2004-2005
CATALOG |

Table
of Contents Welcome Telephone Directory Academic Calendars Year 2004/2005 Fall Semester 2004 Spring Semester 2005 Summer Semester 2005 University Mission Accreditations Degrees, Areas of Specialization, Minors Admissions After Admission Financial Assistance Student Activities Student Services and Resources Tuition and Fees Military and Veterans Information Registration and Records Academic Policies Graduation and General Degree Requirements Public Service and Research Centers College Mission Statements Undergraduate Degree Programs Master's Degree Programs Specialist Degree Programs Doctoral Degree Programs Course Numbering System Course Listings and Descriptions Administration Faculty Index |
Course Listings/Descriptions Semester offering codes corrected and posted on June 7, 2004. |

STA-StatisticsSTA 2023 Elements of Statistics . . . . . 3(F,S,SS)Prerequisite: MAT 1033. Fundamental statistical concepts. Probability, inference, estimation, hypothesis testing. (Gordon Rule Course: Applied Math) and (General Studies Course: MAT/MO) 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 regression. 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 regression. SAS computer techniques. Lab required. (Gordon Rule Course: Applied Math) STA 4XXX 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 4173 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. (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 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 or STA 3162C. Statistical methods useful in design and analysis of experiments in physical, biological and social sciences. Analysis of variance including randomized blocks. Latin square, factorial arrangements, regression. 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 . . . . . 3(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 . . . . . 3(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. STA 6971 Thesis . . . . . 1-6(F,S,SS)Graded on satisfactory/unsatisfactory basis only. Permission is required. |