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100. (GQ) STATISTICAL CONCEPTS AND REASONING (3:3:0) Introduction to the art and science of decision making in the presence of uncertainty.
200. (GQ) ELEMENTARY STATISTICS (4:3:2) Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation. Prerequisite: 2 units in algebra.
240. INTRODUCTION TO BIOMETRY Statistical analysis, sampling, and experimentation in the agricultural sciences; data collection, descriptive statistics, statistical inference, regression, one factor AOV, probability. Students may take only one course from STAT 200, 220, 240, 250 for credit. Prerequisite: three credits in mathematics or calculus.
250. (GQ) INTRODUCTION TO BIOSTATISTICS (3:3:0) Statistical analysis and interpretation of data in the biological sciences; probability; distributions; statistical inference for one- and two-sample problems. Prerequisite: MATH 017 GQ or 3 credits of calculus.
301. (GQ) STATISTICAL ANALYSIS I (3:3:0) Probability concepts; nature of statistical methods; elementary distribution and sampling theory; fundamental ideas relative to estimation and testing hypotheses. Prerequisite: 3 credits of calculus.
318. (MATH 318) ELEMENTARY PROBABILITY (3:3:0) Combinatorial analysis, axioms of probability, conditional probability and independence, discrete and continuous random variables, expectation, limit theorems, additional topics. Students who have passed either STAT (MATH) 414 or 418 may not schedule this course for credit. Prerequisite: MATH 141 GQ.
319. (MATH 319) APPLIED STATISTICS IN SCIENCE (3:3:0) Statistical inference: principles and methods, estimation and testing hypotheses, regression and correlation analysis, analysis of variance, computer analysis. Students who have passed STAT (MATH) 415 may not schedule this course for credit.
401. EXPERIMENTAL METHODS (3:3:0) Random variables; probability density functions; estimation; statistical tests, t-tests; correlation; simple linear regression; one-way analysis of variance; randomized blocks. Prerequisite: MATH 111 GQ or 141 GQ.
414. INTRODUCTION TO PROBABILITY THEORY (3:3:0) Probability spaces, discrete and continuous random variables, transformations, expectations, generating functions, conditional distributions, law of large numbers, central limit theorems. Students may take only one course from STAT (MATH) 414 and 418 for credit. Prerequisite: MATH 231.
415. (MATH 415) INTRODUCTION TO MATHEMATICAL STATISTICS (3:3:0) A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests. Prerequisite: STAT (MATH) 414.
416. (MATH 416) STOCHASTIC MODELING (3:3:0) Review of distribution models, probability generating functions, transforms, convolutions, Markov chains, equilibrium distributions, Poisson spaces, birth and death processes, estimation. Prerequisites: STAT (MATH) 318 or 414; MATH 230.
418. (MATH 418) PROBABILITY (3:3:0) Fundamentals and axioms, combinatorial probability, conditional probability and independence, probability laws, random variables, expectation; Chebyshev's inequality. Students may take only one course from STAT (MATH) 414 and 418 for credit. Prerequisite: MATH 231.
451. (Discontinued in 1999). INTRODUCTION TO APPLIED STATISTICS. (3) Application of statistics to research; descriptive statistics, binomial and normal distributions, t-tests and intervals, linear regression and correlation. Students who have passed Stat 200 or Stat 319 may not schedule this course. Prerequisite: 2 units of algebra.
460. INTERMEDIATE APPLIED STATISTICS (3:3:0) Review of hypothesis testing, goodness-of-fit tests, regression, correlation analysis, completely randomized designs, randomized complete block designs, latin squares. Prerequisite: STAT 200 or 250 or 301 or 401 or 451 or 3 credits in statistics.
462. APPLIED REGRESSION ANALYSIS (3:3:0) Introduction to linear and multiple regression; correlation; choice of models, stepwise regression, nonlinear regression. Prerequisite: any statistics course.
464. APPLIED NONPARAMETRIC STATISTICS (3:3:0) Tests based on nominal and ordinal data for both related and independent samples. Chi-square tests, correlation. Prerequisite: STAT 200 GQ, 401, 451, or 3 credits in statistics.
480. INTRODUCTION TO STATISTICAL PROGRAM PACKAGES (1:0:2) Selection and evaluation of statistical computer packages. Prerequisite: 3 credits in statistics.
496. INDEPENDENT STUDIES (1-18)
497. SPECIAL TOPICS (1-9)
500. APPLIED STATISTICS (3) Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics. Prerequisite: one undergraduate course or equivalent.
501. REGRESSION METHODS (3) Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression. Prerequisite: 6 credits of statistics or STAT 451; matrix algebra.
502. ANALYSIS OF VARIANCE AND DESIGN OF EXPERIMENTS (3) Analysis of variance and design concepts; factorial, nested, and unbalanced data; ANCOVA; blocked, Latin square, split-plot, repeated measures designs. Prerequisite: STAT 462 or 501.
503. DESIGN OF EXPERIMENTS (3) Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs. Prerequisites: STAT 502; STAT 462 or 501.
504. ANALYSIS OF DISCRETE DATA (3) Models for frequency arrays; goodness-of-fit tests; two-, three-, and higher-way tables; latent and logistics models. Prerequisites: STAT 460, 502 or 512; matrix algebra.
505. APPLIED MULTIVARIATE STATISTICAL ANALYSIS (3) Analysis of multivariate data; T^2 tests; partial correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations. Prerequisites: 6 credits in statistics; matrix algebra.
506. SAMPLING THEORY AND METHODS (3) Theory and application of sampling from finite populations. Prerequisites: calculus; 3 credits in statistics.
508. APPLIED STATISTICAL DISTRIBUTION THEORY (3) Analysis of data involving nonnormal families of distributions; model building and selection, parameterizations, inferential algorithms, transformations, simulations, displays, interpretations. Prerequisites: STAT 401 or 409.
509. INTRODUCTION TO BIOSTATISTICAL METHODS (3)
510. APPLIED TIME SERIES ANALYSIS (3) Identification of models for empirical data collected time. Use of models in forecasting. Prerequisite: STAT 462, 501, or 511
511. REGRESSION ANALYSIS AND MODELING (3) Multiple regression methodology using matrix notation; linear, polynomial, and nonlinear models; indicator variable; AOV models; piece-wise regression, autocorrelation; residual analyses. Prerequisites: STAT 451 or 6 credits in statistics; matrix algebra, calculus.
512. DESIGN AND ANALYSIS OF EXPERIMENTS (3) AOV, unbalanced, nested factors; CRD, RCBD, Latin squares, split-plot, and repeated measures; incomplete block, fractional factorial, response surface designs; confounding. Prerequisite: STAT 511.
513. THEORY OF STATISTICS I (3) probability models, random variables, expectation, generating functions, distribution theory, limit theorems, parametric families, exponential families, sampling distributions. Prerequisite: MATH 230.
514. THEORY OF STATISTICS II (3) Sufficiency, completeness, likelihood, estimation, testing, decision thoery, Bayesian inference, sequential procedures, multivariate distributions and inference, nonparametric inference. Prerequisite: STAT 513.
515. STOCHASTIC PROCESSES I (3) Conditional probability and expectation, Markov chains, the exponential distribution and Poisson processes. Prerequisite: MATH (STAT) 414 or STAT 513.
516. (MATH 516) STOCHASTIC PROCESSES (3) Markov chains; generating functions; limit theorems; continuous time and renewal processes; martingales, submartingales, and supermartingales; diffuse processes; applications. Prerequisite: STAT (MATH) 416.
517. (MATH 517) PROBABILITY THEORY I (3) Measure theoretic foundation of probability, distribution functions and laws, types of convergence, central limit problem, conditional probability, special topics. Prerequisite: MATH 501.
518. (MATH 518) PROBABLITY THEORY II (3) Measure theoretic foundation of probability, distribution functions and laws, types of convergence, central limit problem, conditional probability, special topics. Prerequisite: MATH 517.
519. (MATH 519) TOPICS IN STOCHASTIC PROCESSES (3) Selected topics in stochastic processes, including Markov and Wiener processes; stochastic integrals, optimal filtering. Prerequisites: STAT (MATH) 516, 517.
524. ECOMETRICS (3) Stochastic models and statistical methods in ecological problems; population dynamics, spatial patterns in populations of one, two, or more species. Prerequisite: STAT (MATH) 414 or STAT 418.
525. SURVIVAL ANALYSIS I (3) Location estimation, 2- and k- sample problems, matched pairs, tests for association and covariance analysis when the data are censored. Prerequisites: STAT 512, 514
526. SURVIVAL ANALYSIS II (3) Asymptotic theory for Kaplan-Meier estimator, 2- and k- sample rank tests, rank regression, proportional hazards regression. Advanced special topics. Prerequisite: STAT 525
527. (BIOL 527) QUANTITATIVE ECOLOGY (3) Introduction to quantitative population and community ecology, with emphasis on problems, concepts, and methods using mathematical, statistical, and computational analysis. Prerequisites: STAT (MATH) 409, BIOL 210.
528. (BIOL 528) STATISTICAL ECOLOGY SPECTRUM (3) Overview of research and instruction of particular interest to quantitative ecology faculty in the Ecology program. Prerequisite: STAT (BIOL) 527.
534. (M E R 534) DYNAMIC PROGRAMMING (3) The study of the concepts underlying model building and optimization of dynamic systems; applications to engineering, economic, and environmental systems. Prerequisites: STAT (MATH) 414; I E 405, or Q B A 451.
540. STATISTICAL COMPUTING (3) Computational foundations of statistics; algorithms for linear and nonlinear models, discrete algorithms in statistics, graphics, missing data, Monte Carlo techniques. Prerequisites: STAT (MATH) 415; STAT 501 or 511; matrix algebra.
544. CATEGORICAL DATA ANALYSIS I (3) Two-way tables; generalized linear models; logistic and conditional logistic models; loglinear models; fitting strategies; model selection; residual analysis. Prerequisites: STAT 512, 514.
545. CATEGORICAL DATA ANALYSIS II (3) Generalized logit modes; symmetry and agreement models; repeated measures; longitudinal data; delta method; asymptotic distributions; ML & WLS; advanced special topics. Prerequisite: STAT 544.
548. STATISTICAL DISTRIBUTION THEORY (3) Analytical study of nonnormal models and methods in reliability theory, survival analysis, records evaluation, scale/scale-free analysis, and directional statistics. Prerequisites: STAT (MATH) 410, 414, or 416.
551. LINEAR MODELS I (3) A coordinate-free treatment of the theory of univariate linear models, including multiple regression and analysis of variance models. Prerequisites: MATH (STAT) 415 or STAT 514; STAT 512; MATH 436 or MATH 441.
552. LINEAR MODELS II (3) Treatment of other normal models, including geralized linear, repeated measures, random effects, mixed, correlation, and some multivariate models. Prerequisite: STAT 551.
561. STATISTICAL INFERENCE I (3) Multiparameter estimation; linear estimation; maximum likelihood estimation; Bayesian statistics; large sample properties and procedures. Prerequiste: STAT 514.
562. STATISTICAL INFERENCE II (3) Testing statistical composite hypotheses; invariance principles, Bayesian statistics; large sample properties and procedures. Prerequisite: STAT 561.
564. THEORY OF NONPARAMETRIC STATISTICS (3) Estimation and testing based on nonparametric procedures for location and regression models. Distribution theory and asymptotic efficiency.
565. MULTIVARIATE ANALYSIS (3) Theoretical treatment of methods for analyzing multivariate data, including Hotelling's T2, MANOVA, discrimination, principal components, and canonical analysis. Prerequisites: STAT 505, 551.
572. STATISTICAL DECISION THEORY I (3) Structure of statistical games, optimal strategies, fixed sample-size games. Prerequisite: MATH (STAT) 415 or STAT 514.
580. STATISTICAL CONSULTING PRACTICUM (1-2 per semester, maximum of 10) General principals of statistical consulting and statistical consulting experience. Preparation of reports and other aspects of consulting. Prerequisites: STAT 501; STAT 503, 504, or 505.
590. COLLOQUIUM (1-3)
596. INDIVIDUAL STUDIES (1-9)
597. SPECIAL TOPICS (1-9)
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