplete block designs, response surface methodology, and optimal designs. Concepts will be illustrated using examples from the health services. 

PHST 750  Statistics for Bioinformatics  3 hours 
Development of high throughout technologies has changed the face of biological sciences. The high dimensional complicated data generated from DNA sequences, genetic maps, and polymorphic marker data etc. help to unravel the mysteries of many biological processes. However, sophisticated statistical methods and computational tools are needed to analyze these data. This course will introduce basics of genetics and introduction of such data, knowledge of statistical inference and probability, Introduction to stochastic processes, Analysis of DNA and protein sequences, Hidden Markov models, Evolutionary models etc. This course is developed for individuals interested in pursuing research in computational biology, genomics, and bioinformatics. Students are expected to be familiar with some elementary statistics and probability concepts. 

PHST 751  Highthroughput Data Analysis  3 hours 
Highthroughput technology has changed the dimension of biotechnology. The array of highspeed, highly automated biotechnical equipment DNA sequencers, microarray (DNA, Protein), proteomic analyzers ( mass spectrometers) and cell sorters are all designed to capture and process vast amounts of biological data at high speeds. We will briefly discuss some of these technologies. Secondly, this course will concentrate with the process of microarray data mining (analysis) from beginning to end. In particular, this course will provide researchers and practitioners guidelines to use appropriate statistical methodology for experimental design, image processing, normalization, identifying differently expressed genes, clustering and classification techniques etc. Introduction to SPLUS/R library for the data analysis will also be attempted. 

PHST 752  Statistical Genetics  3 hours 
This course covers methods for mapping disease associated genes in human populations, including linkage, association, and quantitative trait analysis. Software and study design for gene mapping studies are also covered. 

PHST 762  Advanced Statistical Inference  3 hours 
This course is a mathematically sophisticated introduction to the theory and methods of statistical inference. Students will learn fundamental technical tools that are essential to carry out methodological research in the field of Biostatistics. Emphasis will be placed on how to correctly propose statistical methods in a general setting including concepts such as asymptotic unbiasedness, robust variance estimation and efficiency. 

PHST 777  Dissertation Research  112 hours 
Mentored research towards completion of the doctoral dissertation. 

PHST 780  Advanced Nonparametrics  3 hours 
A mathematically advanced introduction to theory and methods of nonparametric statistical methods. Course will be useful to students planning to analyze data that do not follow a standard parametric distribution. 

PHST 781  Advanced Linear Models  3 hours 
An introduction to the theory of linear models, with an emphasis on health sciences applications. Topic coverage includes projections, distributions of quadratic forms under normality, estimation procedures, general linear hypotheses, estimating and testing linear parametric functions, simultaneous inference, multifactor ANOVA models, hierarchical linear models, mixed effects models, and covariance parameter estimation methods. Examples will be illustrated using advanced statistical software. 

PHST 782  Generalized Linear Models  3 hours 
Advanced statistical methods using inference based on the exponential family of distributions. Relationship to linear and nonlinear regression. Theoretical development of link functions. Modelbuilding and assessment of goodnessoffit. Estimation and hypothesis testing. Correlated response methods using generalized estimating equations. 

PHST 783  Advanced Survival Analysis  3 hours 
This course is a mathematically advanced introduction to the theory and methods of survival analysis. This course will be useful for students planning to analyze complex event time data including multivariate survival and multistate data. Also it will be useful for students who are planning to carry out research in the general area of survival analysis. 

PHST 785  Nonlinear Regression  3 hours 
Advanced statistical methods for nonlinear models. Review of linear models and intrinsically linear models. Survey of generalized linear models. Development of nonlinear models, with an emphasis on uses in Phase I clinical trials, relationship to differential equations. Estimation and goodnessoffit. Sample size methods. 