Department of STATISTICS
College of Arts and Sciences
Chair: Myles Hollander; Director, Statistical Consulting Center: Zahn; Professors: Hollander, Huffer, Leysieffer, Lin, McGee, McKeague, Sethuraman, Zahn; Associate Professors: Niu, Song; Assistant Professors: Li, Srivastava; Visiting Assistant Professors: Bunea, Chattopadhyay, Chicken; Assistant in Statistics: Ramsier; Professors Emeriti: Basu, Bradley, Marsaglia, Proschan
The Department of Statistics offers programs leading to the bachelor of science (BS) degree (including an honors degree) in statistics with emphases in statistics and probability theory. These are mathematical disciplines that describe concepts of uncertainty in a quantitative way. The disciplines draw inspiration from the many areas to which they are applied. A statistician could be called upon to help decide whether an anesthetic has an adverse health effect upon operating room nurses, recognize images taken by remote sensors, analyze errors of measurement in a scientific experiment, determine public attitudes in an opinion poll, determine if a medical or pharmacological patient intervention is successful, or work with a team to design and analyze an experiment. Random phenomena such as these are handled through the use of probability models, which serve as guides in decision making, interpretation of data, and allocation of resources. Some courses in the curriculum emphasize the construction of probability models, whereas others focus upon the methodology of application of these models.
In the study of statistics, students use and enrich their mathematical expertise and orient their study of the mathematical sciences toward useful and relevant purposes in society. Significant opportunities for well-trained persons with one or more of the specializations of statistics or probability arise in many career environments, such as the social sciences, the natural sciences, business, industry, the health services, and government services. Flexible, individually planned programs of study for minors or majors, including an honors option, are available. Interested students should contact the director of the undergraduate program for more information.
The Department of Statistics offers a wide selection of undergraduate courses in statistical methods for nonmajors with minimal background in mathematics. STA 2122 or STA 2171 is a prerequisite for the remaining courses in the series, which are STA 3024, 4102, 4202, 4203, 4222, 4502, and 4702, and 4853.
The Department of Statistics maintains a laboratory for computational vision, a statistical consulting center, a departmental library and reading room, the Wilcoxon Memorial Room, and provides facilities for computation in connection with course work and research. Instruction is available and use of computers is arranged for approved purposes. The statistics department has extensive computing facilities, which include a local area network of microcomputers, printers and a new laboratory for computational vision equipped with high-performance computers and accessories.
State of Florida Common Course Prerequisites
Revisions to the 2003-2004 State of Florida Common Course Prerequisites were not available at the time this document went to press. Please refer to http://www.facts.org and click on "Academic Reference Manual." Select the 2003-2004 catalog year under the 'Common Prerequisites Manuals' subheading. Students are strongly encouraged to consult with their academic advisor prior to making any decisions based on these prerequisites.
The State of Florida has identified common course prerequisites for this University degree program. These prerequisites are lower-level courses that are required for preparation for the University major prior to a student receiving a baccalaureate degree from The Florida State University. They may be taken either at a community college or in a university lower-division program. It is preferred that these common course prerequisites be completed in the freshman and sophomore years.
The following lists the common course prerequisites or approved substitutions necessary for this degree program:
- One course for three (3) semester hours (COP prefix) in a computer language (Pascal, FORTRAN, C, C+, or C++);
- MAC X311;
- MAC X312;
- One laboratory-based science course for four (4) semester hours from the following: BSC XXXX/XXXXL or CHM XXXX/XXXXL or PHY XXXX/XXXXL.
Requirements
Please review all college-wide degree requirements summarized in the "College of Arts and Sciences" chapter of this General Bulletin.
Requirements for a Major in Statistics
Major
Eighteen (18) semester hours in statistics courses numbered at the 4000 level are required, including STA 4322 and 4442.
Note: STA 2122, STA2171 or STA 3032 may be taken in place of a 4000 level course other than those specified. Additional requirements include CGS 3408 or 3460; MAC 2312, 2313; and MAS 3105. A grade of "C-" or better must be earned in each statistics, mathematics, or computer science course counted toward the major. At least nine (9) semester hours of statistics courses counted toward the major must be taken in the Department of Statistics at The Florida State University. Other statistics courses must be approved by the department.
Options
STA 4322 and 4442 constitute a basic core. Further courses may be selected for emphasis in statistical methodology, statistical theory, probability theory, stochastic processes, or actuarial science (MAP 4170, 4175). Students anticipating graduate study in statistics are encouraged to take additional mathematics courses such as MAA 4226, 4227, and MTG 4302.
Minor
The minor may be in any of the departmental or interdepartmental fields approved by the College of Arts and Sciences. A minor in mathematics may include MAC 2311, 2312, 2313, and MAS 3105.
Honors in the Major
The Department of Statistics offers honors in the major to encourage talented students to undertake independent research. For requirements and other information, see the "University Honors Program and Honor Societies" chapter of this General Bulletin.
Requirements for a Minor in Statistics
Required are twelve (12) semester hours in statistics courses numbered at the 4000 level, including STA 2122, 2171, or 4442. (Note: STA 2122, 2171, or STA 3032 may be considered equivalent to a 4000 level course). Courses should be selected in consultation with the director of the undergraduate statistics program. A grade of
"C-" or better must be earned in each course counted toward the minor. At least six (6) semester hours in statistics courses counted toward the minor must be taken in the Department of Statistics at The Florida State University. Other statistics courses must be approved by the department.
Examples of Options
- 1. A minor in statistical methodology with minimal mathematical prerequisites: STA 2122 or STA 2171, plus eight (8) semester hours selected from any of 4102, 4202, 4203, 4222, 4502, and 4702;
- 2. A minor with statistical theory as well as methodology: STA 4322 and 4442 or 3032, plus six (6) hours selected from any of 4102, 4202, 4203, 4222, 4502, 4702, and 4853.
Definition of Prefixes
- QMB - Quantitative Methods in Business
- STA - Statistics
Undergraduate Courses
ISC 3121. Science, Technology, and Society (3)
SCE 4939r. Seminar in Contemporary Science, Mathematics, and Science Education (1).
Note: for descriptions of the above courses, see interdisciplinary science courses listed in the "College of Arts and Sciences" chapter of this General Bulletin.
QMB 3200. Quantitative Methods for Business Decisions (3).
STA 1013. Statistics through Example (3). Fundamental concepts of statistics including descriptive measures, randomness, estimation of proportions, central tendency, rare event principle, association versus causation, and risks.
STA 2023. Fundamental Business Statistics (3). Prerequisite: MAC 1105 or its equivalent. No credit is given for STA 2023 if "C-" or better has been previously earned in STA 2122, 2171,or 3032. High school students who earn a "3" or better on the AP statistics exam will be given credit for STA 2023. Statistical applications in business, involving graphical and numerical descriptions of data, data collection, elementary probability, random variables, binomial and normal distributions, sampling distributions, and confidence intervals and hypothesis tests for a single example.
STA 2122. Introduction to Applied Statistics (4). Prerequisite: MAC 1105. Subsequent credit for STA 5126 is not permitted. No credit is given for STA 2122 if a "C-" or better is earned in STA 2171, 3032 or QMB 3200. Only two (2) hours credit given for STA 2122 if "C-" or better previously earned in STA 2023 or 3014. Data collection, sample variation, basic probability, confidence intervals, hypothesis testing, analysis of variance, contingency tables, correlation, regression.
STA 2171. Statistics for Biology (4). Prerequisite: MAC 2311. STA 2171 is for biology majors only. Other students must have approval from the Department of Statistics. Only two (2) semester hours of credit are given for STA 2171 if
"C-" or better has been previously earned in STA 2023. No credit is given for STA 2171 if a "C-" or better has been previously earned in STA 2122 or 3032, or QMB 3200. This course provides an introduction to statistics emphasizing applications to biology. Topics include: Descriptive statistics, elementary probablity, the binomial and normal distributions, confidence intervals and hypothesis tests for means and proportions, correlation and regression, contingency tables and goodness-of-fit tests as well as analysis of variance.
STA 3024. Intermediate Applied Statistics (3). Prerequisite: STA 2122 or 2171. Course covers linear and multiple regression; one-and-two-way analysis of variance; chi-square and contingency tables; design, analysis, evaluation and interpretation of statistical models. Well-prepared students can skip STA 3024 and take either STA 4202 or 4203. STA 3024 does not count toward statistics majors or statistics minors.
STA 3032. Probability and Statistics for Sciences and Engineering (5). Prerequisite: MAC 2312. Only two (2) semester hours of credit is given for STA 3032 if a "C-" or better previously has been earned in STA 2122, 2171, or 4442. This course will cover calculus-based probability, discrete and continous random variables, joint distributions, sampling distributions and the central limit theorem. Topics include descriptive statistics, interval estimates and hypothesis tests, ANOVA, correlation, simple and multiple regression, analysis of categorical data, and statistical quality control.
STA 4102. Computational Methods in Statistics I (3). Prerequisites: At least one previous course in statistics above STA 1013; some previous programming experience; or permission of the instructor. Matlab and a programming language (C/Fortran) will be used. Floating point arithmetic, numerical matrix analysis, multiple regression analysis, non-linear optimization, root finding, numerical integration, Monte-Carlo sampling, survey of density estimation.
STA 4103. Computational Methods in Statistics II (3). Prerequisite: STA 4102 or permission of the instructor. Matlab and a programming language (C/Fortran) will be used. A continuation of STA 4102 in computational techniques for linear and non-linear statistics. Statistical image understanding, elements of pattern theory, simulated annealing, Metropolis-Hastings algorithm, Gibbs sampling.
STA 4202. Analysis of Variance and Design of Experiments (3). Prerequisites: STA 2122, 2171, 3032, or QMB 3200. Subsequent credit for STA 5206 is not permitted. Only two (2) hours credit will be given for STA 4202 if "C-" or better has been earned previously in STA 3024. One and two-way classifications, nesting, blocking, multiple comparisons, incomplete designs, variance components, factorial designs, confounding.
STA 4203. Applied Regression Methods (3). Prerequisites: STA 2122, 2171, 3032, or QMB 3200. Subsequent credit for STA 5207 is not permitted. Only two (2) hours credit will be given for STA 4203 if "C-" or better has been earned previously in STA 3024. General linear hypothesis, multiple correlation and regression, residual analysis, and model identification.
STA 4222. Sample Surveys (3). Prerequisite: A course in statistics above STA 1013 or consent of instructor. Simple, stratified, systematic, and cluster random sampling. Ratio and regression estimation, multistage sampling.
STA 4321. Introduction to Mathematical Statistics (3). Prerequisite: MAC 2313. Subsequent credit for STA 5354 is not permitted (for nonmajors only). Distributions of random variables, conditional probability and stochastic independence, special distributions, sampling distributions, estimation, tests of hypotheses, regression, one way ANOVA. Credit for STA 4322 is not permitted.
STA 4322. Mathematical Statistics (3). Prerequisites: STA 4442; MAC 2313. Subsequent credit for STA 5325 is not permitted. Sufficiency, point estimation, confidence intervals, hypothesis testing, regression, linear models, Bayesian analysis.
STA 4442. Introductory Probability I (3). Prerequisite: MAC 2312. Subsequent credit for STA 4442 is not permitted if "C-" or better has been previously earned in STA 3032. Subsequent credit for STA 5440 is not permitted. Random variables, probability distributions, independence, sums of random variables, generating functions, central limit theorem, laws of large numbers.
STA 4502. Applied Nonparametric Statistics (3). Prerequisite: A course in statistics above STA 1013 or consent of instructor. Subsequent credit for STA 5507 is not permitted. Application of nonparametric tests, estimates, confidence intervals, and multiple comparison procedures.
STA 4664. Statistics for Quality and Productivity (3). Prerequisites: STA 4322 or consent of instructor and one of: STA 2122, 2171, 3032, or 4442. Deming's ideas, graphical methods, control charts, design of experiments for product and process improvement.
STA 4702. Applied Multivariate Analysis (3). Prerequisite: STA 4203 or 4322. Subsequent credit for STA 5707 is not permitted. Principal components and factor analysis, canonical correlation, discriminant analysis, multivariate analysis of variance, multidimensional contingency tables, cluster analysis.
STA 4853. Time Series and Forecasting Methods (3). Prerequisites: QMB 3200 or equivalent; STA 2122, 2171, 3032; knowledge of PC's or UNIX. Autoregressive, moving average and mixed models, autocovariance and autocorrelation functions, model identification, forecasting techniques, seasonal model identification, estimation and forecasting, intervention and transfer function model identification, estimation and forecasting. Subsequent credit for STA 5856 is not permitted.
STA 4905r. Directed Individual Study (2-3). (S/U grade only.) May be repeated to a maximum of twelve (12) semester hours.
STA 4930r. Selected Topics in Statistics, Probability, or Operations Research (2-3). May be repeated to a maximum of twelve (12) semester hours.
STA 4970r. Honors Thesis in Statistics (3). Students selected by the University and the department honors programs may take this course. Consent of the thesis adviser is mandatory. May be repeated to a maximum of six (6) semester hours.
Graduate Courses
STA 5106. Computational Methods in Statistics I (3).
STA 5107. Computational Methods in Statistics II (3).
STA 5126. Introduction to Applied Statistics (4).
STA 5166. Statistics in Applications I (3).
STA 5167. Statistics in Applications II (3).
STA 5168. Statistics in Applications III (3).
STA 5169. Advanced Applied Statistics (3).
STA 5176. Statistical Modeling with Application to Biology (3).
STA 5206. Analysis of Variance and Design of Experiments (3).
STA 5207. Applied Regression Methods (3).
STA 5208. Linear Statistical Models (3).
STA 5225. Sample Surveys (3).
STA 5325. Mathematical Statistics (3).
STA 5326. Distribution Theory and Inference (3).
STA 5327. Statistical Inference (3).
STA 5334. Limit Theory of Statistics (3).
STA 5440. Introductory Probability I (3).
STA 5446. Probability and Measure (3).
STA 5447. Probability Theory (3).
STA 5507. Applied Nonparametric Statistics (3).
STA 5619. Operations Research: Linear and Dynamic Programming (3).
STA 5666. Statistics for Quality and Productivity (3).
STA 5676. Reliability Theory and Life Testing (4).
STA 5707. Applied Multivariate Analysis (3).
STA 5746. Multivariate Analysis (3).
STA 5807r. Topics in Stochastic Processes (3).
STA 5856. Time Series and Forecasting Methods (3).
STA 5906r. Directed Individual Study (1-12). (S/U grade only.)
STA 5910r. Supervised Research (1-5).(S/U grade only.)
STA 5920r. Statistics Colloquium (1).(S/U grade only.)
STA 5934r. Selected Topics in Statistics, Probability, or Operations Research (2-3).
STA 5936. Graduate Orientation Seminar (1). (S/U grade only.)
STA 5939. Introduction to Statistical Consulting (3). (S/U grade only.)
STA 5940r. Supervised Consulting (1-3). (S/U grade only.)
STA 5941r. Supervised Teaching (1-5). (S/U grade only.)
STA 6246r. Advanced Topics in Applied Statistics (2-3).
STA 6346. Advanced Statistical Inference (3).
STA 6466. Advanced Probability (3).
STA 6468r. Advanced Topics in Probability and Statistics (2-3).
STA 6555. Nonparametric Curve Estimation (3).
STA 6709. Spatial Statistics (3).
STA 6858. Advanced Time Series Analysis (3).
STA 6906r. Directed Individual Study (1-12). (S/U grade only.)
For listings relating to graduate course work for thesis, dissertation, and master's and doctoral examinations and defense, consult the Graduate Bulletin.
TAX ACCOUNTING:
see Accounting
|
