# STT

See a list of all STT courses. You can also:

### Statistics

## STT 1600 Statistical Concepts

Level:UndergraduateCredit Hours:4Schedule Type:LectureLabFundamentals of statistics, including descriptive statistics, probability, confidence intervals, and testing hypotheses, as well as the basics of Chi-square tests, regression and correlation, and analysis of variance. This course has a one hour per week lab that uses Excel software.

## STT 2640 Elementary Statistics

Level:UndergraduateCredit Hours:4Schedule Type:LectureNumerical and graphical methods for finding and summarizing important features of data. Principles of designing experiments for collecting data. Introduction to probability. Confidence intervals and hypothesis testing introduction.

## STT 3420 Probability and Statistics for Middle School Teachers

Level:UndergraduateCredit Hours:3Schedule Type:LectureLabProbability and statistical methods applied to real problems. Scientific method of investigation. Data collection, organization, display, and analysis. Empirical and axiomatic probability, simulation, variation, sampling, expected values, and statistical inference.

## STT 3600 Applied Statistics I

Level:UndergraduateCredit Hours:3Schedule Type:LectureIntroduction to probability, random variables and their expectations, some commonly used discrete and continuous distributions, concept of random sampling and sampling distributions. Use of computer software packages for simulating, summarizing, and displaying data.

## STT 3610 Applied Statistics II

Level:UndergraduateCredit Hours:3Schedule Type:LectureIntroduction to statistics, standard statistical methods for estimation of parameters and hypothesis testing, introduction to regression analysis and analysis of variance techniques, exposure to data analysis using packaged computer programs.

## STT 3630 Engineering Statistics

Level:UndergraduateCredit Hours:3Schedule Type:LectureIntroduction to probability, distributions, and statistical methods; using calculus to develop the necessary theory. Use of computer software package (e.g., Matlab) for statistical analysis.

## STT 3860 Independent Reading in Statistics and Probability

Level:UndergraduateCredit Hours:1 to 4Schedule Type:Independent StudyTopics vary.

## STT 3960 Topics in Statistics and Probability

Level:UndergraduateCredit Hours:1 to 5Schedule Type:Independent StudyTitles vary.

## STT 4110 Applied Time Series

Level:UndergraduateCredit Hours:3Schedule Type:LectureStochastic models for discrete time series in the time-domain, moving average processes, autoregressive processes, model identification, parameter estimation, and forecasting. Statistical computing software packages are used.

## STT 4210 Sampling Design

Level:UndergraduateCredit Hours:3Schedule Type:LectureClassical sampling designs including simple random sampling, stratified sampling, multi-stage sampling, cluster sampling, and systematic sampling; using auxiliary information and ratio estimators; unequal probability sampling, detectability and line transect methods; compostite and ranked-set sam

## STT 4240 Statistical Quality Control and Improvement

Level:UndergraduateCredit Hours:3Schedule Type:LectureStatistical process control for attributes and variables data: probability distributions, sampling plans, control charts, statistical control, process capability, process improvement, tolerance intervals, evolutionary operation, and applications.

## STT 4260 Survival Analysis

Level:UndergraduateCredit Hours:3Schedule Type:LectureCensoring and truncation, survival and hazard functions, estimation and hypothesis tests, Cox proportional hazards model, diagnostics of the Cox model; state-of-the-art software for survival analysis models.

## STT 4300 Biostatistics

Level:UndergraduateCredit Hours:3Schedule Type:LectureThe statistical methods suitable for analysis of data arising in biological and related studies. Estimation and hypothesis testing are reviewed. Methods include one and two sample tests, simple and multiple regression, and analysis of variance.

## STT 4310 Statistical Methods for Clinical Trials

Level:UndergraduateCredit Hours:3Schedule Type:LectureBasic clinical design methodology, types of clinical trials, analysis of trial data, and statistical issues that commonly arise in clinical trials.

## STT 4610 Theory of Statistics I

Level:UndergraduateCredit Hours:4Schedule Type:LectureProbability, random variables, density and distribution functions, expectation, moment generating functions, special discrete and continuous distributions; joint, marginal and conditional distributions; independence, properties of expected values, functions of random variables, order statistics,

## STT 4620 Theory of Statistics II

Level:UndergraduateCredit Hours:4Schedule Type:LecturePoint estimation, properties of estimators, sufficiency and completeness, single paramater interval estimation, hypothesis testing, most powerful and UMP tests, likelihood ratio tests; the multivariate normal distribution, random vectors and covariance matrices; linear and quadratic forms.

## STT 4640 Computational Statistics

Level:UndergraduateCredit Hours:3Schedule Type:LectureRandom number generation and Monte Carlo methods. The bootstrap and permutation tests. Numerical methods for optimization related to maximum likelihood estimation; nonparametric density estimation, classification and regression trees. Software used for the course includes SPLUS or R.

## STT 4660 Statistical Methods I

Level:UndergraduateCredit Hours:4Schedule Type:LectureSimple linear regression and correlation analysis. Concepts of matrix algebra, the matrix approach for regression and multiple regression. The general linear model. An introduction to generalized linear models and logistic regression. One-way analysis of variance.

## STT 4670 Statistical Methods II

Level:UndergraduateCredit Hours:4Schedule Type:LectureContinuation of STT 4660. Randomization and replication. One and two-way analysis of variance, multiple comparisons, analysis of covariance. Multi-factor experiments. Non-parametric methods. Block designs. Mixed- and random-effects models, including repeated measures.

## STT 4860 Independent Reading in Statistics and Probability

Level:UndergraduateCredit Hours:1 to 4Schedule Type:Independent StudyIndependent study in statistics and probability.

## STT 4920 Undergraduate Statistics Seminar

Level:UndergraduateCredit Hours:3Schedule Type:SeminarDetailed study of a single statistics topic chosen by the student with the approval of the instructor. Integrated Writing course.

## STT 4960 Topics in Statistics and Probability

Level:UndergraduateCredit Hours:1 to 4Schedule Type:Independent StudyTopics in statistics and probability.

## STT 5600 Applied Statistics I

Level:GraduateCredit Hours:3Schedule Type:LectureIntroduces probability, random variables and their expectations, some commonly used discrete and continuous distributions, concept of random sampling and sampling distributions.

## STT 5610 Applied Statistics II

Level:GraduateCredit Hours:3Schedule Type:LectureIntroduces statistics, standard statistical methods for estimation of parameters and hypothesis testing, regression analysis and analysis of variance techniques, and exposure to data analysis using packaged computer programs.

**Department Managed Prerequisite(s): Graduate level STT 5600 Minimum**## STT 5860 Independent Reading in Statistics and Probability

Level:GraduateCredit Hours:1 to 4Schedule Type:Independent StudyIndependent reading in statistics and probability.

## STT 5910 Advanced Statistical Methods for Nursing Research

Level:GraduateCredit Hours:.5Schedule Type:LectureCoverage of concepts, principles, interpretation and practical rules of thumb for advanced statistical methods used in nursing research.

## STT 5960 Topics in Statistics and Probability

Level:GraduateCredit Hours:1 to 4Schedule Type:Independent StudyMay be taken for letter grade or pass/unsatisfactory. Titles vary.

## STT 6110 Applied Time Series

Level:GraduateCredit Hours:3Schedule Type:LectureStochastic models for discrete time series in the time-domain, moving average processes, autoregressive processes, model identification, parameter estimation, and forecasting.

## STT 6210 Sampling Design

Level:GraduateCredit Hours:3Schedule Type:LectureClassical sampling designs including simple random sampling, stratified sampling, multi-stage sampling, cluster sampling, and systematic sampling; Using auxiliary information and ratio estimators; Unequal probability sampling, detectability and line transect methods; composite and ranked-set samp

## STT 6240 Statistical Quality Control and Improvement

Level:GraduateCredit Hours:3Schedule Type:LectureStatistical process control for attributes and variables data: probability distributions, sampling plans, control charts, statistical control, process capability, process improvement, tolerance intervals, evolutionary operation, and applications.

**Department Managed Prerequisite(s): (Undergradu**## STT 6260 Survival Analysis

Level:GraduateCredit Hours:3Schedule Type:LectureCensoring and truncation, survival and hazard functions, estimation and hypothesis tests, Cox proportional hazards model; diagnostics of the Cox model; state-of-the-art software for survival analysis models.

**Department Managed Prerequisite(s): (Undergraduate level STT 3610 Minimum Grade of D o**## STT 6300 Biostatistics

Level:GraduateCredit Hours:3Schedule Type:LectureStatistical methods suitable for analysis of data arising in biological and related studies. Estimation and hypothesis testing are reviewed.

## STT 6310 Statistical Methods for Clinical Trials

Level:GraduateCredit Hours:3Schedule Type:LectureBasic clinical design methodology, types of clinical trials, analysis of trial data, and statistical issues that commonly arise in clinical trials.

**Department Managed Prerequisite(s): (Undergraduate level STT 3610 Minimum Grade of D or Graduate level STT 5610 Minimum Grade of D) or Graduate le**## STT 6460 Statistical Methods for Engineers

Level:GraduateCredit Hours:4Schedule Type:LectureClassical statistical techniques for analysis and interpretation of research data, with extensive use of statistical software. Includes review of basic statistics. Simple, multiple, and polynomial regression.

## STT 6610 Theory of Statistics I

Level:GraduateCredit Hours:4Schedule Type:LectureProbability, random variables, density and distribution functions, expectation, moment

## STT 6620 Theory of Statistics II

Level:GraduateCredit Hours:4Schedule Type:Lectureests, likelihood ratio tests, maximum likelihood estimation (mle) and computational approaches to determine mle's.

## STT 6640 Computational Statistics

Level:GraduateCredit Hours:3Schedule Type:LectureRandom number generation and Monte Carlo methods. The bootstrap and permutation tests. Numerical methods for optimization related to maximum likelihood estimation. Nonparametric density estimation. Monte Carlo Markov Chain (MCMC) methods. Classification and regression trees.

## STT 6660 Statistical Methods I

Level:GraduateCredit Hours:4Schedule Type:LectureSimple linear regression and correlation analysis. Concepts of matrix algebra, the matrix approach for regression and multiple regression. The general linear model. An introduction to generalized linear models. Single factor analysis of variance and multiple comparisons. Nonparametric methods.

## STT 6670 Statistical Methods II

Level:GraduateCredit Hours:4Schedule Type:LectureRandomization and replication. One and two-way analysis of variance, multiple comparisons, analysis of covariance.

## STT 6860 Independent Reading in Statistics and Probability

Level:GraduateCredit Hours:1 to 4Schedule Type:Independent StudyIndependent reading in statistics and probability.

## STT 6960 Topics in Statistics and Probability

Level:GraduateCredit Hours:1 to 4Schedule Type:Independent StudyTopics in statistics and probability.

## STT 7020 Applied Stochastic Processes

Level:GraduateCredit Hours:3Schedule Type:LectureStationary processes, Markov chains, Poisson processes, pure birth process, queuing processes, inventory problems, traffic flow problems, introduction to financial processes.

**Department Managed Prerequisite(s): Graduate level STT 6610 Minimum Grade of D**## STT 7140 Statistical Modeling for Environmental Data

Level:GraduateCredit Hours:3Schedule Type:LectureStatistical techniques for the modeling and analysis of environmental data including advanced regression techniques, generalized linear models, and random effects. Also modeling of spatial and time-series environmental data, including spatio-temporal analysis, using appropriate software.

## STT 7300 Advanced Topics in Biostatistics

Level:GraduateCredit Hours:3Schedule Type:LectureStatistical theory and analysis of data relating to advanced topic in biostatistical applications.

**Department Managed Prerequisite(s): Graduate level STT 6620 Minimum Grade of D and Graduate level STT 6670 Minimum Grade of D**## STT 7400 Categorical Data Analysis

Level:GraduateCredit Hours:3Schedule Type:LectureStandard techniques for analyzing and describing two-dimensional contingency tables. Logistic regression models and loglinear models developed for data structures involving categorical response variables, including model selection procedures, diagnostics,

## STT 7440 Applied Multivariate Analysis

Level:GraduateCredit Hours:3Schedule Type:LectureMatrix theory, multivariate distributions, likelihood ratio tests, MANOVA, principal component and factor analysis, canonical correlation analysis, finite mixture models and the EM algorithm, and classification techniques.

**Department Managed Prerequisite(s): (Undergraduate level MTH 2320 Minim**## STT 7620 Advanced Topics in Linear Models

Level:GraduateCredit Hours:3Schedule Type:LectureThe generalized linear model. Logistic and Poisson regression, multinomial responses, log-linear models and contingency tables. Maximum likelihood estimation. Model selection, diagnostics. Generalized linear mixed effects models and repeated measurements.

## STT 7670 Applied Regression Analysis

Level:GraduateCredit Hours:3Schedule Type:LectureMultiple linear regression with introduction to more complicated models, including nonlinear models and weighted least squares. Up-to-date computing techniques including nonparametric regression techniques.

**Department Managed Prerequisite(s): Graduate level STT 6660 Minimum Grade of D**## STT 7860 Independent Reading in Statistics and Probability

Level:GraduateCredit Hours:1 to 4Schedule Type:Independent StudyIndependent reading in statistics and probability.

## STT 7910 Statistical Consulting

Level:GraduateCredit Hours:2 to 3Schedule Type:PracticumConsultation with graduate students and faculty on statistical problems arising from research projects.

**Department Managed Prerequisite(s): (Graduate level STT 6620 Minimum Grade of D and Graduate level STT 6670 Minimum Grade of D)**## STT 7920 Biostatistical Consulting

Level:GraduateCredit Hours:2 to 3Schedule Type:PracticumConsultation with clients on biostatistical problems, under the direct supervision of a professional statistical consultant.

**Department Managed Prerequisite(s): Graduate level STT 6620 Minimum Grade of D and Graduate level STT 6670 Minimum Grade of D**## STT 7960 Topics in Statistics and Probability

Level:GraduateCredit Hours:1 to 4Schedule Type:Independent StudyTopics in statistics and probability.

## STT 8990 Graduate Research

Level:GraduateCredit Hours:1 to 12Schedule Type:Independent StudySupervised thesis research.