Statistics Courses (STAT)

STAT 1772. Introduction to Statistical Methods — 3 hrs.

Descriptive statistics including correlation and curve fitting. Intuitive treatment of probability and inferential statistics including estimations and hypothesis testing. No credit for students with credit in STAT 1774. Students with credit in STAT 3770 should not enroll in STAT 1772. Prerequisite(s): Satisfactory score on ALEKS exam. (Fall, Spring, Summer)

STAT 1774. Introductory Statistics for Life Sciences — 3 hrs.

Descriptive statistics, basic probability concepts, confidence intervals, hypothesis testing, correlation and regression, elementary concepts of survival analysis. No credit for students with credit in STAT 1772. Prerequisite(s): Satisfactory score on ALEKS exam. (Variable)

STAT 1780. Introduction to Data Science — 3 hrs.

Data acquisition, management, and visualization; selected methodologies of machine learning; applications and model evaluation; implementation in R; ethical issues in data science. Prerequisite(s): ALEKS Score of >50%. (Spring)

STAT 3751. Probability and Statistics — 3 hrs.

Descriptive statistics and graphical representations, basic concepts of probability and distributions, random variables, expectations, sampling theory, tests of statistical significance. Specific attention devoted to the use of technology in motivating and explaining concepts and techniques. (Same as MATH 3751) (Spring)

STAT 3752/5752. Introduction to Probability — 3 hrs.

Axioms of probability, sample spaces having equally likely outcomes, conditional probability and independence, random variables, expectation, moment generating functions, jointly distributed random variables, weak law of large numbers, central limit theorem. Prerequisite(s): MATH 1421; junior standing. (Same as MATH 3752/5752) (Fall and Spring)

STAT 3771/5771. Applied Statistical Methods for Research — 3 hrs.

Inference about two or more population variances, multiple comparisons, categorical data analysis, linear and logistic regression, design of experiments, analysis of variance and covariance, repeated measures and random effects. Prerequisite(s): STAT 1774 or STAT 1772; junior standing. (Spring)

STAT 3775/5775. Introduction to Mathematical Statistics — 3 hrs.

Sampling distribution theory, point and interval estimation, Bayesian estimation, statistical hypotheses including likelihood ratio tests and chi-square tests, selected nonparametric methods. Prerequisite(s): MATH 3752/5752; junior standing. Prerequisite(s) or corequisite(s): MATH 2422. (Spring)

STAT 3776/5776. Regression Analysis — 3 hrs.

Regression analysis, analysis of variance, time series methods. Prerequisite(s): STAT 3775/5775; junior standing. (Fall)

STAT 3778/5778. Spatial Data Analysis — 3 hrs.

Analysis and interpretation of spatial point processes, area, geostatistical and spatial interaction data. Applications to geographic data in real estate, biology, environmental, and agricultural sciences using S-Plus software. Prerequisite(s): STAT 1774 or STAT 1772 or SOC SCI 2020; junior standing. (Same as GEOG 3778/5778) (Odd Springs)

STAT 4772/5772. Statistical Computing I — 3 hrs.

Data management, graphical techniques and data analysis, computationally-intensive methods in statistics including Regression, Logistic Regression and Analysis of Variance. Emphasis on the use of statistical software such as SAS, SPSS, S-Plus, and R. Prerequisite(s): STAT 1774 or STAT 1772; junior standing. (Fall)

STAT 4773/5773. Design and Analysis of Experiments — 3 hrs.

Planning and organizing experiments, one-factor experiments, randomized blocks, Latin squares and related designs, factorial designs and fractional factorial designs, response surface methodology, nested and split-plot designs. Prerequisite(s): STAT 3771/5771 or consent of instructor; junior standing. (Spring)

STAT 4777/5777. Statistical Quality Assurance Methods — 3 hrs.

Exploratory data analysis, Shewhart control charts and their variations, process capability analysis, CUSUM charts, EWMA charts, sampling inspection by attributes and by variables, continuous sampling plans, application of design of experiments in quality engineering. Prerequisite(s): MATH 3752/5752 or consent of instructor; junior standing. (Variable)

STAT 4779/5779. Applied Multivariate Statistical Analysis — 3 hrs.

Multivariate normal distribution, tests of significance with multivariate data, discrimination and classification, clustering, principal components, canonical correlations, use of statistical computer packages. Prerequisite(s): MATH 2500; STAT 3775/5775; junior standing. (Variable)

STAT 4782/5782. Statistical Computing II — 3 hrs.

Computationally-intensive methods in statistics including Multivariate and Categorical analyses. Emphasis on the use of statistical software such as SAS, SPSS, S-Plus, and R. Prerequisite(s): STAT 4772/5772; Junior Standing. (Variable)

STAT 4784/5784. Introduction to Machine Learning — 3 hrs.

Models and Algorithms for Classification: k-NN, Decision Trees, Neural Networks, Logistic Regression, Naive Bayes and Bayesian Networks, Support Vector Machines; Clustering: Hierarchical and k-Means, Kohonen Networks, Association Rules and Segmentation, Model Evaluation Techniques; Ensemble Methods: Bagging and Boosting. Prerequisite(s): CS 1510 or STAT 4772/5772; STAT 1772; junior standing; consent of instructor. (Fall)

STAT 4786/5786. Statistics for Risk Modeling — 3 hrs.

Statistical learning, generalized linear models, time series models, decision trees, principal components. Prerequisite(s): STAT 3775/5775 or consent of instructor; junior standing. (Fall)

STAT 6746. Probabilistic Operations Research — 3 hrs.

Decision making under uncertainty, Markov chains, deterministic and probabilistic dynamic programming, inventory control, production scheduling, supply chain management, portfolio optimizations. Prerequisite(s): MATH 2422; MATH 2500; MATH 3752/5752. (Same as MATH 6746) (Fall and Spring)

STAT 6747. Discrete-Event System Simulation — 3 hrs.

Discrete-event systems simulation theory including input analysis, output analysis; applications of simulation software ARENA to studying performances of systems such as bank services, call centers, material-handling systems, and computer networks. Prerequisite(s): MATH 2422; STAT 1772. (Same as MATH 6747) (Fall and Spring)

STAT 6748. Modeling Industrial Systems Using Queueing Networks — 3 hrs.

Queueing networks, applications to modeling and evaluating industrial systems such as flexible manufacturing systems, pull-type production systems, polling systems in computer networks, handoff schemes in cellular mobile networks; computational package MATLAB. Prerequisite(s): MATH 2422; MATH 2500; MATH 3752/5752. (Same as MATH 6748) (Fall and Spring)

STAT 6772. Advanced Statistical Methods — 3 hrs.

Categorical data analysis, logistic and Poisson regression, forecasting, repeated measures, classification and discriminant analysis, cluster analysis, data mining. Prerequisite(s): STAT 4773/5773. (Variable)

STAT 6779. Topics in Probability and Statistics — 3 hrs.

Topics from correlation and regression analysis, analysis of variance and co-variance, non-parametric methods, order statistics. May be repeated on different topic with consent of instructor. Prerequisite(s): consent of instructor. (Same as MATH 6779) (Variable)