Courses of Instruction

STA 215 Introductory Applied Statistics. A technique-oriented approach to statistical problems with emphasis on applications. Descriptive statistics, probability distributions, estimation, testing hypotheses, t-test, regression and correlation, chi-square tests, one-way analysis of variance. A statistical software package will provide computational assistance.

Prerequisite: MTH 110 or equivalent. Fulfills Mathematical Sciences Foundation. Three credits. Offered every semester.

 

STA 216 Intermediate Applied Statistics. Project-oriented introduction to major statistical techniques using a statistical package such as SAS or SPSS. Hypothesis testing, t-test, multivariate regression, analysis of variance, analysis of covariance, chi-square tests, nonparametric statistics.

Prerequisite: 215 or 312. Three credits. Offered fall and winter semesters.

 

STA 310 Introduction to Biostatistics. An introduction to the statistical methods commonly encountered in medical, biological, and health science problems using a statistical package such as SAS or SPSS. Longitudinal data analysis, repeated measures ANOVA, Friedman test, categorical data analysis, odds ratios, sensitivity and specificity, McNemars test, logistic regression, survival analysis, and reliability.

Prerequisite: 216. Three credits. Offered winter semesters on sufficient demand.

 

STA 311 Introduction to Survey Sampling. A project-oriented overview of topics related to survey sampling. Topics include sampling and non-sampling errors, questionnaire design, non-probability and probability sampling, commonly used sampling methods (e.g., simple random, stratified, systematic, cluster), estimating population sizes, and random response models. SAS or a sampling package software will be used.

Prerequisite: 216. Three credits. Offered winter semesters.

 

STA 312 Probability and Statistics. Introduction to the basic concepts of probability and statistics using calculus; discrete and continuous probability distributions, sampling, estimation, confidence intervals, tests of hypotheses, regression and correlation, applications, and problem solving.

Prerequisite: MTH 201. Three credits. Offered fall and winter semesters.

 

STA 313 Probability and Stochastic Processes. Introduction to probability and stochastic processes for engineering applications. Topics include probability models in electrical and computer engineering, probability theory, random variables, stochastic processes, random signal processing, renewal processing, and Markov chains.

Prerequisites: MTH 202 and either STA 215 or EGR 103. Co-requisite: MTH 302 or MTH 227. Three credits. Offered winter semester.

 

STA 314 Statistical Quality Methods. Statistical techniques applicable to problems of product quality. Methods and philosophy of statistical process control such as reduction of random variability, control charts, and process capability studies. Modern methods for quality control and improvement, including online and off-line procedures. Various management philosophies of quality improvement. Applications and projects.

Prerequisite: 215 or EGR 103. Three credits. Offered fall and winter semesters.

 

STA 315 Design of Experiments. Application-oriented overview of designed experiments. Students will learn about planning and conducting experiments and about analyzing the resulting data using a major statistical package. Simple comparative experiments concerning means and variances, experiments with single or multiple factors, factorial designs, and response surface methodology.

Prerequisite: 216 or 312 or 314. Three credits. Offered fall semesters.

 

STA 317 Nonparametric Statistical Analysis. Applied statistical analysis when the distributions of the populations are unknown. Students will learn how to test for location, test for distributions, compare populations, and calculate measures of association. A statistical software package will be used.

Prerequisite: 216. Three credits. Offered winter semesters on sufficient demand.

 

STA 318 Statistical Computing. A detailed study of the advanced features of major statistical packages used in statistical computing, such as SAS and SPSS. Emphasis on the data entry, data manipulation, data storage, data simulation, and graphical display features of these packages.

Prerequisite: 215. Three credits. Offered on sufficient demand.

 

STA 319 Statistics Project. Students will learn a systematic approach to statistical consulting, how to communicate with nonmathematical audiences, and develop the ability to apply appropriate statistical techniques to research questions. Actual experience with current university and industry research projects and SAS/SPSS is given.

Prerequisite: 216. Three credits. Offered winter semesters.

 

STA 321 Applied Regression Analysis. Multivariate regression analysis with emphasis on application using a statistical software package. Topics include method of least squares, residual analysis, collinearity, data transformation, polynomial regression, general linear model, selecting a best regression model, and logistic regression.

Prerequisite: 216. Three credits. Offered fall semesters on sufficient demand.

 

STA 345 Statistics in Sports. An application-oriented overview of the statistical methodology that can be utilized to describe and evaluate the performance of individuals or teams participating in sports. Emphasis will be on data collection, descriptive statistics, and statistical inference and modeling utilized in sports. Fulfills one of the Issues/Themes requirements.

Prerequisite: STA 215 or STA 312. Three credits. Offered fall and winter semesters.

 

STA 380 Special Topics. Readings, lecture, discussions, or lab (or any combination) in specific statistics topics.

Prerequisites depend upon topic selected. Permission of the instructor required. One to three credits. Offered on sufficient demand.

 

STA 412 Mathematical Statistics I. A theoretical study of the following topics: sample space, conditional probability, independence, Bayes Theorem, Bernoulli Trials, discrete and continuous random variables and their distributions, Chebyshev's inequality, joint distribution, expectation, variance, and moment generating functions.

Prerequisite: either 215 or 312, and MTH 202. Four credits. Offered fall semester.

 

STA 415 Mathematical Statistics II (capstone). A theoretical study of the following topics: the Law of Large Numbers, the Central Limit Theorem, the nature of statistical inference, tests of hypotheses, sampling theory, point and interval estimation, linear models, analysis of categorical data, and distribution-free methods.

Prerequisites: 412 and MTH 227. Four credits. Offered winter semester.

 

STA 416 Multivariate Data Analysis. Multivariate analysis with emphasis on application using a statistical package such as SAS or SPSS. Topics include principal components analysis, factor analysis, discriminant analysis, logistic regression, cluster analysis, multivariate analysis of variance, and canonical correlation analysis.

Prerequisites: 216. Three credits. Offered fall semesters on sufficient demand.

 

STA 421 Bayesian Data Analysis. An introduction to Bayesian data analysis utilizing the Gibbs Sampler and Metropolis-Hastings algorithm (Markov Chain Monte Carlo method). Estimating posterior distribution parameters, evaluating model effectiveness, hypothesis testing and bivariate regression modeling. Appropriate computer programs will be used for analysis of real data sets.

Prerequisite: 412. Three credits. Offered winter semesters on sufficient demand.

 

STA 490 Statistics Internship. Internship in a statistical situation with individual faculty supervision to allow students to apply academic knowledge to actual and professional experiences. Graded credit/no credit.

Prerequisite: Junior status and permission of the instructor. Offered fall and winter semesters. One to three credits.

 

STA 499 Independent Study and Research. Independent research in an area of interest to the students, supervised by a member of the statistics faculty. Hours, credits, topics, and time to be arranged by the student in conference with professor. Approval of the department required. One to three credits. Offered fall and winter semesters.

 

STA 513 Probability and Statistics for Engineers. Application-oriented introduction to topics in probability and statistics commonly encountered in engineering. Descriptive statistics, discrete and continuous probability distributions, sampling distributions, estimation of and hypothesis testing for parameters, and linear regression analysis.

Prerequisites: MTH 201 and either STA 215 or EGR 103. Two credits. Offered the second half of fall semesters on sufficient demand.

 

STA 580 Selected Topics. Readings, lecture, discussions, or labs (or any combination of these) in special topics in statistics or biostatistics.

Prerequisites: Depends on the topic. One to four credits.

 

STA 610 Applied Statistics for Health Professions. Project-oriented overview of major statistical techniques commonly used in problems encountered in health professions. Students will learn to use a major statistical computing package. Hypothesis testing, t-tests, regression, analysis of variance, analysis of covariance, categorical data analysis, nonparametric statistics.

Prerequisite: 215 or equivalent. Three credits. Offered fall, winter, and summer semesters.

 

STA 615 Design of Experiments for Engineers. Application-oriented overview of designed experiments commonly encountered in engineering. Students will learn about planning and conducting experiments and about analyzing the resulting data using a major statistical package. Simple comparative experiments concerning means and variances, experiments with single or multiple factors, factorial designs, Taguchi designs, and response surface methodology.

Prerequisites: 513 or 312 or 314. Three credits. Offered winter semesters on even numbered years.

 

STA 616 Statistical Programming. Provides intensive instruction in the use of SAS to prepare data for statistical analysis. Topics include: importing/exporting data in various formats; character and numeric manipulation; merging, setting and combining datasets; effective programming skills using arrays, loops and macros; creating graphs; producing reports.

Prerequisites: 610 or 622. Three credits. Offered winter semesters.

 

STA 621 Design of Experiments and Regression. Design and analysis of single- and multiple-factor experiments. Includes block designs, repeated measures, factorial and fractional factorial experiments, response surface experimentation. Techniques include simple and multiple linear regression, repeated measures, generalized linear models, correlation, model building diagnosis. Applications in biological and biomedical problems. A computer package will be used.

Prerequisite: 616. Four credits. Offered winter semesters.

 

STA 622 Statistical Methods for Biologists. Design of experiments and application of statistical techniques commonly used by biologists. Emphasis on techniques for count data, correlation and regression, analysis of variance, multivariate analysis, and nonparametric methods using biological data. A computing package will be utilized throughout the course.

Prerequisites: 215. Three credits. Offered fall semesters.

 

STA 623 Categorical Data Analysis. A study of regression models for the analysis of categorical data: logistic, probit and complementary log-log models for binomial random variables; log-linear models for cross-classification of counts; regression models for Poisson rates; and multinomial responses models for both nominal and ordinal responses. Model specification and interpretation are emphasized.

Prerequisite: 616. Two credits. Offered fall semesters.

 

STA 625 Clinical Trials. This course is designed for individuals with a quantitative background who are interested in the scientific, policy, design and management aspects of clinical trials. Topics include types of treatment allocation and randomization, patient recruitment and adherence, power and sample size, interacting with monitoring committees, administering multicenter trials, and study closeout.

Prerequisites: 610 and one of the following: PSM 650, SHP 610, BIO 610, HS 601, or NUR 690. Two credits. Offered winter semesters.

 

STA 630 Perspectives in Advanced Biostatistics. Reflecting on the knowledge and skills acquired throughout the biostatistics program and internship, this course examines the responsibilities of a professional biostatistician. This course will also examine current topics in biostatistics including survival analysis (including Kaplan-Meier estimation), sequential analysis of emerging data, bioequivalence, analysis of health surveys, and Bayesian methods.

Prerequisites: 621 and PSM 691. Three credits. Offered fall semesters.

 

STA 680 Special Topics. Readings, lecture, discussions, or labs (or any combination of these) in special topics in statistics or biostatistics.

Prerequisites: Depends on the topic. One to four credits.

 

STA 699 Independent Study. Independent research in an area of statistics or biostatistics that is of interest to the student and the supervising faculty member. Readings and discussions may be appropriate. Hours, credits, meeting times, and the topic(s) in statistics or biostatistics are determined by the student and faculty mentor. Departmental approval is required. One to four credits. Offered fall and winter semesters.

Page last modified March 13, 2014