VCU Courses

College of Humanities and Sciences :: Statistical Sciences

STAT 208 Statistical Thinking

Semester course; 2 lecture and 1.5 laboratory hours. 3 credits. Prerequisite: satisfactory score on the VCU Mathematics Placement Test within the one-year period immediately preceding the beginning of the course, or a grade of C or better in MATH 131 or higher.An exploration of the use of statistics in the world around us through in-depth case studies. Emphasis is on understanding statistical studies, charts, tables and graphs frequently seen in various media sources. Laboratories involve learning activities centered on case studies. Students may receive credit toward graduation for only one of STAT 208, 210, 212, 312 or MGMT 301.

STAT 210 Basic Practice of Statistics

Semester course; 3 lecture hours. 3 credits. Prerequisite: MATH 131, MATH 141, MATH 151 or satisfactory score on the VCU Mathematics Placement Test within the one-year period immediately preceding the beginning of the course. An exception to this policy is made in the case where the stated alternative prerequisite course has been completed at VCU. Designed for students who will likely take another quantitative reasoning course for which statistics may be a prerequisite. Not open to mathematical sciences or computer science majors.Topics include examining distributions, examining relationships, producing data, sampling distributions and probability, introduction to inference. Students may receive credit toward graduation for only one of STAT 208, 210, 212, 312 or MGMT 301.

STAT 212 Concepts of Statistics

Semester course; 2 lecture and 2 laboratory hours. 3 credits. Prerequisite: MATH 200.An introduction to the nature of statistical thinking and the application of abstract systems to the resolution of nonabstract problems. Probability models for stochastic events. Parametric representations. Estimation, testing hypotheses and interval estimation with application to classical models. Laboratories include activity based learning and computer usage. A core course for mathematical sciences. Students may receive credit toward graduation for only one of STAT 208, 210, 212, 312 or MGMT 301.

STAT 291 Topics in Statistics

Semester course; 1-3 lecture hours. 1-3 credits. A study of selected topics in statistics. Specific topics may fulfill general education requirements. See the Schedule of Classes for specific topics and prerequisites.

STAT 309/MATH 309 Introduction to Probability Theory

Semester course; 3 lecture hours. 3 credits. Prerequisite: MATH 201. Completion of MATH 211 or MATH 300 (or equivalent knowledge) is strongly recommended.A study of the mathematical theory of probability, including finite and infinite sample spaces, random variables, discrete and continuous distributions, mathematical expectation, functions of random variables and sampling distributions.

STAT 312 Data Analysis and Statistics for Elementary Education

Semester course; 3 lecture hours. 3 credits. Prerequisites: MATH 361 and 362. Restricted to students majoring in the liberal studies concentration for early and elementary education.Understanding probability, describing data both graphically and numerically, regression/correlation, common distributions and interpretation, item analysis for tests, interpreting test scores and educational studies, experimental design and limitations, comparing results using t-tests and ANOVA. This course relies heavily on Excel as a data-analysis tool and requires one structured interaction at the elementary school level. Students may receive credit toward graduation for only one of STAT 208, 210, 212, 312 or MGMT 301.

STAT 314 Applications of Statistics

Semester course; 4 lecture hours. 4 credits. Prerequisite: STAT 210 or 212.A study of the concepts and application of statistical methods including: estimation and hypothesis testing for two sample problems; one factor analysis of variance and multiple comparisons; randomized block designs and analysis; inferences on categorical data, including chi-square test for independence for contingency tables; simple linear regression and correlation; multiple linear regression. Special topics include distribution free (nonparametric) methods in various statistical problems, two factor analysis of variance, and the use of a statistical software package for data analysis.

STAT 321 Introduction to Statistical Computing

Semester course; 3 lecture hours. 3 credits. Prerequisites: STAT 212 and MATH 200 or their equivalents.The application of computers to statistical practice using SAS, R or similar statistical software. Topics include data storage and retrieval, data modification and file handling, statistical and graphical data analysis, and simulation.

STAT 391 Topics in Statistics

Semester course; 1-3 lecture hours. 1-3 credits. A study of selected topics in statistics. See the Schedule of Classes for specific topics to be offered each semester and prerequisites.

STAT 404 Introduction to Statistical Inference

Semester course; 3 lecture hours. 3 credits. Prerequisites: Both STAT 212 and STAT/MATH 309, or permission of instructor.Framework for statistical inference. Point and interval estimation of population parameters. Hypothesis testing concepts, power functions, Neyman-Pearson lemma and likelihood ratio tests. Elementary decision theory concepts.

STAT 421 Computational Issues in Statistical Science

Semester course; 3 lecture hours. 3 credits. Prerequisites: STAT 212 and CMSC 245 or CMSC 255, and MATH 310, or their equivalents.Examination of the interface of statistics, computer science and numerical analysis. The course explores the fundamental problems of doing arithmetic with digital computers: rounding, truncation, errors and error propagation, stability and accuracy of algorithms. It then proceeds to examine extensions to the computation of probabilities, percentage points of probability distributions, random number generation, Monte Carlo methods and numerical methods in linear algebra. This course will require programming in higher level language.

STAT 490/OPER 490 Communications in Statistics and Operations Research

Semester course; 3 lecture hours. 3 credits. Prerequisites: ENGL 200 and STAT 314 or OPER 327, or permission of the instructor.Designed to help students attain proficiency in professional and academic communication in the context of statistics and operations research. Focus on the discipline-specific communication skills necessary to excel in careers or graduate studies in these disciplines.

STAT 492 Independent Study

Semester course; variable hours. 2, 3 or 4 credits per semester. Maximum 4 credits per semester; maximum total of 6 credits. Generally open to students of only junior or senior standing who have acquired at least 12 credits in the departmental discipline. Determination of the amount of credit and permission of instructor and department chair must be procured prior to registration of the course.The student must submit a proposal for investigating some area or problem not contained in the regular curriculum. The results of the student's study will be presented in a report.

STAT 503 Introduction to Stochastic Processes

Semester course; 3 lecture hours. 3 credits. Prerequisites: MATH 307 and STAT/MATH 309.A continuation of topics given in STAT/MATH 309. An elementary introduction to stochastic processes and their applications, including Markov chains and Poisson processes.

STAT 508/SOCY 508 Introduction to Social Statistics

Semester course; 2 lecture and 2 laboratory hours. 3 credits. Introduction to statistical methods applicable in a variety of settings, with emphasis on nonexperimental data. Data description and analysis including chi-square and t-tests, using a statistical computing package. Not applicable toward M.S. in Mathematical Sciences, Sociology or Computer Science.

STAT 513-514/BIOS 513-514 Mathematical Statistics I-II

Continuous courses; 3 lecture hours. 3-3 credits. Prerequisite: MATH 307.Probability, random variables and their properties, distributions, moment generating functions, limit theorems, estimators and their properties; Neyman-Pearson and likelihood ratio criteria for testing hypotheses.

STAT 523/BIOS 523 Nonparametric Statistical Methods

Semester course; 3 lecture hours. 3 credits. Prerequisites: Any two courses of statistics or permission of instructor.Estimation and hypothesis testing when the form of the underlying distribution is unknown. One-, two- and k-sample problems. Tests of randomness, Kolmogorov-Smirnov tests, analysis of contingency tables and coefficients of association.

STAT 541 Applied Statistics for Engineers and Scientists

Semester course; 3 lecture hours. 3 credits. Prerequisites: MATH 200-201 or equivalent, and a working knowledge of computers.An introduction to applied statistics intended primarily for students in mathematical sciences, engineering and the Commonwealth Graduate Engineering Program. The fundamental ideas of the collection and display of information, descriptive statistics and exploratory data analysis, elementary probability theory, frequency distributions and sampling are covered. Other topics include tests of hypotheses and confidence intervals for one and two sample problems; ANOVA; principles of one-factor experimental designs including randomized complete black designs, fixed and random effects and multiple comparisons; correlation and linear regression analysis; control charts; contingency tables and goodness-of-fit. Students may receive degree credit for only one of STAT 541, STAT 543 or BIOS 553.

STAT 543/BIOS 543 Statistical Methods I

Semester course; 3 lecture hours. 3 credits. Prerequisite: Graduate standing, or one course in statistics and permission of instructor.Basic concepts and techniques of statistical methods, including: the collection and display of information, data analysis and statistical measures; variation, sampling and sampling distributions; point estimation, confidence intervals and tests of hypotheses for one and two sample problems; principles of one-factor experimental design, one-way analysis of variance and multiple comparisons; correlation and simple linear regression analysis; contingency tables and tests for goodness of fit. Students may not receive degree credit for both STAT 541 and STAT 543. STAT 543 is not applicable toward the M.S. degree in mathematical sciences or the M.S. degree in computer science.

STAT 544/BIOS 544 Statistical Methods II

Semester course; 3 lecture hours. 3 credits. Prerequisite: One of the following: STAT 314, 541, 543 or equivalent.Advanced treatment of the design of experiments and the statistical analysis of experimental data using analysis of variance (ANOVA) and multiple-regression. Includes the use of a statistical software package for data analysis.

STAT 546 Linear Models

Semester course; 3 lecture hours. 3 credits. Prerequisites: STAT 513 and one applied course in statistics, or permission of instructor.A study of the theory underlying the general linear model and general linear hypothesis. Topics include the general linear model for quantitative responses (including multiple regression, analysis of variance and analysis of covariance), binomial regression models for binary data (including logistic regression and probit models) and Poisson regression models for count data (including log-linear models for contingency tables and hazard models for survival data).

STAT 591 Topics in Statistics

Semester course; 3 lecture hours. 3 credits. May be repeated for credit. Prerequisite: Permission of the instructor. Course open to qualified undergraduates.Selected topics in statistics.

STAT 608/SOCY 608 Statistics for Social Research

Semester course; 2 lecture and 2 laboratory hours. 3 credits. Prerequisite: STAT/SOCY 508 or SOCY 214 or permission of instructor.Statistical methods applied in social research. Topics include analysis of variance, correlation and regression, including stepwise methods, and the analysis of discrete data. Study of a statistical package, emphasizing manipulation of survey data sets. Not applicable toward M.S. in Mathematical Sciences or Computer Science.

STAT 613-614 Stochastic Processes

Continuous courses; 3 lecture hours. 3-3 credits. Prerequisites: MATH 508 and STAT 514.Introduction to the theory and applications of stochastic processes. Random walks, Markov processes, queuing theory, renewal theory, birth-death and diffusion processes. Time series, spectral analysis, filter, autocorrelation.

STAT 623 Discrete Multivariate Analysis

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 544 or STAT/SOCY 608 or equivalent.Methods for the analysis of categorical data, including logistic regression and the general log-linear model. Emphasis on social and biomedical applications of these techniques using SPSS and SAS software.

STAT 626 Complex Sampling Designs and Variance Estimation

Semester course; 3 lecture hours. 3 credits. Prerequisites: STAT 544 and 514.The analysis of data from surveys that use multistage samples, and connections to the analysis of observational studies and experiments with missing data. Computer intensive methodologies such as the jackknife and bootstrap will be introduced and applied to the problem of variance estimation in these diverse settings.

STAT 636/OPER 636 Machine Learning Algorithms

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 541 or equivalent.Includes an in-depth analysis of machine learning algorithms for data mining, equipping students with skills necessary for the design of new algorithms. Analyses will include framing algorithms as optimization problems and a probabilistic analysis of algorithms. Students will be exposed to current areas of research in the construction of data mining algorithms.

STAT 642 Design and Analysis of Experiments I

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 541, BIOS 553 or an equivalent statistics course.An introduction to the design and analysis of experiments. Topics include the design and analysis of completely randomized designs, one variable block designs, the family of Latin square designs and split-plot designs. Introductions are also given to multiple comparison procedures and contrasts, analysis of covariance and factorial experiments. Applications involve the use of a statistical software package.

STAT 643 Applied Linear Regression

Semester course; 3 lecture hours. 3 credits. Prerequisite: MATH 200-201, STAT 212 and MATH 310 or equivalents.An introduction to the concepts and methods of linear regression analysis. Topics include simple linear regression, multiple linear regression, the impact of model misspecification, model selection criteria, residual analysis, influence diagnostics, diagnostic plots, multicollinearity, transformations and response surface methodology. Applications involve the use of a statistical software package.

STAT 645 Bayesian Decision Theory

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 514.Presents statistical decision theory and Bayesian analysis, with discussions of loss functions, risk, utility, prior information; conjugate families; posterior distributions, estimation, hypothesis testing; empirical and hierarchical Bayes analysis; and robustness.

STAT 648/OPER 648 Systems Reliability Analysis

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 541 or equivalent or permission of instructor.An introduction to engineering reliability and risk analysis, specifically failure data analysis, maintenance problems, system reliability and probabilistic risk assessment. Applications in computer science and engineering will include stochastic characterization of wear in hardware systems and the development of failure models for software systems. Decision problems such as the optimal maintenance of repairable systems and optimal testing policies for hardware and software systems will be examined. The analysis of risk through fault trees, event trees and accident precursor analysis also will be discussed.

STAT 649/OPER 649 Statistical Quality Control

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 541 or equivalent, or permission of instructor.Demonstrates how statistics and data analysis can be applied effectively to process control and management. Topics include the definition of quality, its measurement through statistical techniques, variable and attribute control charts, CUSUM charts, multivariate control charts, process capability analysis, design of experiments, and classical and Bayesian acceptance sampling. Statistical software will be used to apply the techniques to real-life case studies from manufacturing and service industries.

STAT 650/BIOS 650 Design and Analysis of Response Surface Experiments

Semester course; 3 lecture hours. 3 lecture hours. Prerequisites: STAT 541 and STAT 544 or BIOS 553-554, or permission of the instructor.Philosophy, terminology and nomenclature for response surface methodology, analysis in the vicinity of the stationary point, canonical analysis, description of the response surface, rotatability, uniform information designs, central composite designs and design optimality.

STAT 675 Time Series Analysis I

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 543 or equivalent.Analysis of data when observations are not mutually independent, stationary and nonstationary time series, ARIMA modeling, trend elimination, seasonal models, intervention analysis, transfer function analysis, prediction and applications in economics and engineering.

STAT 690/OPER 690 Research and Communications Seminar

Semester course; 3 lecture hours. 3 credits. Prerequisites: 9 graduate credits in operations research (OPER) and/or statistics (STAT) and permission of the instructor.Designed to help students attain proficiency in professional and academic communication and research in the context of statistics and operations research. The course focuses on the discipline-specific communication and research skills necessary to excel in careers or graduate studies in these disciplines.

STAT 691 Special Topics in Statistics

Semester course; 1-3 lecture hours. 1-3 credits. May be repeated for credit. Prerequisite: Permission of instructor.A detailed study of selected topics in statistics.

STAT 696/OPER 696 Applied Project

Semester course; variable hours (to be arranged). 1-3 credits. A total of three credits will be applied to the M.S. in Mathematical Sciences (operations research or statistics concentration). Can be repeated for credit. Prerequisite: STAT/OPER 690 or permission of the faculty adviser.Designed to allow students to apply concepts and theories learned in other courses to a practical situation. Includes the selection, written description, completion and written report of the project and a presentation of the findings. Students may not receive credit for both OPER/STAT 696 and OPER/STAT 698.

STAT 697 Directed Research

Semester course; variable hours. 1-3 credits per semester. May be repeated for credit. Prerequisite: Graduate standing.Supervised individual research and study in an area not covered in the present curriculum or in one that significantly extends present coverage. Research culminates with an oral presentation and submission of a written version of this presentation to the supervising faculty member.

STAT 698 Thesis

Hours to be arranged. 1-3 credits. A total of 3 or 6 credits may be applied to the M.S. in Mathematical Sciences/Statistics. (A total of 3 credits for an expository thesis or a total of 6 credits for a research thesis.) May be repeated for credit. Prerequisite: Graduate standing.Independent research culminating in the writing of the required thesis as described in this bulletin. Grade of "S," "U" or "F" may be assigned in this course.

STAT 736/OPER 736 Mathematics of Knowledge and Search Engines

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 541 or equivalent.Investigates the mathematics, methods and algorithms for searching for and extracting structures of interest (knowledge) from large and possibly high-dimensional datasets. The motivation is the rapid and phenomenal growth of the search engine (as demonstrated by Google) as a major tool for search on the Internet, which has impacted commerce, education and the study of social, financial and scientific datasets. The development of the mathematical and statistical learning algorithms behind these search engines has led to advances in how large, high-dimensional datasets can be effectively analyzed for the extraction of knowledge.

STAT 742 Design and Analysis of Experiments II

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 642.Advanced study of the design and analysis of experiments. Topics include the design and analysis of incomplete block designs, factorial designs, fractional factorial designs, asymmetric factorial designs, blocking in fractional factorial designs, nested designs and response surface designs. Applications involve the use of a statistical software package.

STAT 744 Regression II

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 643 or equivalent.Theoretical development and advanced applications of the general linear regression model and nonlinear regression models. Topics include an overview of multiple linear regression, generalized least squares and weighted regression, procedures for diagnosing and combating multicollinearity, advanced model selection criteria, influence diagnostics including multiple observation diagnostics and singular value decomposition, nonlinear regression, Poisson regression, logistic regression, generalized linear models and the exponential family, variance modeling and nonparametric regression. Applications involve the use of a statistical software package.

STAT 745 Advanced Bayesian Statistics

Semester course; 3 lecture hours. 3 credits. Prerequisite: STAT 645.Introduces modern aspects of Bayesian methodology. Numerical and sampling techniques such as the Gibbs sampler, importance sampling resampling, Monte Carlo integration, Metropolis-Hastings sampling and adaptive sampling methods. Inferential methods including model selection, highest probability models, Bayesian model averaging, Markov chain Monte Carlo model composition. A large portion of the course will survey the current literature in the areas listed above as well as applications of the methods.

STAT 791 Special Topics in Statistics

Semester course; 1-3 lecture hours. 1-3 credits. May be repeated for credit. Prerequisitie: permission of instructor.A detailed study of selected advanced topics in statistics.

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