| source Rice (X) |
level |
department Statistics (X) |
STAT 100 - DATA, MODELS, AND REALITY: AN INTRODUCTION TO THE SCIENTIFIC METHOD Credits: 3 Course URL: http://www.owlnet.rice.edu/~stat100 The formation of models of reality and the ways models are tested by their analysis in the light of data are considered. We cover a variety of examples from antiquity to the present time. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 280 - ELEMENTARY APPLIED STATISTICS Credits: 4 Course URL: http://statistics.rice.edu/courses.cfm Topics include basic probability, descriptive statistics, probability distributions, confidence intervals, significance testing, simple linear regression and correlation, association between categorized variables. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 281 - THE ROLE OF CHANCE IN AN INFORMATION WORLD Credits: 3 The concept of probability is a powerful idea pervading many aspects of our lives and this notion has a surprisingly long history. This course is meant to be accessible to any curious undergraduate (or graduate student) and starts out with the colorful early history of the concept. Based on this background, during the next phase of course, we will develop the precise concepts that support the intuition. We move on to discussing the concept of probability and its use in an essential manner in the physics, computer science and mathematical finance. Mathematical background typical of a sophomore or junior in science, engineering, business or any field with a quantitative foundations, will be adequate. Cross-listed with COMP 281 and ELEC 281. Cross-list: COMP 281, ELEC 281. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 300 - MODEL BUILDING Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm Examples to illustrate mathematical and statistical formulation (modeling) of scientific problems, their solution and interpretation. Problems from engineering, epidemiology, economics, and other areas are covered. Real-world situations are emphasized. Satisfies statistics design criteria. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 305 - INTRODUCTION TO STATISTICS FOR BIOSCIENCES Credits: 4 Course URL: http://www.owlnet.rice.edu/~stat305 An introduction to statistics for Biosciences with emphasis on statistical models and data analysis techniques. Computer-assisted data analysis, examples, is explored in laboratory sessions. Topics include descriptive statistics, correlation and regression, categorical data analysis, statistical inference through confidence intervals and significance testing, rates, and proportions, basic epidemiology. Real-world examples are emphasized; for example, genetics, dose-response, biological assays. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 310 - PROBABILITY AND STATISTICS Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm Probability and the central concepts and methods of statistics including probability distributions, expectation, estimation, hypothesis testing, sampling distributions, linear models. Section 1 presents the general use in multiple disciplines; section 2 focuses on problem sets and examples in civil and environmental engineering. Cross-list: ECON 382. Recommended prerequisite(s): MATH 212. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 312 - PROBABILITY & STATISTICS FOR CIVIL AND ENVIRONMENTAL ENGINEERS Credits: 3 Basic methodologies and problem solving of probibility and statistics for civil and environmental engineering. Calculus is required. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 313 - UNCERTAINTY AND RISK IN URBAN INFRASTRUCTURES Credits: 3 Practical applications and relevance of infrastructure risk are developed in the context of real engineering problems and phenomena, including unique systems and challenges of the gulf const area. The course starts with a survey of the roles of probability in engineering and focuses on computer-based methods, the Bayesian approach, risk analysis tools, and infrastructure safety. Cross-list: CEVE 313. Preferably section 2 of STAT 310. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 331 - APPLIED PROBABILITY Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm Elementary probability theory, conditional probability, independence, discrete and continuous random variables, expectation, standard discrete and continuous distributions, transformation techniques, central limit theorems, estimation, and correlation. Selected topics such as the Poisson process, Markov chains, and statistical techniques. Illustrations from engineering are emphasized. Cross-list: ELEC 331. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 385 - METHODS OF DATA ANALYSIS AND SYSTEM OPTIMIZATION Credits: 4 Course URL: http://statistics.rice.edu/courses.cfm The three general topic areas covered in this methodology oriented course are statistical methods including regression, sampling, and experimental design; simulation based methods in statistics, queuing and inventory problems; and an introduction to optimization methods. Excel will serve as the basic computing software. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 400 - ECONOMETRICS Credits: 3 Survey of estimation and forecasting models. Includes multiple regression time series analysis. A good understanding of linear algebra is highly desirable. Required for mathematical economic analysis majors. Cross-list: ECON 400. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 405 - STATISTICAL COMPUTING AND GRAPHICS Credits: 3 Programming techniques and tools useful and advanced statistical studies. Higher level graphical methods and exploratory data analysis. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 410 - INTRODUCTION TO REGRESSION AND STATISTICAL COMPUTING Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm A survey of regression, linear models, and experimental design. Topics include simple and multiple linear regression, single- and multi-factor studies, analysis of variance, analysis of covariance, model selection, diagnostics. Data analysis using statistical software is emphasized. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 411 - ADVANCED STATISTICAL METHODS Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm Advanced topics in statistical applications such as sampling, experimental design and statistical process control. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 421 - COMPUTATIONAL FINANCE II: TIME SERIES ANALYSIS Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm Applied time series modeling and forecasting, with applications to financial markets. UG/GR version: STAT 621. STAT 621 is a graduate version of STAT 421 with advanced assignments. Graduate/Undergraduate Equivalency: STAT 621. Recommended prerequisite(s): STAT 410. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 422 - BAYESIAN DATA ANALYSIS Credits: 3 Course URL: http://www.owlnet.rice/~stat422 This course will cover Bayesian methods for analyzing data. The emphasis will be on applied data analysis rather than theoretical development. We will consider a variety of models, including linear regression, hierarchical models, and models for categorical data. Computational methods will be emphasized. Course taught at the University of Texas - Health Science Center. Graduate/Undergraduate Equivalency: STAT 622. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 423 - PROBABILITY IN BIOINFORMATICS AND GENETICS Credits: 3 Course URL: http://statistics.rice.edu.courses.cfm Course introduces the student to modern biotechnology and genomic data. Statistical methods to analyze genomic data are covered, including probability models, basic stochastic processes, and statistical modeling. Biological topics include DNA sequence analysis, phylogenetic inference, gene finding, and molecular evolution. UG/GR version: STAT 623. Graduate/Undergraduate Equivalency: STAT 623. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 431 - OVERVIEW OF MATHEMATICAL STATISTICS Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm Topics include random variables, distributions, transformations, moment generating functions, common families of distributions, independence, sampling distributions, the basics of estimation theory, hypothesis testing and Bayesian inference. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 440 - STATISTICS FOR BIOENGINEERING Credits: 1 Course covers application of statistics to bioengineering. Topics include descriptive statistics, estimation, hypothesis testing, ANOVA, and regression. Offered first five weeks of the semester. Cross-list: BIOE 440. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 450 - STATISTICAL DESIGN IN PRACTICE Credits: 3 This course introduces current theoretical and applied problems encountered in statistical practice. The content changes each semester in response to contemporary topics. Graduate/Undergraduate Equivalency: STAT 540. Instructor permission required College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 453 - BIOSTATISTICS Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm An overview of statistical methodologies useful in the practice of Biostatistics. Topics include epidemiology, rates, and proportions, categorical data analysis, regression, and logistic regression, retrospective studies, case-control studies, survival analysis. Real biomedical applications serve as context for evaluating assumptions of statistical methods and models. S-Plus (R) serves as computing software. Graduate/Undergraduate Equivalency: STAT 553. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 470 - FROM SEQUENCE TO STRUCTURE: AN INTRODUCTION TO COMPUTATIONAL BIOLOGY Credits: 4 Course URL: http://statistics.rice.edu/courses.cfm Contemporary introduction to problems in computational biology spanning sequence to structure. The course has three modules: the first introduces students to the design and statistical analysis of gene expression studies; the second covers statistical machine learning techniques for understanding experimental data generated in computational biology; and the third introduces problems in the modeling of protein structure using computational methods from robotics. The course is project oriented with an emphasis on computation and problem-solving. Cross-list: BIOE 470, COMP 470. Recommended Prerequisites: COMP 280 and COMP 212 and (STAT 310 or STAT 331). College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 485 - QUANTITATIVE ENVIRONMENTAL DECISION MAKING Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm A project oriented computer intensive course focusing on statistical and mathematical solutions and investigations for the purpose of environmental decisions. This course is the undergraduate version of STAT 685 with reduced requirements. Graduate/Undergraduate Equivalency: STAT 685. Recommended Prerequisites: STAT 305 and STAT 385. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 486 - COMPUTATIONAL FINANCE I: MARKET MODELS Credits: 3 Course URL: http://statistics.rice.edu/courses.cfm This course takes the classical efficient market models and superimposes upon it models for other stochastic phenomena not generally accounted for in efficient market theory, showing how risk is lessened by portfolios and other mechanisms. The course uses computer simulations as an alternative to closed form solutions. UG/GR version: STAT 686. Graduate/Undergraduate Equivalency: STAT 686. College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page
STAT 490 - INDEPENDENT STUDY Credits: Hours Variable College: School of Engineering Department: Statistics
Score: 9.065848 Details | Listing | Web page