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Courses in Statistics

STAT 011 - Intro to Stats via Microcomp: Various study designs considered. Graphical and analytic techniques for presenting results. Wide variety of applications surveyed. PC-based software used. Experience gained in sample survey work. Prerequisite: High school algebra.; Credits: 3.
STAT 051 - Probability With Statistics: Introduction to probabilistic and statistical reasoning, including probability distribution models and applications to current scientific/social issues. Roles of probability, study design, and exploratory/confirmatory data analysis. Prerequisites: Two years H.S. algebra. No credit for sophomores, juniors, or seniors in the mathematical and engineering sciences.; Credits: 3.
STAT 095 - Special Topics: Lectures, reports, and directed readings at an introductory level. Prerequisite: As listed in course schedule.; Credits: 1-3.
STAT 111 - Elements of Statistics: Basic statistical concepts, methods, and applications, including correlation, regression, confidence intervals, and hypothesis tests. Prerequisites: Two years of high school algebra, sophomore standing.; Credits: 3.
STAT 140 - Natural Resource Biostatistics: (See Natural Resources 140.); Credits: 4.
STAT 141 - Basic Statistical Methods: Foundational course for students taking further quantitative courses. Exploratory data analysis, probability distributions, estimation, hypothesis testing. Introductory regression, experimentation, contingency tables, and nonparametrics. Computer software used. Prerequisites: Math. 11, 13, 19 or 21, sophomore standing.; Credits: 3.
STAT 143 - Statistics for Engineering: Data analysis, probability models, parameter estimation, hypothesis testing. Multi- factor experimental design and regression analysis. Quality control, SPC, reliability. Engineering cases and project. Statistical analysis software. Prerequisites: Math. 12, 14, 20 or 22, sophomore standing.; Credits: 3.
STAT 151 - Applied Probability: Foundations of probability, conditioning, and independence. Business, computing, biological, engineering reliability, and quality control applications. Classical discrete and continuous models. Pseudo-random number generation. Prerequisites: Math. 12, 14, 20 or 22.; Credits: 3.
STAT 153 - Prob & Stat for Cmptr Sci: Foundations of probability, conditioning, independence, expectation and variance. Discrete and continuous probability distributions. Computer simulation examples. Introductory descriptive and inferential statistics. Simple regression analysis. Pre/co-requisites: Math 20 or 22.; Credits: 3.
STAT 183 - Statistics for Business: Advanced quantitative methodologies for contemporary business scenarios. Analysis of variance, multiple regression, time series analysis, non-parametric methods, Bayesian statistics and decision analysis. Prerequisites: STAT 141 or EC 170; Credits: 3.
STAT 191 - Special Projects: Student-designed special project under supervision of a staff member culminating in a report. Prerequisites: Junior standing, permission of Program Director.; Credits: 1-4.
STAT 195 - Special Topics: Lectures, reports, and directed readings. Prerequisite: As listed in course schedule.; Credits: 1-3.
STAT 200 - Med Biostatistics&Epidemiology: (Cross listed with Biostatistics 200.) Introductory design and analysis of medical studies. Epidemiological concepts, case-control and cohort studies. Clinical trials. Students evaluate statistical aspects of published health science studies. Prerequisite: 141 or 143; or 211.; Credits: 3.
STAT 201 - Stat Analysis Via Computers: (Cross listed with Biostatistics 201.) Intensive coverage of computer-based data processing and analysis using statistical packages, subroutine libraries, and user-supplied programs. Students analyze real data and prepare a comprehensive report. Prerequisites: 111 with instructor's permission, or 141, or corequisite 211.; Credits: 3.
STAT 211 - Statistical Methods I: (Cross listed with Biostatistics 211.) Fundamental concepts for data analysis and experimental design. Descriptive and inferential statistics, including classical and nonparametric methods, regression, correlation, and analysis of variance. Statistical software. Prerequisite: Junior standing.; Credits: 3.
STAT 221 - Statistical Methods II: (Cross listed with Biostatistics 221.) Multiple regression and correlation. Basic experimental design. Analysis of variance (fixed, random, and mixed models). Analysis of covariance. Computer software usage. Prerequisites: 141 or 143; or 211.; Credits: 3.
STAT 223 - Applied Multivariate Analysis: Multivariate normal distribution. Inference for mean vectors and covariance matrices. Multivariate analysis of variance (MANOVA), discrimination and classification, principal components, factor analysis. Prerequisites: Any 200-level Statistics course, 221 or 225 recommended, matrix algebra recommended.; Credits: 3.
STAT 224 - Stats for Quality&Productivity: Statistical process control; Shewhart, cusum and other control charts; process capability studies. Total Quality Management. Acceptance, continuous, sequential sampling. Process design and improvement. Case studies. Prerequisites: 141 or 143; or 211.; Credits: 3.
STAT 225 - Applied Regression Analysis: Simple linear and multiple regression models; least squares estimates, correlation, prediction, forecasting. Problems of multicollinearity and influential data (outliers).; Credits: 3.
STAT 227 - Adv Statistical Methods II: (Cross listed with Psychology 341.) Continuation of 340. In-depth study of the analysis of variance and multiple regression. Further study of analysis and interpretation of data from the behavioral sciences. Prerequisite: 211 with computer experience or Psychology 340.; Credits: 3.
STAT 229 - Survival Analysis: Probabilistic models and inference for time-to-event data. Censored data, life tables, Kaplan-Meier estimation, logrank tests, proportional hazards regression. Specialized applications (e.g. clinical trials, reliability). Prerequisites: Any 200-level Statistics course, one year of calculus.; Credits: 3.
STAT 231 - Experimental Design: Randomization, complete and incomplete blocks, cross-overs, Latin squares, covariance analysis, factorial experiments, confounding, fractional factorials, nesting, split plots, repeated measures, mixed models, response surface optimization. Prerequisites: 211; 221 recommended.; Credits: 3.
STAT 233 - Survey Sampling: Design and data analysis for sample surveys. Simple random, stratified, systematic, cluster, multistage sampling. Practical issues in planning and conducting surveys. Prerequisites: 211; or 141 or 143 with instructor's permission.; Credits: 3.
STAT 235 - Categorical Data Analysis: (Cross listed with Biostatistics 235.) Measures of association and inference for categorical and ordinal data in multiway contingency tables. Log linear and logistic regression models. Prerequisite: 211.; Credits: 3.
STAT 237 - Nonparametric Statistical Mthd: Nonparametric and distribution free methods; categorical, ordinal, and quantitative data; confidence intervals; rank and chi-square hypothesis tests; computer-intensive procedures (bootstrap, exact tests). Prerequisites: 211; or 141 or 143 with instructor's permission.; Credits: 3.
STAT 241 - Statistical Inference: (Cross listed with Biostatistics 241.) Introduction to statistical theory: related probability fundamentals, derivation of statistical principles, and methodology for parameter estimation and hypothesis testing. Prerequisites: 151 or 153 or 251; 141 or equivalent; Math. 121.; Credits: 3.
STAT 251 - Probability Theory: (Cross listed with Math. 207.) Distributions of random variables and functions of random variables. Expectations, stochastic independence, sampling and limiting distributions (central limit theorems). Concepts of random number generation. Prerequisite: Math 121; Stat 151 or 153 recommended.; Credits: 3.
STAT 252 - Appl Discr Stochas Proc Models: Markov chain models for biological, social, and behavioral systems models. Random walks, transition and steady-state probabilities, passage and recurrence times. Prerequisite: STAT 151 or STAT 153 or STAT 251; Credits: 1.
STAT 253 - Appl Time Series & Forecasting: Autoregressive moving average (Box-Jenkins) models, autocorrelation, partial correlation, differencing for nonstationarity, computer modeling. Forecasting, seasonal or cyclic variation, transfer function and intervention analysis, spectral analysis. Prerequisite: 211 or 225; or 141 or 143 with instructor's permission. Cross-listing: CSYS 253.; Credits: 3.
STAT 254 - Appl Cont Stoch Process Models: Queueing models for operations research and computer science systems analysis. Birth-and-death processes with applications. Exponential, Erlang and Poisson distributions. Monte Carlo simulation. Pre/co-requisites: STAT 151 or STAT 153 or STAT 251; Credits: 1.
STAT 256 - Neural Computation: Introduction to artificial neural networks, their computational capabilities and limitations, and the algorithms used to train them. Statistical capacity, convergence theorems, backpropagation, reinforcement learning, generalization. Prerequisites: Math 124 (or 271), Stat 153 or equivalent, computer programming. Cross-listing: CS 256/CSYS 256.; Credits: 3.
STAT 261 - Statistical Theory I: (Cross listed with Biostatistics 261.) Point and interval estimation, hypothesis testing, and decision theory. Application of general statistical principles to areas such as nonparametric tests, sequential analysis, and linear models. Prerequisites: STAT 251 or either STAT 151 or STAT 153 with instructor permission.; Credits: 3.
STAT 262 - Statistical Theory II: (Cross listed with BIOS 262.) Point and interval estimation, hypothesis testing, and decision theory. Application of general statistical principles to areas such as nonparametric tests, sequential analysis, and linear models. Prerequisites: 241 with instructor permission or 261.; Credits: 3.
STAT 265 - Integrated Product Development: (Cross listed with Business Administration 293.) Project-based course focusing on the entire product life cycle. Team dynamics, process and product design, quality, materials, management, and environmentally-conscious manufacturing. Prerequisite: Senior standing.; Credits: 3.
STAT 270 - Stochastic Processes in EE: Probability theory, random variables, and stochastic processes. Response of linear systems to random inputs. Applications in electrical engineering. Cross-listed with EE 270. Prerequisites: EE 171 and STAT 151.; Credits: 3.
STAT 271 - Filtering of Time Series: Foundations of linear and nonlinear least squares estimation, smoothing and prediction, computational aspects, Kalman filtering, nonlinear filtering, parameter identification, and adaptive filtering. Cross-listed with EE 271. Prerequisite: EE 270.; Credits: 3.
STAT 281 - Statistics Practicum: Intensive experience in carrying out a complete statistical analysis for a research project in substantive area with close consultation with a project investigator. Prerequisites: Any one of 200, 201, 221 through 237; or 253; some statistical software experience. No credit for graduate students in Statistics or Biostatistics.; Credits: 1-4.
STAT 293 - Undergrad Honors Thesis: A program of reading, research, design, and analysis culminating in a written thesis and oral defense. Honors notation appears on transcript and Commencement Program. Contact Statistics Program Director for procedures.; Credits: 1-8.
STAT 294 - Undergrad Honors Thesis: A program of reading, research, design, and analysis culminating in a written thesis and oral defense. Honors notation appears on transcript and Commencement Program. Contact Statistics Program Director for procedures.; Credits: 1-8.
STAT 295 - Special Topics: For advanced students. Lectures, reports, and directed readings on advanced topics. Prerequisite: As listed in course schedule.; Credits: 1-4.
STAT 308 - Applied Biostatistics: The rationale and application of biostatistical methods in the biological, health and life sciences with emphasis on interpreting and reporting results. sciences. Cross-listings: MPBP 308, BIOS 308; Prerequisites: STAT 141 or equivalent.; Credits: 3.
STAT 313 - Stat Analysis for Management: See Business Administration 313.; Credits: 3.
STAT 321 - Seminar in Advanced Statistics: Seminar presentations and discussions of statistical literature pertaining to the theoretical aspects of methods studied in 221, 223, 224, 225, and 229, respectively. Corequisites: 221 for 321; 223 for 323; 224 for 324; 225 or 221 for 325, 229 for 329. 241 or 261 recommended. Cross-listings: Biostatistics 321, 323, 324, 325, 329.; Credits: 1.
STAT 323 - Seminar in Advanced Statistics: Seminar presentations and discussions of statistical literature pertaining to the theoretical aspects of methods studied in 221, 223, 224, 225, and 229, respectively. Corequisites: 221 for 321; 223 for 323; 224 for 324; 225 or 221 for 325, 229 for 329. 241 or 261 recommended. Cross-listings: Biostatistics 321, 323, 324, 325, 329.; Credits: 1.
STAT 324 - Seminar in Advanced Statistics: Seminar presentations and discussions of statistical literature pertaining to the theoretical aspects of methods studied in 221, 223, 224, 225, and 229, respectively. Corequisites: 221 for 321; 223 for 323; 224 for 324; 225 or 221 for 325, 229 for 329. 241 or 261 recommended. Cross-listings: Biostatistics 321, 323, 324, 325, 329.; Credits: 1.
STAT 325 - Seminar in Advanced Statistics: Seminar presentations and discussions of statistical literature pertaining to the theoretical aspects of methods studied in 221, 223, 224, 225, and 229, respectively. Corequisites: 221 for 321; 223 for 323; 224 for 324; 225 or 221 for 325, 229 for 329. 241 or 261 recommended. Cross-listings: Biostatistics 321, 323, 324, 325, 329.; Credits: 1.
STAT 329 - Seminar in Advanced Statistics: Seminar presentations and discussions of statistical literature pertaining to the theoretical aspects of methods studied in 221, 223, 224, 225, and 229, respectively. Corequisites: 221 for 321; 223 for 323; 224 for 324; 225 or 221 for 325, 229 for 329. 241 or 261 recommended. Cross-listings: Biostatistics 321, 323, 324, 325, 329.; Credits: 1.
STAT 350 - Advanced Methods in Biostat: Essential topics in modern biostatistics including epidemiology studies, clinical trials, statsitical genetics, issues involved in secondary data analysis of complex surveys. Prerequisites: STAT 261 & STAT 200 or instructor permission. Cross-listed with BIOS 350.; Credits: 3.
STAT 355 - Statisticl Pattern Recognition: Analysis of algorithms used for feature selection, density estimation, and pattern classification, including Bayes classifiers, maximum likelihood, nearest neighbors, kernels, discriminants, neural networks and clustering. Prerequsite: STAT 241 or 251 or instructor permission. Cross-listing: CS 355/CSYS 355.; Credits: 3.
STAT 360 - Linear Models: Theory of linear models, least squares and maximum likelihood estimation, fixed, random and mixed models, variance component estimation, introduction to generalized linear models, bootstrapping. Prerequisite: STAT 261 and knowledge of matrix algebra or instructor permission.; Credits: 3.
STAT 369 - Applied Geostatistics: Introduction to the theory of regionalized variables, geostatistics (kriging techniques): special topics in multivariate analysis; Applications to real data subject to spatial variation are emphasized. Pre/co-requisites: STAT 223 or 225; CS 16/CE 11 or permission. Cross-listings: STAT 369/CSYS 369.; Credits: 3.
STAT 380 - Sem:Statistics & Biostatistics: Presentation and discussion of current topics, methodological research and applications in Statistics and Biostatistics by graduate students, faculty and guest speakers. Prerequisite: Permission.; Credits: .5-1.
STAT 381 - Statistical Research: Methodologic or data analytic research culminating in oral and written reports to the faculty. Prerequisite: Permission. Cross-listing: Biostatistics 381.; Credits: 1-3.
STAT 385 - Consulting Practicum: Supervised field work in statistical consulting. Experiences may include advising UVM faculty and students or clients in applied settings such as industry and government agencies. Prerequisites: Second year graduate standing in Statistics or Biostatistics and permission of Statistics Program Director. Cross-listing: Biostatistics 385.; Credits: 1-3.
STAT 391 - Master's Thesis Research: Credits: 1-6.
STAT 395 - Advanced Special Topics: Lectures or directed readings on advanced and contemporary topics not presently included in other statistics courses. Prerequisites: As listed in course schedule. Cross-listing: Biostatistics 395.; Credits: 1-3.