STAT100
Career Explorations in Statistics

Description: Introduction to the field of statistics, and exploration of careers available to those trained in statistics.

Course details
Credit Hours:1
Max credits per semester:1
Max credits per degree:1
Grading Option:Graded

Credit Hours:1

ACE:

STAT101
Introduction to Data

Removal of all entrance deficiencies in mathematics.

Description: An introduction to statistics through exploratory data analysis and data visualization. Topics include data types, chart types, methods for working with and reducing data, simple regression, regression diagnostics. Focuses on how to communicate statistical information and how to critically consume statistical information presented in the media and popular press.

This course is a prerequisite for: STAT 102

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT102
Principles of Statistical Analysis

Prerequisites: STAT 101; concurrent STAT 151

Description: Introduction to formal statistical inference and elementary probability for statistics majors. Explores the practical application of statistical techniques to meaningful scientific problems. Inference topics will be implemented using both simulation-based approaches and classical, theory-based methods.

This course is a prerequisite for: STAT 212; STAT 262; STAT 349

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT151
Introduction to Statistical Computing

Description: Introduction to programming for statistical analysis. Covers basic programming concepts necessary for statistics, good computing practice, and use of built-in functions to complete basic statistical analyses.

This course is a prerequisite for: STAT 251; STAT 349

Course details
Credit Hours:1
Max credits per semester:1
Max credits per degree:1
Grading Option:Graded

Credit Hours:1

ACE:

STAT212
Principles of Study Design

Prerequisites: STAT 102

Description: Introduction to statistical aspects of study design. Both designed experiments and observational studies are covered. Sampling techniques, major experimental and treatment design structures, as well as power and sample size considerations.

This course is a prerequisite for: STAT 301; STAT 325; STAT 412

Course details
Credit Hours:4
Max credits per semester:4
Max credits per degree:4
Grading Option:Graded

Credit Hours:4

ACE:

STAT218
Introduction to Statistics

Prerequisites: Removal of all entrance deficiencies in mathematics.

Credit toward the degree may be earned in only one of: CRIM 300 or ECON 215 or EDPS 459 or SOCI 206. Credit toward the degree cannot be earned in STAT 218 if taken after or taken in parallel with STAT/MATH 380.

Description: The practical application of statistical thinking to contemporary issues; collection and organization of data; probability distributions; statistical inference; estimation; and hypothesis testing.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option
ACE Outcomes: ACE 3 Math/Stat/Reasoning

Credit Hours:3

ACE:ACE 3 Math/Stat/Reasoning

STAT251
Statistical Computing I: Data Wrangling

Prerequisites: STAT 151

Description: Techniques for processing, cleaning, and visualizing messy data. Topics include data reduction strategies, data transformations, combining multiple data sources, and special types of data (text, spatial, dates and times, hierarchical).

This course is a prerequisite for: STAT 325; STAT 351; STAT 443; STAT 452; STAT 485

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT262
Probability for Statisticians

Prerequisites: STAT 102; MATH 208

Description: Probabilistic undergirding of statistical procedures including moments, common parametric families, marginal and conditional densities, sufficient statistics, modes of convergence, laws of large numbers and the central limit theorem and how they apply to estimators.

This course is a prerequisite for: STAT 301; STAT 414

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT301
Mathematical Statistics and Modeling I

Prerequisites: MATH 314, STAT 212, STAT 262

Description: Essential statistical theory and methods for professional statistical practice. Broad statistical topics include estimation and hypothesis testing, elementary Bayesian concepts, multiple linear regression, linear mixed effects models, analysis of variance (ANOVA), logistic regression, Poisson regression, and nonparametric methods.

This course is a prerequisite for: STAT 302; STAT 452; STAT 475; STAT 478

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT302
Mathematical Statistics and Modeling II

Prerequisites: STAT 301

A continuation of Mathematical Statistics and Modeling I (STAT 301) .

Description: Essential statistical theory and methods for professional statistical practice. Topics include data transformation, multiple sources of error, elementary model selection, generalized linear mixed models, Bayesian models, and other theory and methods deemed appropriate as statistical science continues to evolve.

This course is a prerequisite for: STAT 432; STAT 443; STAT 451; STAT 464; STAT 471; STAT 474; STAT 485; STAT 486

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT318
Introduction to Statistics II

Prerequisites: STAT 218 or equivalent.

Description: Tests for means/proportions of two independent groups, analysis of variance for completely randomized design, contingency table analysis, correlation, single and multiple linear regression, nonparametric procedures, design of experiments.

This course is a prerequisite for: STAT 412; STAT 414; STAT 450

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT325
Statistical Collaboration I

Prerequisites: STAT 212, STAT 251

Description: Introduction to the role and purpose of statistical consulting and interdisciplinary collaboration. Covers processes for successful interdisciplinary collaboration, including asking good questions, dealing with difficult clients, communicating statistics to non-statisticians, working in teams and determining solutions to answer the client's research question.

This course is a prerequisite for: STAT 425

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT349
Technical Skills for Statisticians

Prerequisites: STAT 151, STAT 102

Description: Creation of research reports, business reports, and executive summaries. Presentation strategies, consequences of statistical modeling for real-world decision making, and countering common misconceptions and errors in statistical reasoning. Focus on real-world applications in research, business, and public service.

This course is a prerequisite for: STAT 351

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT351
Statistical Computing II: Data Management and Visualization

Prerequisites: STAT 251, STAT 349

Description: Computational skills for management, visualization and analysis of large and complex data which are necessary for modern statistics. Includes a wide range of topics necessary for data analytics, including harvesting data from websites and common data structures, setting up and working with databases, and designing interactive data displays.

This course is a prerequisite for: STAT 425; STAT 451; STAT 471

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT380
Statistics and ApplicationsCrosslisted with STAT 380H, RAIK 270H

Prerequisites: A grade of P, C, or higher in MATH 107 or MATH 107H.

Credit toward the degree can not be earned in STAT 218 if taken after or taken in parallel with STAT/MATH 380.

Description: Probability calculus; random variables, their probability distributions and expected values; t, F and chi-square sampling distributions; estimation; testing of hypothesis; and regression analysis with applications.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option
Groups:Advanced Mathematics Courses
ACE Outcomes: ACE 3 Math/Stat/Reasoning

Credit Hours:3

ACE:ACE 3 Math/Stat/Reasoning

STAT380H
Statistics and ApplicationsCrosslisted with STAT 380, RAIK 270H

Prerequisites: A grade of P, C, or higher in MATH 107 or MATH 107H.

Credit toward the degree can not be earned in STAT 218 if taken after or taken in parallel with STAT/MATH 380.

Description: Probability calculus; random variables, their probability distributions and expected values; t, F and chi-square sampling distributions; estimation; testing of hypothesis; and regression analysis with applications.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option
Groups:Advanced Mathematics Courses
ACE Outcomes: ACE 3 Math/Stat/Reasoning

Credit Hours:3

ACE:ACE 3 Math/Stat/Reasoning

STAT412
Advanced Statistical Design

Prerequisites: STAT 212 or STAT 318

Description: Advanced statistical designs, including complex treatment and experimental designs and analyses. Incomplete Blocks, Response Surfaces, Advanced Row-Column designs, Split-Plots, Repeated Measures, Crossover designs, Analysis of Covariance, and Meta-analysis.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT414
Introduction to Survey Sampling

Prerequisites: STAT 262 or STAT 318 or STAT 380

Description: Sampling frames, sampling methodology, questionnaire design. Basics of standard sampling plans including simple random sampling, ratio estimators, stratified sampling, and cluster sampling. More advanced topics may include complex surveys, nonresponse, confidentiality problems, and adaptive methods.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT425
Statistical Collaboration II

Prerequisites: STAT 325; STAT 351

Description: Practical experience in applying collaboration skills, working with domain experts to strategically plan and analyze the domain experts' research data. Collaboration with the domain expert will include proposing a design and sample size for a research study, determination and implementation of appropriate statistical analyses, and summarization and presentation of analysis results.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded
ACE Outcomes: ACE 10 Integrated Product

Credit Hours:3

ACE:ACE 10 Integrated Product

STAT430
Sensory EvaluationCrosslisted with FDST 430, FDST 830, STAT 830

Prerequisites: Introductory course in statistics.

Description: Food evaluation using sensory techniques and statistical analysis.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT432
Introduction to Spatial Statistics

Prerequisites: STAT 302 or STAT 463 (could be concurrent to either)

Description: Introduces statistical analysis of spatial and spatiotemporal data. Topics include statistical theory, methods and applications for geostatistical, lattice and point processes. The focus is on methods and applications, but necessary and essential theories and proofs will also be covered.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT442
Computational BiologyCrosslisted with BIOC 842, STAT 842, BIOC 442

Prerequisites: Any introductory course in biology, or genetics, or statistics.

Description: Databases, high-throughput biology, literature mining, gene expression, next-generation sequencing, proteomics, metabolomics, system biology and biological networks.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT443
Statistical Analysis of Genomics Data

Prerequisites: STAT 251, STAT 302

Familiarity with R or Python highly recommended

Description: Introduction to basic statistical analyses in bioinformatics. Techniques for processing and analysis of commonly occurring genomic data types such as GWAS, micro-arrays, mass. spec, and RNAseq. Estimation of gene networks and visualization of data and results from analysis.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT450
Introduction to Regression Analysis

Prerequisites: STAT 301 or STAT 463

Previous knowledge of matrix algebra is beneficial.

Description: Practical tools and techniques for building linear regression models using real-world data and assessing their validity; necessary theory and supporting proofs will also be covered. Topics include introduction of simple/multiple linear regression, parameter estimation and inference in both frequentist and Bayesian frameworks, model diagnostics, and variable selection.

This course is a prerequisite for: STAT 475; STAT 478

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT451
Development of Statistical Software

Prerequisites: STAT 302, STAT 351

ACE 10 scholarly product will be a statistical software package which fills a need in the ecosystem.

Description: Advanced statistical software development. Packaging code into functions, intelligent software design, compiled languages to speed up code, development and release cycles.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded
ACE Outcomes: ACE 10 Integrated Product

Credit Hours:3

ACE:ACE 10 Integrated Product

STAT452
Advanced Computational Statistics

Prerequisites: STAT 251, STAT 301

Description: Comprehensive treatment of modern and classical computational statistics, including algorithms for statistical prediction, inference, numerical optimization, Markov Chain Monte Carlo methods, bootstrapping and computing tools for big data problems.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT462
Introduction to Mathematical Statistics I: Distribution Theory

Prerequisites: Grade of C or better in MATH 208 or MATH 107H.

STAT 380 or equivalent is strongly recommended.

Description: Sample space, random variable, expectation, conditional probability and independence, moment generating function, special distributions, sampling distributions, order statistics, limiting distributions, and central limit theorem.

This course is a prerequisite for: ACTS 401; STAT 463

Course details
Credit Hours:4
Max credits per semester:4
Max credits per degree:4
Grading Option:Graded with Option
Offered:FALL

Credit Hours:4

ACE:

STAT463
Introduction to Mathematical Statistics II: Statistical Inference

Prerequisites: C or better in STAT 462

Description: Interval estimation; point estimation, sufficiency, and completeness; Bayesian procedures; uniformly most powerful tests, sequential probability ratio test, likelihood ratio test, goodness of fit tests; elements of analysis of variance and nonparametric tests.

This course is a prerequisite for: STAT 432; STAT 450; STAT 486

Course details
Credit Hours:4
Max credits per semester:4
Max credits per degree:4
Grading Option:Graded with Option
Offered:SPRING

Credit Hours:4

ACE:

STAT464
Model Selection and Prediction

Prerequisites: STAT 302

Description: Methods for selecting models applicable to real-world problems. Prediction as a modeling goal, models for prediction as opposed to inference. Methods for emerging data types, such streaming data, social network data, censored data, and others.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded

Credit Hours:3

ACE:

STAT471
Analysis of Messy Data

Prerequisites: STAT 302, STAT 351

Description: Analysis of complex, real-world data sets. Analysis techniques will vary depending on interest and availability of data sets.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded
ACE Outcomes: ACE 10 Integrated Product

Credit Hours:3

ACE:ACE 10 Integrated Product

STAT474
Introduction to Nonparametric Statistics

Prerequisites: STAT 302

Description: Most commonly used nonparametric techniques in statistics including rank-based methods for testing and estimation, nonparametric estimators of parameters, distributions, and curves, assessing the properties of data, and permutation tests including how to cope with multiple comparisons. Comparisons between methods will be emphasized throughout.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT475
Introduction to Categorical Data Analysis

Prerequisites: STAT 301 or STAT 450

Description: Introduction to methodology for analyzing categorical data, including contingency table methods, binary regression, multinomial regression, and loglinear regression.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT478
Introduction to Time Series Analysis

Prerequisites: STAT 301 or STAT 450

Description: A basic introduction to modern time series analysis including time series regression and exploratory data analysis, the classical decomposition, ARIMA models, model identification/estimation/forecasting, seasonality, Fourier analysis, spectral estimation, and state space models.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT485
Statistical Learning

Prerequisites: STAT 251, STAT 302

Proficiency in a statistical computing language may replace STAT 251

Description: An introduction to supervised and unsupervised methods for statistical learning and data mining. Bias-variance trade-off, classification, regression, factor analysis, and neural networks for modeling and prediction.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT486
Introduction to Bayesian Analysis

Prerequisites: STAT 302 or STAT 463

Description: Principles of Bayesian analysis including forming posteriors from priors and likelihoods. Bayesian estimation, testing, linear regression, and hierarchical models. Computing posterior distributions using existing software and standard classes of algorithms such as MCMC.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded with Option

Credit Hours:3

ACE:

STAT494
Topics in Statistics and Probability

Prerequisites: Permission.

Description: Special topics in either statistics or the theory of probability.

Course details
Credit Hours:1-5
Max credits per semester:5
Max credits per degree:24
Grading Option:Graded with Option

Credit Hours:1-5

ACE:

STAT496
Independent Study

Prerequisites: Prior arrangement with a faculty member and submission of proposed study plan to department office.

Course details
Credit Hours:1-5
Max credits per semester:5
Max credits per degree:5
Grading Option:Graded with Option

Credit Hours:1-5

ACE:

STAT499
Undergraduate Thesis

Prerequisites: Permission

Description: Independent research project carried out under the guidance of a faculty member in the Department of Statistics. Culminates in the presentation of a thesis to the department.

Course details
Credit Hours:3
Max credits per semester:3
Max credits per degree:3
Grading Option:Graded
ACE Outcomes: ACE 10 Integrated Product

Credit Hours:3

ACE:ACE 10 Integrated Product