Note: P-prerequisite; C - corequisite; R - recommended; Fall - offered fall semester; Spring - offered spring semester; Summer - offered in the summer session. For courses with no designated semester, consult the Master Schedule. Equiv. - course is equivalent to the indicated course taught at Indiana University Bloomington, or the indicated course taught at Purdue University, West Lafayette.

Undergraduate Level

Lower-Division Courses

STAT 113 Statistics and Society (3 cr.) P: none. Fall, Spring, Summer. Intended to familiarize the student with basic statistical concepts and some of their applications in public and health policies as well as in social and behavioral sciences. No mathematics beyond simple algebra is needed, but quantitative skills are strengthened by constant use. Involves much reading, writing and critical thinking through discussions on such topics as data ethics, public opinion polls and the political process, the question of causation, the role of government statistics, and dealing with chance in everyday life. Applications include public opinion polls, medical experiments, smoking and health, the consumer price index, state lotteries, etc. Can be used for general education or as preparation for later methodology courses.

Upper-Division Courses

STAT 301 Elementary Statistical Methods I (3 cr.) P: MATH 111 or 110 (minimum grade of C-) or equivalent. Not open to students in the Department of Mathematical Sciences. Fall, spring, summer. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout.

STAT 302 Elementary Statistical Methods II (3 cr.) P: 301 or equivalent. Continuation of 301. Multiple regression and analysis of variance, with emphasis on statistical inference and applications to various fields.

STAT 311 Introductory Probability (3 cr.) P: MATH 261 or equivalent. Fundamental axioms and laws of probability; finite sample spaces and combinatorial probability; conditional probability; Bayes theorem; independence; discrete and continuous random variables; univariate and bivariate distributions; binomial, negative binomial, Poisson, normal, and gamma probability models; mathematical expectation; moments and moment generating functions.

STAT 350 Introduction to Statistics (3 cr.) P: MATH 163 or 165 or equivalent. Fall, Spring. A data-oriented introduction to the fundamental concepts and methods of applied statistics. STAT 350 is intended primarily for majors in the mathematical sciences (Mathematics, Actuarial Sciences, Mathematics Education). The objective is to acquaint the students with the essential ideas and methods of statistical analysis for data in simple settings. It covers material similar to that of STAT 511 but with emphasis on more data-analytic material. Includes a weekly computing laboratory using Minitab.

STAT 371 Seminar: Preparation for Actuarial Exam I (2 cr.) This course is intended to help actuarial students prepare for the first Actuarial Exam (Exam P).

STAT 416 Probability (3 cr.) P: MATH 261 or equivalent. Not open to students with credit in 311. Fall. An introduction to mathematical probability suitable as preparation for actuarial science, statistical theory, and mathematical modeling. General probability rules, conditional probability, and Bayes theorem, discrete and continuous random variables, moments and moment generating functions continuous distributions and their properties, law of large numbers and central limit theorem.

STAT 417 Statistical Theory (3 cr.) P: STAT 416 R: 350 or equivalent. Spring. An introduction to the mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Bayes and maximum likelihood estimation. Sufficient statistics. Properties of test of hypotheses. Most powerful and likelihood-ratio tests. Distribution theory for common statistics based on normal distributions.

STAT 472 Actuarial Models I (3 cr.) P: STAT 416 or equivalent. Mathematical foundations of actuarial science emphasizing probability models for life contingencies as the basis for analyzing life insurance and life annuities, determining premiums and net premium reserves, and building up multiple life models and multiple decrement models. This course, together with its sequel, STAT 473, provides most of the background for Course 3 exam (Exam M) of the Society of Actuaries and the Casualty Actuarial Society.

STAT 473 Actuarial Models II (3 cr.) P: STAT 472. Continuation of STAT 472. Together, these courses cover contingent payment models, survival models, frequency and severity models, compound distribution models, simulation models, stochastic process models and ruin models.

STAT 490 Topics in Statistics for Undergraduates (1-5 cr.) Supervised reading and reports in various fields.

Undergraduate and Graduate Level

STAT 511 Statistical Methods I (3 cr.) P: MATH 164. Spring. Descriptive statistics; elementary probability; random variables and their distributions; expectation; normal, binomial, Poisson, and hypergeometric distributions; sampling distributions; estimation and testing of hypotheses; one-way analysis of variance; correlation and regression.

STAT 512 Applied Regression Analysis (3 cr.) P: 511. Fall. Inference in simple and multiple linear regression, estimation of model parameters, testing and prediction. Residual analysis, diagnostics and remedial measures. Multicollinearity. Model building, stepwise and other model selection methods. Weighted least squares. Nonlinear regression. Models with qualitative independent variables. One-way analysis of variance. Orthogonal contrasts and multiple comparison tests. Use of existing statistical computing package.

STAT 513 Statistical Quality Control (3 cr.) P: 511. Control charts and acceptance sampling, standard acceptance plans, continuous sampling plans, sequential analysis, statistics of combinations, and some nonparametric methods. Use of existing statistical computing packages.

STAT 514 Designs of Experiments (3 cr.) P: 512. Spring. Fundamentals, completely randomized design, randomized complete blocks. Latin squares, multiclassification, factorial, nested factorial, incomplete blocks, fractional replications, confounding, general mixed factorial, split-plot and optimum design. Use of existing statistical computing packages.

STAT 515 Statistical Consulting Problems (1-3 cr.) P: Consent of advisor. Consultation on real-world problems involving statistical analysis under the guidance of a faculty member. A detailed written report and an oral presentation are required.

STAT 516 Basic Probability and Applications (3 cr.) P: MATH 261 or equivalent. Fall. A first course in probability intended to serve as a foundation for statistics and other applications. Intuitive background; sample spaces and random variables; joint, conditional, and marginal distributions; special distributions of statistical importance; moments and moment generating functions; statement and application of limit theorems; introduction to Markov chains.

STAT 517 Statistical Inference (3 cr.) P: 511 or 516. Spring. A basic course in statistical theory covering standard statistical methods and their applications. Includes unbiased, maximum likelihood, and moment estimation; confidence intervals and regions; testing hypotheses for standard distributions and contingency tables; introduction to nonparametric tests and linear regression.

STAT 519 Introduction to Probability (MATH 519) (3 cr.) P: MATH 261. Fall. Sample spaces and axioms of probability, conditional probability, independence, random variables, distribution functions, moment generating and characteristics functions, special discrete and continuous distributions - univariate and multivariate cases, normal multivariate distributions, distribution of functions of random variables, modes of convergence and limit theorems, including laws of large numbers and central limit theorem.

STAT 520 Time Series and Applications (3 cr.) P: 519. A first course in stationary time series with applications in engineering, economics, and physical sciences. Stationarity, autocovariance function and spectrum; integral representation of a stationary time series and interpretation; linear filtering; transfer function models; estimation of spectrum; multivariate time series. Use of existing statistical computing packages.

STAT 521 Statistical Computing (3 cr.) C: STAT 512 or equivalent. A broad range of topics involving the use of computers in statistical methods. Collection and organization of data for statistical analysis; transferring data between statistical applications and computing platforms; techniques in exploratory data analysis; comparison of statistical packages.

STAT 522 Sampling and Survey Techniques (3 cr.) P: 512 or equivalent. Survey designs; simple random, stratified, and systematic samples; systems of sampling; methods of estimation; ratio and regression estimates; costs.

STAT 523 Categorical Data Analysis (3 cr.) P: 528 or equivalent, or consent of instructor. Models generating binary and categorical response data, two-way classification tables, measures of association and agreement, goodness-of-fit tests, testing independence, large sample properties. General linear models, logistic regression, probit and extreme value models. Loglinear models in two and higher dimensions; maximum likelihood estimation, testing goodness-of-fit, partitioning chi-square, models for ordinal data. Model building, selection, and diagnostics. Other related topics as time permits. Computer applications using existing statistical software.

STAT 524 Applied Multivariate Analysis (3 cr.) P: 528 or equivalent, or consent of instructor. Fall. Extension of univariate tests in normal populations to the multivariate case, equality of covariance matrices, multivariate analysis of variance, discriminant analysis and misclassification errors, canonical correlation, principal components, factor analysis. Strong emphasis on the use of existing computer programs.

STAT 525 Intermediate Statistical Methodology (3 cr.) C: 528 or equivalent, or consent of instructor. Generalized linear models, likelihood methods for data analysis, diagnostic methods for assessing model assumptions. Methods covered include multiple regression, analysis of variance for completely randomized designs, binary and categorical response models, and hierarchical loglinear models for contingency tables.

STAT 528 Mathematical Statistics I (3 cr.) P: 519 or equivalent. Spring. Sufficiency and completeness, the exponential family of distributions, theory of point estimation, Cramer-Rao inequality, Rao-Blackwell Theorem with applications, maximum likelihood estimation, asymptotic distributions of ML estimators, hypothesis testing, Neyman-Pearson Lemma, UMP tests, generalized likelihood ratio test, asymptotic distribution of the GLR test, sequential probability ratio test.

STAT 529 Bayesian Statistics and Applied Decision Theory (3 cr.) C: 528 or equivalent. Foundation of statistical analysis, Bayesian and decision theoretic formulation of problems; construction of utility functions and quantifications of prior information; methods of Bayesian decision and inference, with applications; empirical Bayes; combination of evidence; game theory and minimax rules, Bayesian design and sequential analysis. Comparison of statistical paradigms.

STAT 532 Elements of Stochastic Processes (MATH 532) (3 cr.) P: 519 or equivalent. A basic course in stochastic models including discrete and continuous time processes, Markov chains, and Brownian motion. Introduction to topics such as Gaussian processes, queues and renewal processes, and Poisson processes. Application to economic models, epidemic models, and reliability problems.

STAT 533 Nonparametric Statistics (3 cr.) P: 519 or equivalent. Binomial test for dichotomous data, confidence intervals for proportions, order statistics, one-sample signed Wilcoxon rank test, two-sample Wilcoxon test, two-sample rank tests for dispersion, Kruskal-Wallis test for one-way layout. Runs test and Kendall test for independence, one- and two-sample Kolmogorov-Smirnov tests, nonparametric regression.

STAT 536 Introduction to Survival Analysis (3 cr.) P: STAT 517 or equivalent. Deals with the modern statistical methods for analyzing time-to-event data. Background theory is provided, but the emphasis is on the applications and the interpretations of results. Provides coverage of survivorship functions and censoring patterns; parametric models and likelihood methods, special life-time distributions; nonparametric inference, life-tables, estimation of cumulative hazard functions, the Kaplan-Meier estimator; one and two-sample nonparametric tests for censored data; semiparametric proportional hazards regression (Cox Regression), parameters' estimation, stratification, model fitting strategies and model interpretations. Heavy use of statistical software such as Splus and SAS.

STAT 598 Topics in Statistical Methods (1-3 cr.) P: Consent of instructor. Directed study and reports for students who wish to undertake individual reading and study on approved topics.