STA 3032     Engineering Statistics (UF) . . . . . 3(CALL DEPT)
Prerequisite: MAC 2311
A survey of 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 regressions

STA 3162C      Applied Statistics . . . . . 4(S)
Prerequisite: MAC 2311
Inferential statistics from an applied point of view. Probability and sampling distributions, confidence intervals and hypothesis testing, ANOVA, correlation, simple and multiple linear regressions. SAS computer techniques. Lab required. (Gordon Rule Course: Applied Math)

STA 4XXX        Analysis of Variance . . . . . 3(F)
Prerequisite: STA 2023
Introducing concepts of analysis of variance (ANOVA); single-factor (one-way) ANOVA and two-factor (two-way) ANOVA with balanced and unbalanced data; random and mixed effects models. Offered concurrently with STA 5206; graduate student will be assigned additional work

STA 4173     Biostatistics Pending Faculty Senate Approval . . . . . 3(F,S,SS)
Prerequisite: STA 2023
A second course in statistics for students in the Biological Sciences. Topics covered include analysis of variance, regression analysis, nonparametric statistics, contingency tables. Offered concurrently with STA 5XXX; graduate student will be assigned additional work. (Gordon Rule Course: Applied Math)

STA 4321     Introduction to Mathematical Statistics I . . . . . 3(F,S)
Prerequisite: MAC 2312
Probability, conditional probability, distributions of random variables, distribution of functions of random variables, limiting distributions, multivariate probability distributions. (Gordon Rule Course: Applied Math)

STA 4322     Mathematical Statistics II   . . . . . 3(S)
Prerequisite: STA 4321
Point and interval estimates, measures of quality of estimates, Bayesian estimates, robust estimation, statistical hypothesis testing, including goodness of fit, contingency tables and ANOVA, SPR test, the Cramer-Rao inequality, multiple comparisons, completeness, distributions of quadratic forms, multivariate normal distributions. Offered concurrently with STA 5326; graduate students will be assigned additional work. (Gordon Rule Course: Applied Math)

STA 4664     Introduction to Statistical Quality Control . . . . . 3(S)
Prerequisite: STA 2023
Covers control charts, capability indices, and related topics used in process control. (Gordon Rule Course: Applied Math)

STA 5XXX        Biostatistics . . . . . 3(F,S,SS)
Prerequisite: STA 2023
A second course in statistics for students in the Biological Sciences. Topics covered include analysis of variance, regression analysis, nonparametric statistics, contingency tables. Offered concurrently with STA 4173; graduate student will be assigned additional work

STA 5166     Special Topics in Statistics . . . . . 3(S,SS)
Prerequisite: STA 2023 or STA 3162C
Introduction to one- and two-way ANOVA; nonparametric methods, correlation and linear regression analysis. Introduction to SAS

STA 5206     Analysis of Variance . . . . . 3(F)
Prerequisite: STA 2023
Introducing concepts of analysis of variance (ANOVA); single-factor (one-way) ANOVA and two-factor (two-way) ANOVA with balanced and unbalanced data; random and mixed effects models. Offered concurrently with STA 4XXX; graduate student will be assigned additional work

STA 5207     Applied Regression Analysis . . . . . 3(S)
Prerequisite: STA 2023 or STA 3162C
Regression analysis, simple and multiple; procedures for selection of a best set of regressors

STA 5326     Mathematical Statistics II . . . . . 3(S)
Prerequisite: STA 4321
Point and interval estimates, measures of quality of estimates, Bayesian estimates, robust estimation, statistical hypothesis testing, including goodness of fit, contingency tables and ANOVA, SPR test, the Cramer-Rao inequality, multiple comparisons, completeness, distributions of quadratic forms, multivariate normal distributions. Offered concurrently with STA 4322; graduate students will be assigned additional work

STA 6246     Design and Analysis of Experiments . . . . . 3(S)
Prerequisite: STA 5206
Further concepts in design and analysis of planned experiments with emphasis on confounding and fractional replications of factorial experiments; composite designs; incomplete block designs; estimation of variance components

STA 6507     Nonparametric Statistics  . . . . . 3(SS)
Prerequisite: STA 4321 and STA 2023 or STA 3162C
Extensive coverage of goodness-of-fit tests, location problems, association analysis and general nonparametric topics

STA 6607     Operations Research I . . . . . 3(F)
Prerequisite: STA 4321 and MAS 3105 or MAS 5107
Mathematical probability models and distributions; linear programming models; the simplex method; duality and sensitivity analysis; inventory models; queuing theory; simulation

STA 6608     Operations Research II . . . . . (S)
Prerequisite: STA 6607
Decision theory and games, PERT/CPM, Markovian decision process, integer programming, dynamic programming, reliability and maintenance

STA 6666     Statistical Quality Control I . . . . . (F)
Prerequisite: STA 4321 and STA 2023 or STA 3162C
Procedures used in acceptance sampling and statistical process control are based on concepts and theory from probability and statistics. Introduces the applications of these procedures, investigates them from the standpoint of their statistical properties and develops the methodology for construction, evaluation and comparison of procedures

STA 6707     Multivariate Methods . . . . . 3(F)
Prerequisites: STA 4321, STA 5206, or STA 5207
Multivariate extensions of Chi-Square and t-tests; discrimination and classification procedures; applications to diagnostic problems in biological, medical, anthropological and social research; multivariate analysis of variance; factor analysis and principle components analysis.

STA 6857     Time Series . . . . . 3(F)
Prerequisite: MAA 4212 and STA 5207
Box-Jenkins procedure applied to identification, estimation and verification of the time series processes

STA 6930     Proseminar in Statistics . . . . . 1(F,S)
Each M.A. candidate (except those who choose the thesis option), shall, under the direction of a project advisor, independently investigate a topic or topics in mathematics/statistics or mathematics education through the study of journal articles or other appropriate sources. The candidate shall submit a formal written report and make an oral presentation of the results of his/her investigations. The goal of the proseminar is to provide students an opportunity to integrate the total experience gained during their graduate training. Graded on satisfactory/unsatisfactory basis only. MA candidacy and permission is required