- STAT102 - Basics of Data Science
(University Core Curriculum) This course addresses the fundamental challenge of how to extract information from data. It focuses on a set of problems from statistics and data science such as describing the relationship between observations, testing hypotheses, estimating confidence, and prediction. Prerequisite: High School Algebra, some computer experience.
Credit Hours: 3
- STAT282 - Introduction to Statistics
(University Core Curriculum Course) (Same as MATH 282) Designed to introduce beginning students to basic concepts, techniques, and applications of statistics. Topics include the following: organization and display of data, measures of location and dispersion, elementary probability, statistical estimation, and parametric and nonparametric tests of hypotheses. Prerequisite: MATH 108 with a grade of C or better. Satisfies University Core Curriculum Quantitative Reasoning requirement in lieu of 110 or 101.
Credit Hours: 3
- STAT403 - Basic Short-Term Actuarial Mathematics
This course examines loss models including severity models, aggregate loss, estimation, ratemaking and reserving, and estimation. This course prepares students for Exam FAM-S. Prerequisite: STAT 483 with a grade of C or better. Credit Hours: 3.
Credit Hours: 3
- STAT473 - Reliability and Survival Models
(Same as MATH 473) Introduction to statistical analysis of data on lifetime, including hazard functions and failure distributions; estimation and hypothesis testing in life testing experiments with complete as well as censored data. Prerequisite: MATH 480 or MATH 483 or STAT 483 with a grade of C or better.
Credit Hours: 3
- STAT474 - Time Series
(Same as MATH 474) An introduction to time series: AR, MA and ARIMA models; estimation, time series models. Prerequisite: MATH 480 or STAT 480 or MATH 483 or STAT 483 with a grade of C or better.
Credit Hours: 3
- STAT480 - Probability, Stochastic Processes and Applications I
Introduction to the central topics of modern probability including elementary stochastic processes; random variables and their properties; sum of independent random variables and the Central Limit Theorem; random walks; discrete time finite state Markov chains; applications to random number generators and image and signal processing. Also generating functions, conditional probability, expectation, moments. Prerequisite: MATH 250 with a grade of C or better.
Credit Hours: 3
- STAT483 - Mathematical Statistics in Engineering and the Sciences
(Same as MATH 483) Develops the basic statistical techniques used in applied fields like engineering, and the physical and natural sciences. Principal topics include probability; random variables; expectations; moment generating functions; transformations of random variables; point and interval estimation; tests of hypotheses. Applications include one-way classification data and chi-square tests for cross classified data. Prerequisite: MATH 250 with a grade of C or better.
Credit Hours: 4
- STAT484 - Applied Regression Analysis and Experimental Design
(Same as MATH 484) Introduction to linear models and experimental design widely used in applied statistical work. Topics include linear models; analysis of variance; analysis of residuals; regression diagnostics; randomized blocks; Latin squares; factorial designs. Applications include response surface methodology and model building. Computations will require the use of a statistical package such as SAS. Prerequisite: MATH 221, and either MATH 483 or STAT 483, with grades of C or better.
Credit Hours: 3
- STAT485 - Applied Statistical Methods
(Same as MATH 485) Introduction to sampling methods and categorical data analysis widely used in applied areas such as a social and biomedical sciences and business. Sampling methods topics include: simple random and stratified sampling; ratio and regression estimators. Categorical data analysis topics include: contingency tables; loglinear models; logistic regression; model selection; use of a computer package. Prerequisite: MATH 483 or STAT 483 with a grade of C or better.
Credit Hours: 3
- STAT486 - Statistical Computing
(Same as MATH 486) This course covers Statistical Computing Software packages such as R and SAS; helps prepare students for SAS certification. Topics include obtaining and analyzing output for regression, experimental design, and generalized linear models. Prerequisites: MATH 484 or STAT 484, and CS 202 both with a grade of C or better.
Credit Hours: 3