Courses

STAT 2023. Biostatistics (Sp). 3 Hours.

An introductory course in biostatistics emphasizing methods for collecting, graphing, and understanding data. Special emphasis is placed upon available methods for both exploratory and confirmatory data analysis. Particular attention is given to statistical methods for data sets with discrete variables. Pre- or Corequisite: MATH 2554. Corequisite: Lab component.

STAT 2303. Principles of Statistics (ACTS Equivalency = MATH 2103) (Sp, Su, Fa). 3 Hours.

A problem-oriented course with applications from many fields. Emphasis on understanding the nature of statistical orderliness implied by probability laws. Statistical analysis is treated as a means of decision making in the face of uncertainty. Prerequisite: MATH 1203 or MATH 1204 each with a grade of C or better, or a score of at least 80% on the University of Arkansas Mastery of Algebra Exam, or a score of at least 26 on the math component of the ACT exam, or a score of at least 600 on the math component of the old SAT or 620 on the math component of the new SAT.

STAT 3013. Introduction to Probability (Sp, Su, Fa). 3 Hours.

A calculus-based introduction to probability. Discrete probability spaces and counting techniques, discrete and continuous probability distributions, random variables, random samples, law of large numbers, central limit theorem. Prerequisite: MATH 2564.

This course is cross-listed with MATH 3013.

STAT 4001L. Statistics Methods Laboratory (Sp, Fa). 1 Hour.

Introduction to the statistical software SAS, including its use for common statistical analyses. A practical complement to the statistical methodology covered in STAT 4003.

STAT 4003. Statistical Methods (Sp, Fa). 3 Hours.

Describing Data, Basic Probability, Random variables, Uniform, Normal and Binomial Distributions, Sampling Distributions, Confidence Intervals, Hypothesis testing, Correlation and Regression, Contingency table, Comparing two populations, ANOVA. Prerequisite: MATH 2554 or MATH 2554C.

STAT 4033. Nonparametric Statistical Methods (Sp, Su, Fa). 3 Hours.

Chi square tests. Kolmogorov-Smirnov goodness-of-fit tests, the Mann-Whitney and Wilcoxon 2-sampling tests, and various nonparametric measures of association. Prerequisite: STAT 2303 or STAT 2023 or departmental consent.

STAT 4043. Sampling Techniques (Sp, Su, Fa). 3 Hours.

Considers optimum techniques of simple random, stratified random, cluster, systematic and multistage sampling from finite populations subject to cost precision constraints. Wide range of applications. Prerequisite: STAT 4003.

STAT 405V. Internship in Professional Practice (Sp, Su, Fa). 1-3 Hour.

Professional work experience involving significant use of mathematics or statistics in business, industry or government. Prerequisite: Departmental consent. May be repeated for up to 3 hours of degree credit.

STAT 4101L. Introduction to R (Fa). 1 Hour.

A hands-on introduction to R software, a free and open-source computing environment used for data manipulation and analysis across a broad spectrum of subject areas. Intended for new users. Content begins with simple data manipulation, then complex data structures and common statistical procedures are covered.

STAT 4333. Analysis of Categorical Responses (Sp). 3 Hours.

Statistical tools to analyze univariate and multivariate categorical responses. Emphasis is given to Generalized Linear Models, including logistic regression and loglinear models. Prerequisite: STAT 4003 or departmental consent.

STAT 4373. Experimental Design (Sp). 3 Hours.

Topics in the design and analysis of planned experiments, including randomized block, Latin square, split plot, and BIB designs, use of fractional factorial replication, and repeated measures. Prerequisite: STAT 4003.

STAT 5103. Introduction to Probability Theory (Fa). 3 Hours.

Fundamentals of probability, distribution theory, and random variables; expected value, moments, and generating functions; classic parametric families of distributions; central limit theorems, inequalities, and laws of large numbers. Prerequisite: MATH 2574 and graduate standing in mathematics or statistics, or departmental consent.

STAT 5113. Statistical Inference (Sp). 3 Hours.

Statistical theory of estimation and testing hypothesis. Prerequisite: STAT 5103 and graduate standing in mathematics or statistics, or departmental consent.

STAT 5313. Regression Analysis (Sp). 3 Hours.

Review of matrix algebra, parameter estimation in linear models, regression diagnostics, collinearity, variable selection, nonparametric regression, Bayesian regression. Prerequisite: STAT 4003 or departmental consent.

STAT 5333. Analysis of Categorical Responses (Sp). 3 Hours.

Statistical tools to analyze univariate and multivariate categorical responses. Emphasis is given to Generalized Linear Models, including logistic regression and loglinear models. Prerequisite: STAT 4003 or departmental consent.

STAT 5343. Stochastic Processes (Sp, Su, Fa). 3 Hours.

Markov chains, branching processes, birth-death processes, queuing theory with application. Prerequisite: STAT 5103, and graduate standing in mathematics or statistics, or departmental consent.

STAT 5353. Methods of Multivariate Analysis (Sp). 3 Hours.

Statistical tools to analyze multivariate datasets. Topics include the multivariate linear model, principal component analysis, factor analysis, linear discriminant analysis, clustering, classification and regression trees, support vector machines, nonlinear dimensionality reduction. Prerequisite: STAT 5313, and graduate standing in mathematics or statistics, or departmental consent.

STAT 5383. Time Series Analysis (Sp, Su, Fa). 3 Hours.

Identification, estimation and forecasting of time series. Spectral analysis including the fast Fourier transform computational aspects are emphasized. Prerequisite: STAT 5103, and graduate standing in mathematics or statistics, or departmental consent.

STAT 5413. Spatial Statistics (Fa). 3 Hours.

Applied spatial statistics, covering univariate spatial modeling (kriging), multivariate spatial modeling (cokriging), methods of estimation and inference, and spatial sampling designs. Special relevance to remote sensing. Prerequisite: STAT 5313, and graduate standing in mathematics or statistics, or departmental consent.

STAT 5443. Computational Statistics (Sp). 3 Hours.

In-depth introduction to computer-based algorithms used for inference and forecasting. Course content may vary by semester. Possible algorithms covered could include: resampling methods (bootstrap), Markov chain Monte Carlo, variable selection in high-dimensional regression (LASSO and LARS), artificial neural networks, ensemble methods (boosting, bagging, random forests), and kernel methods. Prerequisite: STAT 5113 or departmental consent.

STAT 550V. Statistical Consulting (Sp, Su, Fa). 1-3 Hour.

Designed to give students a statistical consulting practicum. Students meet with clients, analyze data and prepare reports for the clients. May be repeated for up to 6 hours of degree credit.

STAT 610V. Research in Statistics (Irregular). 1-4 Hour.

Prerequisite: Graduate standing in mathematics or statistics, or departmental consent.

STAT 639V. Topics in Statistics (Irregular). 1-3 Hour.

Current state of the art on methodology in one of the topics: multivariate analysis, time series analysis, sequential analysis, factor analysis, or biostatistics. Prerequisite: Graduate standing in mathematics or statistics, or departmental consent. May be repeated for degree credit.