STAT - Statistics

STAT 216Q Introduction to Statistics: 3 Credits (3 Lec)

PREREQUISITE: Math Level 300, or a C- or better in any 100 level or above M course. (F, Sp) Traditional and resistant estimators of location and spread, fundamentals of inference using randomization and classical methods, confidence intervals, and tests of hypotheses. This course is taught in the TEAL format. COMMON FINAL ONLY

View Course Outcomes:

Understand how to describe the characteristics of a distribution.\\n
Understand how data can be collected, and how data collection dictates the choice of statistical method and appropriate statistical inference.\\n
Interpret and communicate the outcomes of estimation and hypothesis tests in the context of a problem.\\n
To understand the scope of inference for a given dataset.\\n

STAT 290R Undergraduate Research: 1-8 Credits (1 Other)

PREREQUISITE: Consent of department head. (F, Sp) Directed undergraduate research. Course will address responsible conduct of research. -
Repeatable up to 8 credits.

STAT 291 Special Topics: 1-4 Credits (1-4 Lec)

PREREQUISITE: None required but some may be determined necessary. Courses not required in any curriculum for which there is a particular one-time need, or given on a trial basis to determine acceptability and demand before requesting a regular course number
Repeatable up to 12 credits.

STAT 332 Statistics for Scientists and Engineers: 3 Credits (3 Lec)

PREREQUISITE: M 172. (F, Sp) Methods of estimation, data collection, analysis and display of quantitative information, continuous and discrete random variables, families of probability distributions, hypothesis testing, regression, ANOVA

View Course Outcomes:

Upon completing this course, a student will be able to:\\nDemonstrate knowledge and use of discrete and continuous random variables and their probability distributions\\n\\n
Recognize well known families of probability distributions and when they are used
Identify the various ways data are collected
Find and interpret graphical and numerical summaries of data
Carry out and interpret the results of basic statistical analyses and procedures, including regression, interval estimation and hypothesis testing"

STAT 337 Intermediate Statistics with Introduction to Statistical Computing: 3 Credits (3 Lec)

PREREQUISITE: STAT 216Q or STAT 332 or EIND 354. (F, Sp, Su) One- and two-sample tests and associated confidence intervals for means and proportions (and analogous randomization- and resampling-based techniques); One- and Two-way analysis of variance; F-tests, correlation, simple and multiple regression, contingency tables. Introduction to statistical computing, reproducible research, and analysis using a modern scripting language; emphasis on connecting study design to scope of inference in the context of authentic studies and understanding or reproducing statistical results as used in journal articles; COMMON FINAL ONLY

View Course Outcomes:

Demonstrate an understanding of statistical results as used in journal articles, and discuss scope of inference in the context of authentic research questions and data sets.
Use a statistical computing language to complete the following:\\n
Create modern data visualizations for a variety of data types and provide written interpretations
Estimate and interpret one-way and two-way ANOVA (including an interaction), and assess model assumptions
Estimate and interpret a multiple linear regression model, including with an interaction, and assess model assumptions
Perform and discuss model refinement and understand the basics of commonly used model selection techniques
Perform, interpret, and assess model assumptions of Chi-squared tests of independence and homogeneity

STAT 408 Statistical Computing and Graphical Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 337. (Sp) Introduction to statistical packages R or SAS, including data importation, cleaning, graphing, and basic programming. Emphasis on use of graphical displays to explore, understand, and present data, and on organization of code

View Course Outcomes:

become literate in statistical programming,
effectively communicate through visual presentation of data,
understand and imitate good programming practices

STAT 411 Methods for Data Analysis I: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: STAT 337. (F, Sp) Introduction to statistical inference and design, t-tools, non-parametric alternatives, one-way ANOVA, simple linear regression, multiple linear regression, with an emphasis on statistical thinking, appropriate inference, interpretation of results, and writing

View Course Outcomes:

Explain the fundamental concepts of statistical inference
Explain the connections among the randomization distribution, permutation distribution, sampling distribution, and the commonly used t-distribution
Recognize the connections between study design and appropriate st statistical analysis and scope of inference
Demonstrate understanding of a basic linear model using the reference-level parameterization and the meaning of the parameters of the model
Demonstrate ability to appropriately tie a question of interest to a model parameter
Demonstrate understanding of the assumptions underlying common models and methods, and how to critique and check appropriateness of those assumptions
Demonstrate a basic understanding of using statistical software to perform data analysis
Demonstrate a basic understanding of using computer software to investigate statistical concepts through simulation
Demonstrate ability to write statistical reports including justification for assumptions and decisions made, a concise summary of findings interpreting results in the context of the problem, and a written description of the scope of inference of the findings
Demonstrate ability to critically evaluate conclusions made from a statistical analysis
Demonstrate ability to recognize common mistakes made in statistical analysis, interpretation, and inference in general
Complete a final project demonstrating that the above learning outcomes are combined in the context of a real study. In this process students will also demonstrate ability to effectively take part in a peer review process.

STAT 412 Methods for Data Analysis II: 3 Credits (2 Lec, 2 Lab)

PREREQUISITE: STAT 411. (F, Sp) Continuation of STAT 411/STAT 511 to cover principles of experimental design, multi-factor ANOVA, repeated measures, logistic regression, Poisson log-linear regression, and introductions to multivariate and time series analyses, with an emphasis on statistical thinking, appropriate inference and interpretation, and writing. Co-convened with STAT 512

View Course Outcomes:

Builds on the learning outcomes from STAT 511 to extend them to more sophisticated study designs and analysis procedures.
Explain the fundamental concepts of statistical inference
Explain the connections among the randomization distribution, permutation distribution, sampling distribution, and the commonly used t-distribution.
Recognize the connections between study design and appropriate statistical analysis and scope of inference
Demonstrate understanding of a basic linear model using the reference-level parameterization and the meaning of the parameters of the model
Demonstrate ability to appropriately tie a question of interest to a model parameter
Demonstrate understanding of the assumptions underlying common models and methods, and how to critique and check appropriateness of those assumptions
Demonstrate a basic understanding of using statistical software to perform data analysis
Demonstrate a basic understanding of using computer software to investigate statistical concepts through simulation
Demonstrate ability to write statistical reports including justification for assumptions and decisions made, a concise summary of findings interpreting results in the context of the problem, and a written description of the scope of inference of the findings
Demonstrate ability to critically evaluate conclusions made from a statistical analysis
Demonstrate ability to recognize common mistakes made in statistical analysis, interpretation, and inference in general
Complete a final project demonstrating that the above learning outcomes are combined in the context of a real study. In this process students will also demonstrate ability to effectively take part in a peer review process.

STAT 421 Probability Theory: 3 Credits (3 Lec)

PREREQUISITE: M 273
COREQUISITE: M 242. (F) Fundamentals of probability; discrete and continuous random variables; expected value; variance; joint, marginal, and conditional distributions; conditional expectations; applications; simulation; central limit theorem; order statistics
.

View Course Outcomes:

Explain and use fundamentals of probability
Demonstrate knowledge and use of discrete and continuous random variables and their probability distributions
Recognize well-known families of probability distributions and when they are used
Find expected values and variances; joint, marginal, and conditional distributions; and conditional expectations
Demonstrate a basic understanding of computer simulation
Explain the relevance of the concepts in the context of solving practical problems and relating to the foundation of statistical inference

STAT 422 Mathematical Statistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 421. (Sp) Senior capstone course. Introduction to the theory of point estimation, interval estimation, and hypothesis testing

View Course Outcomes:

Demonstrate knowledge and use of probability theory as a foundation for statistical inference
Derive estimators, hypothesis tests and confidence intervals for unknown parameters
Compare and evaluate estimators, hypothesis tests and confidence intervals based on desirable statistical properties
Demonstrate knowledge and use of the Central Limit Theorem and sampling distributions for commonly used statistics.
Demonstrate a basic understanding of computer simulation
Apply concepts to practical problems and relate them to other coursework and experiences in statistics.

STAT 425 Biostatistical Data Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 412. (Spring Even Years) Statistical methodology applicable to vital statistics, life tables and survival curves, clinical trials, epidemiologic investigations, and cause-effect studies

View Course Outcomes:

To understand how epidemiology is used for public health\\nimprovements and disease prevention.\\n\\n
To know how to compute and interpret relative risk and\\nodds ratio.
To build and interpret logistic regression models for odds\\nratios.
To build and interpret survival models.
To understand the tradeoffs in sensitivity and specificity of\\nmedical tests.
To interpret measures of association between exposure\\nand disease.

STAT 431 Nonparametric Statistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 337 or STAT 511. () F alternate years, to be offered even years. Goodness-of-fit tests, sign tests, randomization and permutation tests, Wilcoxon and Mann-Whitney tests, Kruskal-Wallis and Friedman's tests, Spearman and Kendall's measures of association, bootstrap techniques, and other alternative nonparametric test procedures. Emphasis on methods and interpretations rather than theory

View Course Outcomes:

Learn when and how to perform classical nonparametric procedures, including goodness-of-fit tests, procedures for single and multi-sample data, tests for trend and association, and methods for censored data.\\n
Learn computer-intensive methods, including bootstrapping, randomization tests, and permutation tests.
Experience independent learning by reading a journal article on a nonparametric method not covered during the course, write a brief report summarizing its content, include a numerical example, and give a presentation to the class.

STAT 436 Introduction to Time Series Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 411/STAT 511 or consent of instructor. () F alternate years, to be offered even years. An introduction to time series analysis considering time series regression, autoregressive, moving average, and ARIMA models, time series model building, estimation, and forecasting, and basic frequency domain methods. Co-convened with STAT 536

STAT 437 Introduction to Applied Multivariate Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 411 or STAT 511 or consent of instructor. () S alternate years, to be offered odd years. Classic multivariate methods, including but not limited to principal components analysis, canonical correlation analysis, factor analysis, discrimination and classification methods, cluster analysis, and other topics may depend on instructor

View Course Outcomes:

Graphically explore and describe common features of interest in multivariate data. \\n\\n
Estimate and interpret a principal component analysis.
Estimate and interpret a factor analysis.
Perform and interpret a cluster analysis.
Identify an appropriate multivariate analysis amongst those covered based on the description of a research problem.\\n

STAT 439 Introduction to Categorical Data Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 412/STAT 512. () S alternate years, to be offered even years. Contingency table analysis, Poisson regression, logistic regression, log-linear models, multicategory logit models

STAT 441 Experimental Design: 3 Credits (3 Lec)

PREREQUISITE: STAT 411/STAT 511 and M 221 or M 333 or M 441 or consent of instructor. (Sp) An introduction to the design and analysis of experiments: topics include analysis of variance methods, matrix forms, multiple comparisons, fixed and random effects, factorial designs, balanced complete and incomplete blocking designs, designs with nested effects, and split plot designs

View Course Outcomes:

Understand the design concepts of blocking, interactions, nesting, split-plotting, random effects, analysis of covariance, residual diagnostics, and when and how these concepts should be applied.
Use analysis of variance methods to analyze data from single and multiple factor experiments using statistical software.
Gain practical experience via proposing and; running an experiment, and presenting the results in a statistical report and formal class presentation.

STAT 446 Sampling: 3 Credits (3 Lec)

PREREQUISITE: STAT 337 or STAT 511. (F) Probability sampling, sources of bias and uncertainty, survey design, methods for the natural sciences, simple random sampling, stratified random sampling, systematic sampling, cluster sampling

View Course Outcomes:

Demonstrate classical sampling survey procedures applied to finite populations (including simple random sampling, stratified sampling, cluster sampling, and systematic sampling).\\n\\n
Demonstrate sampling methods that use unequal probability sampling.
Demonstrate ratio and regression analytical methods that utilize auxiliary variable information.
Demonstrate bootstrap resampling estimation methods.
Demonstrate practical application via proposing and running a sampling design, and presenting the results in a statistical report and formal class presentation.

STAT 448 Mixed Effects Models: 3 Credits (3 Lec)

PREREQUISITE: STAT 411/STAT 511 or consent of instructor. () F alternate years, to be offered odd years. In depth analysis of random, fixed and mixed effects models including use of stat software and interpretation of results. Emphasis on observations correlated in time (repeated measures) and space, and on random coefficients models (growth curves)

STAT 456R Bayesian Statistical Inference: 3 Credits (3 Lec)

PREREQUISITE: STAT 408. (Spring, odd years.) This course will introduce the basic ideas of Bayesian statistics and provide a contrast with techniques for classical inference. The course focuses on both the philosophical foundations and practical implementation of Bayesian methods

View Course Outcomes:

Describe fundamental differences between Bayesian and classical inference,
Select models and priors, write likelihoods, write full probability models and derive posterior distributions, and critically assess/examine model and prior assumptions,
Use computer code, including R, STAN, JAGS or Nimble, to sample from posterior distributions, and diagnose non-convergence of samplers, and
Make inferences from posterior distributions and learn how to perform posterior predictive assessments of models.

STAT 490R Undergraduate Research: 1-6 Credits (1 Other)

PREREQUISITE: Junior standing in statistics and consent of department head. (F, Sp, Su) Directed undergraduate research/creative activity which may culminate in a research paper, journal article, or undergraduate thesis. Course will address responsible conduct of research. May be repeated
Repeatable up to 12 credits.

STAT 491 Special Topics: 1-4 Credits (1-4 Lec)

PREREQUISITE: Course prerequisites as determined for each offering. On demand. Course not required in any curriculum for which there is a particular one-time need, or given on a trial basis to determine acceptability and demand before requesting a regular course number
Repeatable up to 12 credits.

STAT 492 Independent Study: 1-3 Credits (1-3 Other)

PREREQUISITE: Junior standing, consent of instructor, and approval of department head. (F, Sp) Directed research and study on an individual basis
Repeatable up to 6 credits.

STAT 494 Seminar: 1 Credits (1 Other)

PREREQUISITE: Junior standing and as determined for each offering. (Su) Topics offered at the upper division level which are not covered in regular courses. Students participate in preparing and presenting material
Repeatable up to 4 credits.

STAT 497 Educational Methods: Statistics: 1-3 Credits (1-3 Other)

PREREQUISITE: Junior standing, consent of instructor, and approval of department head. (F, Sp) As co-teachers of a Statistics course, students will learn and have the opportunity to practice classroom teaching strategies as well as mentoring skills
Repeatable up to 6 credits.

View Course Outcomes:

Practice different approaches to explaining statistics concepts to students in a way that is effective for a broad variety of learners
Describe common student misconceptions with statistics concepts and how to address these misconceptions
Organize and teach a lesson plan for a given set of statistical concepts to a statistics course

STAT 498 Internship: 2-12 Credits (2-12 Other)

PREREQUISITE: Junior standing, consent of instructor, and approval of department head. (F, Sp) An individualized assignment arranged with an agency business, or other organization to provide guided experience in the field
Repeatable up to 12 credits.

STAT 500 Applied Methods in Statistics: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: Graduate standing or consent of instructor. This course is intended for graduate students not majoring in mathematical sciences. Graphical techniques, data collection plans, populations, samples, sampling distributions, analysis of variance for one-way classifications, multiple comparisons, simple linear regression, scope of inference and transparent communication of uncertainty

View Course Outcomes:

Describe a data set using appropriate numerical summaries and graphical tools
Communicate the scope of inference that can be made in a study in the context of the research question.
Implement the fundamental techniques of statistical inference
Evaluate the validity of a statistical analysis by assessing the implicit assumptions made by commonly used methods
Ability to apply basic statistical analyses within a specific scientific domain, and to communicate results clearly and concisely in writing
Learn to use R statistical software to make appropriate data visualizations, and fit linear regression models to data, and gain a working familiarity with best practices for producing reproducible code and writing using R Markdown

STAT 501 Intermediate Probability and Statistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 422 or consent of instructor. (F, Su) Families of probability distributions, distributions of functions of random variables, limiting distributions, order statistics. Cross-listed with M 501

STAT 502 Intermediate Mathematical Statistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 501 or M 501. (Sp) Estimation, likelihood inference, statistical hypothesis tests, sufficient statistics, exponential families, Bayesian statistics. Cross-listed with M 502

STAT 505 Linear Models: 3 Credits (3 Lec)

PREREQUISITE: STAT 412 or STAT 512. (F) Special matrix theory for statistics, multivariate normal distribution, distributions of quadratic forms, estimation and testing for the general linear model, one-way and two-way classification models, contrasts (main effect, simple effect and interaction), multiple comparison techniques

STAT 506 Advanced Regression Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 505. (Sp) Applications of linear models using statistical packages; detecting and dealing with violations of assumptions including nonconstant variance, nonnormality, and collinearity; mixed effects models

STAT 509 Stochastic Processes: 3 Credits (3 Lec)

PREREQUISITE: STAT 421. () S on demand. Conditional probability theory, discrete and continuous time markov chains including birth and death processes and long run behavior; Poisson processes; queuing systems; system reliability. Cross-listed with M 509

STAT 510 Statistical Consulting Seminar: 1 Credits (1 Other)

PREREQUISITE: Graduate standing in statistics. (F, Sp) Seminar discussions of issues and cases in statistical consulting. Supervised practice in consulting with researchers from various disciplines
Repeatable up to 6 credits.

STAT 511 Methods of Data Analysis I: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: STAT 216Q or equivalent or STAT 500. (F, Sp) For non-statistics graduate students. Introduction to statistical inference and design, t-tools, non-parametric alternatives, one-way ANOVA, simple linear regression and multiple linear regression, with an emphasis on statistical thinking, appropriate inference, interpretation of results and writing. Semester project required

View Course Outcomes:

Explain the fundamental concepts of statistical inference.
Explain the connections among the randomization distribution, permutation distribution, sampling distribution, and the commonly used t-distribution.
Recognize the connections between study design and appropriate statistical analysis and scope of inference
Demonstrate understanding of a basic linear model using the reference-level parameterization and the meaning of the parameters of the model
Demonstrate ability to appropriately tie a question of interest to a model parameter
Demonstrate understanding of the assumptions underlying common models and methods, and how to critique and check appropriateness of those assumptions
Demonstrate a basic understanding of using statistical software to perform data analysis
Demonstrate a basic understanding of using computer software to investigate statistical concepts through simulation
Demonstrate ability to write statistical reports including justification for assumptions and decisions made, a concise summary of findings interpreting results in the context of the problem, and a written description of the scope of inference of the findings
Demonstrate ability to critically evaluate conclusions made from a statistical analysis
Demonstrate ability to recognize common mistakes made in statistical analysis, interpretation, and inference in general
Complete a final project demonstrating that the above learning outcomes are combined in the context of a real study; In this process students will also demonstrate ability to effectively take part in a peer review process.

STAT 512 Methods of Data Analysis II: 3 Credits (2 Lec, 2 Lab)

PREREQUISITE: STAT 411/STAT 511 (co-convened). (F, Sp) Continuation of STAT 411/STAT 511 to cover principles of experimental design, multi-factor ANOVA, repeated measures, logistic regression, Poisson log-linear regression, and introductions to multivariate and time series analyses, with an emphasis on statistical thinking, appropriate inference and interpretation, and writing. A semester project is required. Co-convened with STAT 412

View Course Outcomes:

Builds on the learning outcomes from STAT 511 to extend them to more sophisticated study designs and analysis procedures.
Explain the fundamental concepts of statistical inference
Explain the connections among the randomization distribution, permutation distribution, sampling distribution, and the commonly used t-distribution.
Recognize the connections between study design and appropriate statistical analysis and scope of inference
Demonstrate understanding of a basic linear model using the reference-level parameterization and the meaning of the parameters of the model
Demonstrate ability to appropriately tie a question of interest to a model parameter
Demonstrate understanding of the assumptions underlying common models and methods, and how to critique and check appropriateness of those assumptions
Demonstrate a basic understanding of using statistical software to perform data analysis
Demonstrate a basic understanding of using computer software to investigate statistical concepts through simulation
Demonstrate ability to write statistical reports including justification for assumptions and decisions made, a concise summary of findings interpreting results in the context of the problem, and a written description of the scope of inference of the findings
Demonstrate ability to critically evaluate conclusions made from a statistical analysis
Demonstrate ability to recognize common mistakes made in statistical analysis, interpretation, and inference in general
Complete a final project demonstrating that the above learning outcomes are combined in the context of a real study. In this process students will also demonstrate ability to effectively take part in a peer review process.

STAT 520 Topics in Applied Statistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 422 and consent of instructor. () On demand. Current topics selected from computational statistics, time series and spatial statistics, decision theory, sampling, linear and mixed models, and multivariate statistics

STAT 525 Biostatistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 412 or STAT 512 or STAT 505. (F) Department of Mathematical Sciences

View Course Outcomes:

Explain how epidemiology is used for public health improvements\\nand disease prevention.\\n
Compute and interpret relative risk and odds ratio.
Build and interpret logistic regression models for odds ratios.
Build and interpret survival models.
Explain the tradeoffs in sensitivity and specificity of medical tests.
Interpret measures of association between exposure and disease

STAT 528 Statistical Quality Control: 3 Credits (3 Lec)

PREREQUISITE: STAT 421 or an equivalent transfer course in probability theory. () F alternate years, to be offered odd years. Modeling process quality, traditional SQC tools, control charts for variable and attribute data, CUSUM and WMA charts, process capability analysis, reliability statistics, accelerated testing

STAT 532 Bayesian Data Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 422 or STAT 502 or M 502 and STAT 506 recommended. (F) Fundamentals of Bayesian inference, methods of Bayesian data analysis, computational methods for posterior simulation, fundamentals of hierarchical modeling

STAT 534 Spatial Data Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 412, STAT 512, and STAT 422, or equivalent, or consent of the instructor. () S alternate years, to be offered odd years. Statistical methods of spatial data analysis, stationary and nonstationary random fields, covariance structures, geostatistical models and analysis, spatial point process models and analysis, spatial lattice models and analysis

STAT 536 Time Series Analysis: 3 Credits (3 Lec)

PREREQUISITE: STAT 411, STAT 511, or consent of the instructor. An introduction to time series analysis considering time series regression, autoregressive, moving average, and ARIMA models, time series model building, estimation, and forecasting, and basic frequency domain methods. Co-convened with STAT 436
Department of Mathematical Sciences.

STAT 537 Multivariate Analysis I: 3 Credits (3 Lec)

PREREQUISITE: STAT 505. () S alternate years, to be offered even years. Multivariate regression, principal components analysis, exploratory and confirmatory factor analysis, discriminant and classification analysis, cluster analysis, classification and regression trees, basic structural equation modeling, along with bagging and boosting methods

STAT 538 Multivariate Analysis II: 3 Credits (3 Lec)

PREREQUISITE: STAT 537. () On demand. Special topics in multivariate analysis including general latent variable methods, analysis of covariance structures, common principle components, robust and distribution free multivariate analysis

STAT 539 Generalized Linear Models: 3 Credits (3 Lec)

PREREQUISITE: STAT 422 and STAT 411/STAT 511. () S alternate years, to be offered odd years. Analysis of categorical data including logistic regression, log-linear models, analysis of deviance, extrabinomial variation, quasi-likelihood

STAT 541 Experimental Design: 3 Credits (3 Lec)

PREREQUISITE: STAT 411/STAT 511 and M 221 or M 333 or M 441. (Sp) An introduction to the design and analysis of experiments: topics include analysis of variance methods, matrix forms, multiple comparisons, fixed and random effects, factorial designs, balanced complete and incomplete blocking designs, designs with nested effects, and split plot designs

View Course Outcomes:

1. Understand the design concepts of blocking, interactions, nesting, split-plotting, random effects, analysis of covariance, residual diagnostics, and when and how these concepts should be applied.
2. Use analysis of variance methods to analyze data from single and multiple factor experiments using statistical software.
3. Learn theoretical results associated with estimation and statistical inference applied to the analysis of experimental data.
4. Gain practical experience via proposing and running an experiment, and presenting the results in a statistical report and formal class presentation.

STAT 550 Advanced Mathematical Statistics: 3 Credits (3 Lec)

PREREQUISITE: STAT 502 or M 502 and either M 384, M 505, or M 547. () S alternate years, to be offered even years. Sufficiency, completeness, ancillary statistics, invariance, likelihood-based inference, large sample theory, Edgeworth and saddlepoint approximations

View Course Outcomes:

Use rigorous mathematical techniques to derive mathematical statistics results, including construction of hypothesis tests and confidence intervals
Describe ;and program optimization algorithms used in estimation
Compare and contrast different statistical inference ;approaches based on principles of mathematical statistics
Derive asymptotic distributions and properties of statistics
Communicate summaries of journal articles on mathematical statistics topics, both written and oral

STAT 575 Professional Paper and Project: 1-4 Credits (1-4 Lec)

PREREQUISITE: Graduate standing. (F, Sp, Su) A research or professional paper or project dealing with a topic in the field. The topic must have been mutually agreed upon by the student, his or her major advisor, and graduate committee
Repeatable up to 6 credits.

STAT 576 Internship: 1-12 Credits (1-12 Other)

PREREQUISITE: Graduate standing, consent of instructor and approval of department head. (F, Sp, Su) An individualized assignment arranged with an agency, business or other organization to provide guided experience in the field
Repeatable up to 99 credits.

STAT 578 Response Surface Methodology: 3 Credits (3 Lec)

PREREQUISITE: STAT 541 or STAT 505. (Su) Diagnostics; fractional-factorial designs; method of steepest ascent; canonical analysis; response optimization; ridge analysis; response surface design including central composite designs, orthogonal designs, rotatable designs, and optimal designs; mixture designs

STAT 589 Graduate Consultation: 3 Credits (3 Other)

PREREQUISITE: Master's standing. (F, Sp) This course may be used only by students who have completed all of their coursework (and thesis, if on a thesis plan) but who need additional faculty or staff time

STAT 590 Master's Thesis: 1-10 Credits (1-10 Other)

PREREQUISITE: Master's standing
Repeatable up to 99 credits.

STAT 591 Special Topics: 1-4 Credits (1-4 Lec)

PREREQUISITE: Upper division courses and others as determined for each offering. On demand. Courses not required in any curriculum for which there is a particular one time need, or given on a trial basis to determine acceptability and demand before requesting a regular course number
Repeatable up to 12 credits.

STAT 592 Independent Study: 1-3 Credits (1-3 Other)

PREREQUISITE: Graduate standing, consent of instructor, approval of department head and Dean of Graduate Studies. (F, Sp, Su) Directed research and study on an individual basis
Repeatable up to 6 credits.

STAT 594 Seminar: 1 Credits (1 Other)

PREREQUISITE: Graduate standing or seniors by petition. () On demand. Course prerequisites as determined for each offering. Topics offered at the graduate level which are not covered in regular courses. Students participate in preparing and presenting discussion material
Repeatable up to 6 credits.

STAT 689 Doc Reading & Research: 3-5 Credits (3-5 Other)

PREREQUISITE: Doctoral standing. (F, Sp, Su) This course may be used by doctoral students who are reading research publications in the field in preparation for doctoral thesis research
Repeatable up to 15 credits.

STAT 690 Doctoral Thesis: 1-10 Credits (1-10 Other)

PREREQUISITE: Doctoral standing
Repeatable up to 99 credits.