Department Information
The mission of the Department of Statistics is to provide its students with a fundamental understanding of statistical reasoning and methodology, to train them to apply this knowledge to the collection and analysis of data, and to prepare them for careers in a highly technological society in which science and decision-making are increasingly driven by a rapid expansion in the quantity and availability of data.
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CONTACT
Email | 352.392.1941 (tel) | 352.392.5175 (fax)
P.O. Box 118545
102 GRIFFIN-FLOYD HALL
GAINESVILLE FL 32611-8545
Map
Curriculum
Courses
STA 2023 Introduction to Statistics 1 3 Credits
Grading Scheme: Letter Grade
Graphical and numerical descriptive measures. Simple linear regression. Basic probability concepts, random variables, sampling distributions, central limit theorem. Large and small sample confidence intervals and significance tests for parameters associated with a single population and for comparison of two populations. Use of statistical computer software and computer applets to analyze data and explore new concepts. (M)
Attributes: General Education - Mathematics
STA 3024 Introduction to Statistics 2 3 Credits
Grading Scheme: Letter Grade
An introduction to the analysis of variance. Nonparametric statistical methods and applications. Analysis of count data: chi-square and contingency tables. Simple and multiple linear regression methods with applications.
Prerequisite: STA 2023 or the equivalent.
STA 3032 Engineering Statistics 3 Credits
Grading Scheme: Letter Grade
The basic concepts in probability and statistics with engineering applications. Topics include probability, discrete and continuous random variables, estimation, hypothesis testing, and linear and multiple regression. (M)
Prerequisite: MAC 2311.
Attributes: General Education - Mathematics
STA 3100 Programming With Data in R 3 Credits
Grading Scheme: Letter Grade
Introduction to statistical computing and programming with data. Topics include basic programming in R; data types and data structures in R; importing and cleaning data; specifying statistical models in R; statistical graphics; statistical simulation using pseudo-random numbers; reproducible research and the documentation of statistical analyses.
Prerequisite: STA 2023 with a minimum grade of B or STA 3032 with a minimum grade of B- or (AP statistics score of 4 or 5).
STA 4183 Theory of Interest 3 Credits
Grading Scheme: Letter Grade
Measurement of simple and compound interest, accumulated and present value. Annuities, yield rates, amortization schedules, sinking funds, bonds, securities and related funds.
Prerequisite: MAC 2312.
STA 4210 Regression Analysis 3 Credits
Grading Scheme: Letter Grade
Simple linear regression and multiple linear regression models. Inference about model parameters and predictions, diagnostic and remedial measures about the model, independent variable selection, multicolinearity, autocorrelation and nonlinear regression. SAS implementation of the above topics.
Prerequisite: STA 3024 or STA 3032 or (STA 4321 and STA 2023) or (MAS 3114 and STA 2023) or (MAS 4105 and STA 2023).
STA 4211 Design of Experiments 3 Credits
Grading Scheme: Letter Grade
The basic principles of experimental design: analysis of variance for experiments with a single factor; randomized blocks and Latin square designs: multiple comparison of treatment means; factorial and nested designs; analysis of covariance; response surface methodology.
Prerequisite: STA 4210.
STA 4222 Sample Survey Design 3 Credits
Grading Scheme: Letter Grade
Introduces the design of sample surveys and the analysis of survey data, emphasizing practical applications of survey methodology. Topics include sources of errors in surveys, questionnaire construction, simple random, stratified, systematic, and cluster sampling, ratio and regression estimation, and a selection of special topics such as applications to quality control and environmental science.
Prerequisite: (STA 4321 and STA 2023) or STA 3032 or STA 4322.
STA 4321 Introduction to Probability 3 Credits
Grading Scheme: Letter Grade
Introduction to the theory of probability, counting rules, conditional probability, independence, additive and multiplicative laws, Bayes Rule. Discrete and continuous random variables, their distributions, moments and moment generating functions. Multivariate probability distributions, independence, covariance. Distributions of functions of random variables, sampling distributions, central limit theorem.
Prerequisite: MAC 2313 or MAC 3474 with a minimum grade of C.
STA 4322 Introduction to Statistics Theory 3 Credits
Grading Scheme: Letter Grade
Sampling distributions, central limit theorem, estimation, properties of point estimators, confidence intervals, hypothesis testing, common large sample tests, normal theory small sample tests, uniformly most powerful and likelihood ratio tests, linear models and least squares, correlation. Introduction to analysis of variance.
Prerequisite: STA 4321 or the equivalent.
STA 4502 Nonparametric Statistical Methods 3 Credits
Grading Scheme: Letter Grade
Introduction to nonparametric statistics, including one- and two-sample testing and estimation methods, one- and two-way layout models and correlation and regression models.
STA 4504 Categorical Data Analysis 3 Credits
Grading Scheme: Letter Grade
Description and inference using proportions and odds ratios, multi-way contingency tables, logistic regression and other generalized linear models, log-linear models applications.
STA 4702 Multivariate Statistical Methods 3 Credits
Grading Scheme: Letter Grade
Review of matrix theory, univariate normal, t, chi-squared and F distributions and multivariate normal distribution. Inference about multivariate means including Hotelling's T2, multivariate analysis of variance, multivariate regression and multivariate repeated measures. Inference about covariance structure including principal components, factor analysis and canonical correlation. Multivariate classification techniques including discriminant and cluster analyses. Additional topics at the discretion of the instructor, time permitting.
Prerequisite: (STA 3024 or STA 4210 or STA 4322 or STA 6127 or STA 6167) and (MAS 3114 or MAS 4105 or the equivalent).
STA 4712 Introduction to Survival Analysis 3 Credits
Grading Scheme: Letter Grade
Survival analysis data methods including Kaplan-Meier and Nelson estimators of the survival, accelerated failure time and proportional hazards models and frailty and recurrent event models.
Prerequisite: STA 4210.
STA 4821 Stochastic Processes 3 Credits
Grading Scheme: Letter Grade
Theoretical development of elementary stochastic processes, including Poisson processes and their generalizations, Markov chains, birth and death processes, branching processes, renewal processes, queuing processes and genetic and ecological processes.
Prerequisite: STA 4321 or equivalent.
STA 4853 Introduction to Time Series and Forecasting 3 Credits
Grading Scheme: Letter Grade
Stationarity, autocorrelation, ARMA models; frequency domain methods and the spectral density; forecasting methods; and computationally-oriented application to case studies.
STA 4905 Individual Work 1-5 Credits
Grading Scheme: Letter Grade
Special topics designed to meet the needs and interests of individual students.
Prerequisite: department permission.
STA 4911 Undergraduate Research in Statistics 0-3 Credits
Grading Scheme: S/U
Provides firsthand, supervised research. Projects may involve inquiry, design, investigation, scholarship, discovery, or application.
STA 4930 Special Topics 3 Credits
Grading Scheme: Letter Grade
Variable topics designed to meet the students' needs and interests.
Prerequisite: department permission.
STA 4940 Internship 1-3 Credits
Grading Scheme: S/U
Supervised activity associated with planning and/or analyzing data from a research project. Supervision by a faculty member or delegated authority and a post-internship written report are required. (S-U)
Prerequisite: STA 4211 and undergraduate coordinator permission.