STATISTICS (STA) COURSE DESCRIPTIONS
1043 Introduction to Statistical Reasoning [TCCN: MATH 1442.]
(3-0) 3 hours credit. Prerequisite: Satisfactory performance on placement examination.
Intended primarily for liberal arts majors, this course provides an overview of statistical methods useful for judgment and decision making under conditions of uncertainty. The emphasis of the course will be on using statistical reasoning to gain insight and draw conclusions from observations. The common pitfalls of statistical studies and common myths about the fallacies of inference will be discussed. Topics may include data analysis, inference, correlation, and regression.
1053 Basic Statistics [TCCN: MATH 1342.]
(3-0) 3 hours credit. Prerequisite: Satisfactory performance on placement examination.
Descriptive statistics; histograms; measures of location and dispersion; elementary probability theory; random variables; discrete and continuous distributions; interval estimation and hypothesis testing; simple linear regression and correlation; and applications of the chi-square distribution.
1404 Probability and Statistics for the Biosciences [TCCN: MATH 2442.]
(4-0) 4 hours credit. Prerequisite: MAT 1194 or an equivalent.
Probability and statistics from a dynamical perspective, using discrete-time dynamical systems and differential
equations to model fundamental stochastic processes such as Markov chains and the Poisson processes important
in biomedical applications. Specific topics to be covered include probability theory, conditional probability,
Markov chains, Poisson processes, random variables, descriptive statistics, covariance and correlations, the binomial distribution, parameter estimation, hypothesis testing and regression.
1993 Biostatistics
(3-0) 3 hours credit. Prerequisites: STA 1043, STA 1053 or PSY 2073 and MAT 1023 or MAT 1033 or an equivalent.
Point estimator properties, inference about the means and variances of two or more populations, categorical data analysis, linear regression, analysis of variance, and nonparametric tests. Open to students of all disciplines. (Formerly titled Statistical Methods for the Life and the Social Sciences.)
2303 Applied Probability and Statistics for Engineers
(3-0) 3 hours credit. Prerequisite: MAT 1223.
Fundamental concepts of probability and statistics with practical applications to engineering problems. Emphasis on sampling, statistical inference, measurement error analysis and quantifying risk, safety and reliability in engineering design.
3003 Applied Statistics
(3-0) 3 hours credit. Prerequisite: Completion or concurrent enrollment in MAT 1153, MAT 1203, MAT 1214, or an equivalent.
Data collection and experimental design; numeric and graphical displays of data; basic probability, Bayes’ Theorem, random variables, statistical concepts and models; tests of means and variances of two or more populations; simple simulations and inferences based on resampling; introduction to statistical computation packages and the development of writing, presentation, and evaluation skills.
3013 Multivariate Analysis for the Life and Social Sciences
(3-0) 3 hours credit. Prerequisite: STA 1993, STA 3003, STA 3513, or an equivalent.
Linear algebra preliminaries, the multivariate normal distribution, tests on means, discriminant analysis, cluster analysis, principal components, and factor analysis. Use of software packages will be emphasized. Open to students of all disciplines.
3313 Experiments and Sampling
(3-0) 3 hours credit. Prerequisite: MS 1023, PSY 3013, STA 1043, STA 1053, STA 2303, STA 3003, STA 3533, or STA 3543
Research techniques for collecting quantitative data: sample surveys, designed experiments, simulations, and observational studies; development of survey and experimental protocols; measuring and controlling sources of measurement error.
3433 Applied Nonparametric Statistics
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3003,
STA 3513, STA 3533, STA 3543, or equivalent.
Tests of location, goodness-of-fit tests, rank tests, tests based on nominal and ordinal data for both related and independent samples, and measures of association.
3513 Probability and Statistics
(3-0) 3 hours credit. Prerequisites: MAT 1223 and STA 3003.
Discrete and continuous distributions, moments and generating functions, bivariate and multivariate distributions and their applications. Functions of random variables, sampling distributions and the Central Limit Theorem.
3523 Mathematical Statistics
(3-0) 3 hours credit. Prerequisite: STA 3513 or an equivalent.
Confidence intervals, hypothesis testing, maximum likelihood estimation, moment estimators, Bayes’ estimates, linear and general linear models, including multiple regression and ANOVA.
3533 Probability and Random Processes
(3-0) 3 hours credit. Prerequisites: EE 3423 and either EGR 2323 or MAT 3253.
Probability, random variables, distribution and density functions, limit theorems, random processes, correlation functions, power spectra, and response of linear systems to random inputs.
3543 Statistics and Experimental Design for Computer Science
(3-0) 3 hours credit. Prerequisite: MAT 2213.
Elementary probability, random variables, binomial, Poisson, normal and exponential distributions, elementary queuing theory, sampling distributions, point and interval estimation, hypothesis tests, principles of experimentation.
3813 Discrete Data Analysis
(3-0) 3 hours credit. Prerequisite: STA 1993, STA 3003, STA 3513, STA 3533, or STA 3543.
Introduction to methods for analyzing discrete (categorical) data. Course emphasizes the uses and interpretations of the methods rather than the underlying theory. Topics include Two-way and Three-Way Contingency Tables, Partial Association, Cochran-Mantel-Haenszel Method, Generalized Linear models, Model Inference and Model Checking, Logistic Regression, Loglinear Models, and Models for Matched Pairs.
4133 Introduction to Programming and Data Management in SAS
(3-0) 3 hours credit. Prerequisite: Successful completion of a programming course is strongly recommended.
This course introduces essential programming concepts using SAS software, with a focus on data management and the preparation of data for statistical analysis. Topics include reading raw data, creating temporary and permanent datasets, manipulating datasets, summarizing data, and displaying data using tables, charts and plots. (Formerly titled Statistical Computing Packages.)
4143 Data Mining
(3-0) 3 hours credit. Prerequisites: STA 1993 or an equivalent, and STA 4133 or an equivalent.
Acquisition, organization, exploration, and interpretation of large data collections. Data cleaning, representation and dimensionality, multivariate visualization, clustering, classification, and association rule development. A variety of commercial and research software packages will be used.
4233 Statistical Programming Using SAS Software
(3-0) 3 hours credit. Prerequisites: STA 4133 or approval of instructor; and one of the following: MS 3313, PSY 3013, STA 1404, STA 1993, STA 2303, STA 3003, STA 3513, STA 3533, or STA 3543.
Analysis of datasets using the statistical software package SAS. Methods for analyzing continuous and categorical data will be introduced, using procedures from Base SAS, SAS/GRAPH and SAS/STAT software. Techniques for efficient programming will be stressed. Examples will be drawn from regression analysis, analysis of variance, categorical analysis, multivariate methods, simulation, and resampling.
4643 Introduction to Stochastic Processes
(3-0) 3 hours credit. Prerequisite: STA 3513.
Probability models, Poisson processes, finite Markov chains, including transition probabilities, classification of states, limit theorems, queuing theory, and birth and death processes.
4713 Applied Regression Analysis
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3003,
STA 3533, or STA 3543.
An introduction to regression analysis, with emphasis on practical aspects, fitting a straight line, examination of residuals, matrix treatment of regression analysis, fitting and evaluation of general linear models, and nonlinear regression.
4723 Introduction to the Design of Experiments
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3003,
STA 3533, or STA 3543.
General concepts in the design and analysis of experiments. Emphasis will be placed on both the experimental designs and analysis and tests of the validity of assumptions. Topics covered include completely randomized designs, randomized block designs, complete factorials, fractional factorials, and covariance analysis. The use of computer software packages will be stressed.
4753 Time-Series Analysis
(3-0) 3 hours credit. Prerequisite: STA 3513, STA 3533, or STA 3543, or an equivalent.
Development of descriptive and predictive models for time-series phenomena. A variety of modeling approaches will be discussed: decomposition, moving averages, time-series regression, ARIMA, and forecasting errors and confidence intervals.
4803 Statistical Quality Control
(3-0) 3 hours credit. Prerequisite: STA 1993, STA 2303, STA 3003, STA 3513, or an equivalent.
Statistical methods are introduced in terms of problems that arise in manufacturing and their applications to the control of manufacturing processes. Topics include control charts and acceptance sampling plans. (Same as MAT 4803. Credit cannot be earned for STA 4803 and MAT 4803.)
4903 Applied Survival Analysis
(3-0) 3 hours credit. Prerequisite: STA 1993, STA 3003, STA 3523, or an equivalent.
Measures of survival, hazard function, mean residual life function, common failure distributions, procedures for selecting an appropriate model, the proportional hazards model. Emphasis on application and data analysis using SAS.
4911-3 Independent Study
1 to 3 hours credit. Prerequisites: Permission in writing (form available) from the instructor, the student’s advisor, the Department Chair, and the Dean of the College in which the course is offered.
Independent reading, research, discussion, and/or writing under the direction of a faculty member. May be repeated for credit, but not more than 6 semester credit hours, regardless of discipline, will apply to a bachelor’s degree.
4951-3 Special Studies in Statistics
(1-0, 2-0, 3-0) 1 to 3 hours credit. Prerequisite: Consent of instructor.
An organized course offering the opportunity for specialized study not normally or not often available as part of the regular course offerings. Special Studies may be repeated for credit when the topics vary, but not more than 6 semester credit hours, regardless of discipline, will apply to a bachelor’s degree.
4993 Honors Thesis
3 hours credit. Prerequisites: STA 3523 and consent of instructor. Enrollment limited to students applying for Honors in Management Science and Statistics (see page 101).
Supervised research and preparation of an honors thesis. May be repeated once for credit with advisor’s approval.