### STATISTICS

**STAT-099**

**Course Level:** Graduate

**STAT-196**

**Selected Topics: Non-recurring (1-6)**

**Course Level:** Undergraduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-202**

**Basic Statistics (4)**

**Course Level:** Undergraduate

Data presentation, display, and summary, averages, dispersion, simple linear regression, and correlation, probability, sampling distributions, confidence intervals, and tests of significance. Use of statistical software both to analyze real data and to demonstrate and explore concepts. Usually offered every term. Prerequisite: MATH-15x or higher. Note: students may receive credit for only one of STAT-202, STAT-203, or STAT-204.

**STAT-203**

**Basic Statistics with Calculus (4)**

**Course Level:** Undergraduate

A calculus-based introduction to basic statistics including data presentation, display and summary, correlation, development of least squares regression models, probability, independence, probability density functions, moments, use of moment generating functions, sampling distributions, confidence intervals, and tests of significance. Concepts are explored through simulation and the use of the calculus tools of finding maxima and minima of a function and the area under a curve. Usually offered every term. Prerequisite: MATH-221 or one semester of calculus. Note: students may receive credit for only one of STAT-202, STAT-203, or STAT-204.

**STAT-204**

**Introduction to Business Statistics (4)**

**Course Level:** Undergraduate

Statistical concepts and methods used in business decision making. Topics include probability rules, discrete and continuous distributions, descriptive and graphical statistics, estimation, confidence intervals, hypothesis testing, analysis of variance, regression, and applications of MS Excel data analysis tools to economic and business data. Usually offered every term. Grading: A-F only. Prerequisite: MATH-150, MATH-151, MATH-154, or MATH-155. Note: students may receive credit for only one of STAT-202, STAT-203, or STAT-204.

**STAT-294**

**Community Service-Learning Project (1)**

**Course Level:** Undergraduate

Grading: Pass/Fail only. Permission: instructor and Center for Community Engagement & Service.

**STAT-296**

**Selected Topics: Non-recurring (1-6)**

**Course Level:** Undergraduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-302**

**Intermediate Statistics (3)**

**Course Level:** Undergraduate

Methods include techniques for estimation and inference with qualitative and quantitative data focusing on simple linear and multiple regression, correlation, logistic regression, and analysis of variance. Usually offered every term. Prerequisite: STAT-202 or STAT-203 with a grade of C or higher. Note: students may receive credit for only one of STAT-302, STAT-320, or STAT-514.

**STAT-320**

**Biostatistics (3)**

**Course Level:** Undergraduate

This course examines how statistical methods are utilized within the fields of biology, medicine, and public health. Advanced statistical methods, including ANOVA, multiple regression, analysis of covariance, survival analysis, and nonparametric methods are discussed, with emphasis on their applicability to public health. Usually offered every spring. Prerequisite: STAT-202 or STAT-203. Note: students may receive credit for only one of STAT-302, STAT-320, or STAT-514.

**STAT-370**

**Introduction to Statistical Computing and Modeling (3)**

**Course Level:** Undergraduate

The basics of programming using the open source statistical program R. Data analysis, both numerical and qualitative, including graphical and formal inference. Applications include numerical methods, text mining, modeling, and simulation. Usually offered every spring. Prerequisite: MATH-221 and STAT-202 or STAT-203.

**STAT-390**

**Independent Reading Course in Statistics (1-6)**

**Course Level:** Undergraduate

Permission: instructor and department chair.

**STAT-394**

**Community Service-Learning Project (1)**

**Course Level:** Undergraduate

Grading: Pass/Fail only. Permission: instructor and Center for Community Engagement & Service.

**STAT-396**

**Selected Topics: Non-recurring (1-6)**

**Course Level:** Undergraduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-402**

**Introduction to Mathematical Statistics (3)**

**Course Level:** Undergraduate

Probability, probability distributions, sampling, sampling distributions, and introduction to the theory of point estimation and statistical inference, including confidence intervals and hypothesis testing. Usually offered every spring. Prerequisite: MATH-401.

**STAT-405**

**Introduction to Survey Sampling (3)**

**Course Level:** Undergraduate

This course introduces the basic approaches to surveys, including simple random, systematic, and stratified sampling. Also included is the design of questionnaires and the analysis of sample data. Emphasis is on the practical application of sampling. Meets with STAT-605. Usually offered alternate falls. Prerequisite: STAT-202, STAT-203, or STAT-514.

**STAT-415**

**Regression (3)**

**Course Level:** Undergraduate

Simple and multiple regression, least squares, curve fitting, graphic techniques, and tests and confidence intervals for regression coefficients. Meets with STAT-615. Usually offered every fall and summer. Prerequisite: STAT-302, STAT-320, or STAT-514.

**STAT-422**

**Advanced Biostatistics (3)**

**Course Level:** Undergraduate

Introduction to methodologies used to understand complex problems in four major areas of biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Phases of clinical trials, dynamics of epidemiology and disease, estimation of survival, hazard and mortality functions, and analysis of gene expression data are covered. Usually offered every fall. Meets with STAT-622. Grading: A-F only. Prerequisite: STAT-302, or STAT-320, or STAT-514.

**STAT-424**

**Data Analysis (3)**

**Course Level:** Undergraduate

An introduction to exploratory data analysis including graphical summaries, model assessment and selection, model inference and averaging, and data mining elements. Explores supervised statistical learning for regression and classification, unsupervised machine learning algorithms, and related topics. Meets with STAT-624. Usually offered every spring. Prerequisite: STAT-415.

**STAT-425**

**Statistical Software (3)**

**Course Level:** Undergraduate

Introduction to the use of the SAS language to prepare, modify, and analyze data, interpret output and final preparation of results. Emphasis on practical programming principles and use of built-in procedures. Comparisons with other programming languages. Meets with STAT-625. Usually offered every fall. Prerequisite: STAT-514 or two statistics courses.

**STAT-490**

**Independent Study Project in Statistics (1-6)**

**Course Level:** Undergraduate

Permission: instructor and department chair.

**STAT-491**

**Internship in Statistics (1-6)**

**Course Level:** Undergraduate

Permission: instructor and department chair.

**STAT-496**

**Selected Topics: Non-recurring (1-6)**

**Course Level:** Undergraduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-514**

**Statistical Methods (3)**

**Course Level:** Undergraduate/Graduate

Averages, dispersion, probability, sampling, and approach to normality; simple and multiple regression; tests and confidence intervals for means, proportions, differences, and regression coefficients; nonparametric statistics; and analysis of variance. Usually offered every term. Prerequisite: STAT-202 or STAT-203. Note: does not carry credit for graduate programs in mathematics or statistics; students may receive credit for only one of STAT-302, STAT-320, or STAT-514.

**STAT-516**

**Design of Experiments (3)**

**Course Level:** Undergraduate/Graduate

Design and analysis of the results of balanced experiments, simple analysis of variance, components of variance, analysis of covariance, and related subjects. Usually offered every spring. Prerequisite: STAT-302, STAT-320, or STAT-514.

**STAT-517**

**Special Topics in Statistical Methodology (3)**

**Course Level:** Undergraduate/Graduate

Topics vary by section, may be repeated for credit with different topic. Alternating topics in statistics from an applied viewpoint. Topics include sampling, multivariate techniques, factor analysis, and time series. Usually offered alternate summers (odd years). Prerequisite: STAT-302, STAT-320, or STAT-514.

**STAT-519**

**Nonparametric Statistics (3)**

**Course Level:** Undergraduate/Graduate

Application of nonparametric techniques in the analysis of social-science data, with emphasis on tests appropriate for data having interval, nominal, and ordinal scales. Usually offered alternate falls (even years). Prerequisite: STAT-302, STAT-320, or STAT-514.

**STAT-520**

**Applied Multivariate Analysis (3)**

**Course Level:** Undergraduate/Graduate

Introduction to multivariate analysis emphasizing statistical applications. Includes matrix theory, multivariate distributions, tests of hypotheses, multivariate analysis of variance, principal components, discriminant analysis, canonical correlation, multivariate regression, and related subjects. Usually offered alternate falls (odd years). Prerequisite: STAT-302, STAT-320, or STAT-514.

**STAT-521**

**Analysis of Categorical Data (3)**

**Course Level:** Undergraduate/Graduate

Chi-square tests, contingency tables (2 X 2, r X c, and multidimensional), loglinear models, and other special models. Usually offered alternate springs (even years). Prerequisite: STAT-302 or STAT-514.

**STAT-522**

**Time-Series Analysis (3)**

**Course Level:** Undergraduate/Graduate

An introduction to the theory of time-dependent data. The analysis includes modeling, estimation, and testing of data in the time domain using autoregressive and moving average models. Usually offered alternate springs (odd years). Prerequisite: STAT-415 or STAT-520 or STAT-615.

**STAT-584**

**Introduction to Stochastic Processes (3)**

**Course Level:** Undergraduate/Graduate

Introduction to random walks, Markov chains and processes, Poisson processes, recurrent events, birth and death processes, and related subjects. Usually offered alternate springs. Prerequisite: MATH-501 or STAT-530.

**STAT-590**

**Independent Reading Course in Statistics (1-6)**

**Course Level:** Undergraduate/Graduate

Permission: instructor and department chair.

**STAT-596**

**Selected Topics: Non-recurring (1-6)**

**Course Level:** Undergraduate/Graduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-601**

**Topics in Advanced Probability and Statistics (3)**

**Course Level:** Graduate

Topics vary by section, may be repeated for credit with different topic. Mathematical foundations of statistical theory. Special topics in probability and mathematical statistics. Usually offered alternate springs (odd years). Permission: instructor.

**STAT-605**

**Introduction to Survey Sampling (3)**

**Course Level:** Graduate

This course introduces the basic approaches to surveys, including simple random, systematic, and stratified sampling. Also included is the design of questionnaires and the analysis of sample data. Emphasis is on the practical application of sampling. Meets with STAT-405. Usually offered alternate falls. Prerequisite: STAT-514.

**STAT-610**

**Statistical Inference: Estimation (3)**

**Course Level:** Graduate

The mathematical foundations of statistical inference; the Theory of Estimation including minimum risk-, Bayes-, minimax-, and equivariant estimation; decision theory; and large sample behavior. Usually offered alternate falls (even years). Prerequisite: STAT-600.

**STAT-611**

**Theory of Sampling (3)**

**Course Level:** Graduate

This course covers the mathematical development of the principles of survey design, including methods for determining expected value, bias, variance, and mean square error; simple random, systematic, stratified, cluster, multistage, and double sampling; unbiased, ration, regression and composite estimation; measurement error; and comparison of alternative designs. Usually offered alternate springs. Prerequisite: STAT-605.

**STAT-615**

**Regression (3)**

**Course Level:** Graduate

Simple and multiple regression, least squares, curve fitting, graphic techniques, and tests and confidence intervals for regression coefficients. Meets with STAT-415. Usually offered every fall and summer. Prerequisite: STAT-514.

**STAT-616**

**Generalized Linear Models (3)**

**Course Level:** Graduate

Extension of regression methodology to more general settings where standard assumptions for ordinary least squares are violated. Generalized least squares, robust regression, bootstrap, regression in the presence of auto-correlated errors, generalized linear models, logistic and Poisson regression. Usually offered every spring. Prerequisite: STAT-515 and a course in calculus.

**STAT-618**

**Bayesian Statistics (3)**

**Course Level:** Graduate

Principles and applications of modern statistical decision theory, with a special focus on Bayesian modeling, data analysis, inference, and optimal decision making. Prior and posterior; comparison of Bayesian and frequentist approaches, including minimax decision making and elementary game theory. Bayesian estimation, hypothesis testing, credible sets, and Bayesian prediction. Introduction to Bayesian computing software and applications to diverse fields. Grading: A-F only. Prerequisite: STAT 514.

**STAT-622**

**Advanced Biostatistics (3)**

**Course Level:** Graduate

Introduction to methodologies used to understand complex problems in four major areas of biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Phases of clinical trials, dynamics of epidemiology and disease, estimation of survival, hazard and mortality functions, and analysis of gene expression data are covered. Usually offered every fall. Meets with STAT-422. Grading: A-F only. Prerequisite: STAT-514.

**STAT-624**

**Data Analysis (3)**

**Course Level:** Graduate

An introduction to exploratory data analysis including graphical summaries, model assessment and selection, model inference and averaging, and data mining elements. Explores supervised statistical learning for regression and classification, unsupervised machine learning algorithms, and related topics. Meets with STAT-424. Usually offered every spring. Prerequisite: STAT-520 or STAT-615.

**STAT-625**

**Statistical Software (3)**

**Course Level:** Graduate

Introduction to the use of the SAS language to prepare, modify, and analyze data, interpret output and final preparation of results. Emphasis on practical programming principles and use of built-in procedures. Comparisons with other programming languages. Meets with STAT-425. Usually offered every fall. Prerequisite: STAT-514.

**STAT-630**

**Mathematical Statistics I (3)**

**Course Level:** Graduate

Probability, random variables, probability distributions and functions of random variables, generating functions, order statistics, the theory of point estimation, (maximum likelihood, minimum variance unbiased estimators, confidence intervals), and theory of hypothesis testing (Neyman-Pearson, likelihood ratio, etc.). Usually offered every fall.

**STAT-631**

**Mathematical Statistics II (3)**

**Course Level:** Graduate

Probability, random variables, probability distributions and functions of random variables, generating functions, order statistics, the theory of point estimation, (maximum likelihood, minimum variance unbiased estimators, confidence intervals), and theory of hypothesis testing (Neyman-Pearson, likelihood ratio, etc.). Usually offered every spring. Prerequisite: STAT-630.

**STAT-632**

**Advanced Mathematical Statistics (3)**

**Course Level:** Graduate

Theory of estimation, properties of estimators, large-sample properties and techniques, and applications. Usually offered every fall. Prerequisite: STAT-631.

**STAT-690**

**Independent Study Project in Statistics (1-6)**

**Course Level:** Graduate

Permission: instructor and department chair.

**STAT-691**

**Internship in Statistics (1-6)**

**Course Level:** Graduate

Individual placement and supervision in an approved organization involving statistical analysis, methodology, or theory. Permission: instructor and department chair.

**STAT-696**

**Selected Topics: Non-recurring (1-6)**

**Course Level:** Graduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-796**

**Selected Topics: Non-Recurring (1-6)**

**Course Level:** Graduate

Topics vary by section, may be repeated for credit with different topic.

**STAT-797**

**Master's Thesis Research (1-6)**

**Course Level:** Graduate

Grading: SP/UP only.

**STAT-798**

**Statistical Research and Consulting (1-3)**

**Course Level:** Graduate

May be repeated for credit. Through written reviews and oral presentations, students investigate advances in statistical theory and applications in recent journals. Through interaction with other departments, students learn to formulate statistically problems expressed in the language of another discipline and interact in a consulting role with researchers outside of statistics. This course develops statistical consulting skills ranging from basic concepts relating to how to formulate the nature of the client's problem, to solving it and presenting the solution in the language of the client. Students complete major statistical consulting problems under supervision and statistical support for projects on campus as well as outside consulting projects. Usually offered every spring. Permission: department.