content

COURSE DESCRIPTIONS
STATISTICS
(STA)

1043 Introduction to Statistical Reasoning
(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 judgement 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
(3-0) 3 hours credit. Prerequisite: Satisfactory performance on placement examination.
Descriptive statistics; histograms; measures of location and dispersion; elementary probability theory; random variables; binomial and normal distributions; interval estimation and hypothesis testing; simple linear regression and correlation; and applications of the chi-square distribution. [TCCN: MATH 1342.]

1993 Statistical Methods for the Life and Social Sciences
(3-0) 3 hours credit. Prerequisites: STA 1053 or STA 2073 and MTC 1023 or MTC 1033 or an equivalent course.
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.

2073 Statistics for Psychology
(3-0) 3 hours credit. Prerequisites: MTC 1023, MTC 1033, or MTC 1073, and one psychology course.
The use of statistics in psychological research includes: elementary probability theory; descriptive statistics, including histograms, graphing, and measures of central tendency and dispersion; correlational techniques; binomial and normal distributions; and inferential statistics, including hypothesis testing, interval estimation, and analysis of variance. (Formerly STA 1073. Credit cannot be earned for both STA 2073 and STA 1073.)

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.

3013 Multivariate Analysis for the Life and Social Sciences
(3-0) 3 hours credit. Prerequisite: STA 1993, 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 computer library programs. Open to students of all disciplines.

3313 Introduction to Sample Survey Theory and Methods
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3513, or STA 3543.
Simple random sampling, stratified random sampling, ratio and regression estimates, systematic sampling, cluster sampling, unequal probability sampling, two-stage and multistage sampling, and nonsampling errors.

3433 Applied Nonparametric Statistics
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3523, or STA 3543.
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. Prerequisite: Completion of or concurrent enrollment in MAT 2213.
Axioms of probability, functions of random variables, important discrete and continuous distributions, sampling distributions, and Central Limit Theorem.

3523 Statistical Methods
(3-0) 3 hours credit. Prerequisite: STA 3513, STA 3533, or an equivalent. Point and interval estimation, hypothesis testing, and applied topics which may include chi-square tests, linear regression, and analysis of variance.

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 or STA 3523.
Methods especially useful for problems arising in the life and social sciences: analysis of count data, contingency tables, and Probit and Logit analysis.

4133 Introductory Data Analysis with Statistical Software
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3523, or STA 3543.
This course introduces statistical analysis of data sets using modern statistical packages such as SAS, SPSS, JMP, or EXCEL. Examples will be drawn from regression analysis, analysis of variance, and multivariate methods.

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 3523, 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 Design and Analysis of Experiments
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3523, 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.

4803 Statistical Quality Control
(3-0) 3 hours credit. Prerequisite: STA 1993, 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 Survival Analysis
(3-0) 3 hours credit. Prerequisite: STA 3523 or an equivalent.
Measures of survival, hazard function, mean residual life function, common failure distributions and a procedure for selecting an appropriate model, and the probabilistic approach to biomedical applications.

4913 Independent Study
3 hours credit. Prerequisite: Permission in writing (form available) from the instructor, the student's advisor, the Department Chair and 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.

4953 Special Studies in Statistics
(3-0) 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 78.)

text size– | + | R |