Statistics (STAT)

1342. Elementary Statistics. (MATH 1342) 3(3-0)
Elementary description of tools of statistics inference, including empirical and theoretical distributions, probability, sampling, treatment of both continuous and discrete data, correlation, and applications to practical problems.
Prerequisite: MATH 1314 or MATH 1324.

2342. Statistical Analytics. 3(3-0)
Foundation course in statistical analysis, with emphasis on method and interpretation of results.  Review of
probability and common distributions, Sampling distributions of mean, proportion and variance, Central limit
theorem; Hypothesis testing: One sample and two sample tests (based on z and t distributions), confidence
interval, power of a test, sample size calculation, contingency table, chi-squared test, and introduction to
ANOVA. 
Prerequisite: Elementary Statistics (STAT 1342) or equivalent

3331. Introduction to NonParametric Statistics. 3(3-0)
Provides the basic foundation for non-parametric statistical methods which are distribution-free.  Focus on
methods and interpretation of results.  Course covers various measures of scales (nominal, ordinal, ratio
and interval) and overview of analyzing data having these scales of measurements using non-parametric
methods. Emphasis on one- and two-sample tests of locations using standard non-parametric methods such
as sign test, rank test, Wilcoxon test, Mann- Whiteney test, Kruscal-Walis test, etc..
Prerequisite: Elementary Statistics (STAT 1342) or equivalent

3332. Introduction to Data Analysis: SAS Certification Preparation. 3(3-0)
[Banner version: Intro to Data Analysis]
Designed to prepare student for Statistical Computing using SAS (Statistical Analysis Software).  Course
covers all of the objectives tested on the SAS Certification Exam (Base).  Major topics include importing
and exporting raw data files, creating and modifying SAS data sets.  Identifying and correcting data syntax,
programming logic errors, and some common PROCs.  After taking this course, students are encouraged to
take SAS Certification conducted by SAS institute.
Prerequisite: Elementary Statistics (STAT 1342) or equivalent

3344. Introduction to Applied Regression and Design of Experiments. 3(3-0)
[Banner Version: Intro to Regression and Design]
Introduction to basic methods of regression and the fundamental principles and techniques used in designing
experiments. Regression topics include introduction of correlation, regression, multiple regression, and
ANOVA, Diagnostics of regression models, Model selection: Forward selection, backward elimination, and
stepwise selection.  Design topics include statistical principles in the design and analysis of industrial
experiments, completely randomized, randomized complete and incomplete block, Latin square and
Plackett Burnam screening designs.
Prerequisite: Elementary Statistics (STAT 1342) or equivalent

4301. Biostatistics. 3(3-0)
For students in biology, health sciences, human sciences and wildlife science.  Descriptive and inferential statistics, basic probability concepts, probability distributions, estimation, hypothesis testing, correlation, simple linear regression, principles of epidemiology, statistical vs. clinical significance and quasi-statistical methods. 
Prerequisites: MATH 1314.

4303. Statistical Methods. 3(3-0)
Calculus-based probability, discrete and continuous random variables, joint distributions, sampling distributions, the central limit theorem, descriptive statistics, interval estimates, hypothesis tests, ANOVA, correlation and simple regression.
Prerequisite:  MATH 2414 

4350. Probability. 3(3-0)
Sample spaces, combinatorics, independence, conditional probability, and Bayes' rule. Discrete and continuous probability distribution, Chebychev's inequality, and limit theorems.
Prerequisite: MATH 3415.

4351. Mathematics Theory of Statistics. 3(3-0)
Sampling distributions, estimation properties and methods, testing hypothesis, power of tests and likelihood ratios.
Prerequisites:  STAT 4350 or the equivalent and 3 semester hours of advanced mathematics.

4390. Selected Topics in Statistics. 3(3-0)
Topics in statistics not adequately covered in other courses.  Course may be repeated for credit as topic changes.
Prerequisite:  3 semester hours of  advanced mathematics or statistics.

This page was last updated on: April 22, 2017