STOR 053 Networks: Degrees of Separation and Other Phenomena Relating to Connected Systems (3) -
Networks, mathematical structures that are composed of nodes and a set of lines joining the nodes, are used to model a wide variety of familiar systems: distribution networks such as electric power grids, anatomical networks such as neural systems, communication networks such as the world-wide web, and social networks representing relationships between cultural groups. These networks have distinct properties that help answer questions about the underlying system: how susceptible is a power grid to breakdown? how fast can a computer virus spread? how connected are the members of different corporate boards? Questions of this type, some suggested by class members, will be posed and modeled by networks.

STOR 056 Operations Research through War and Peace(3) -
First Year Seminar.Covers the origin and evolution of Operations Research from the WWII to its modern use in industry and government. Stidham

STOR 072 Using Computers to Unlock the Genetic Code(3) -
First Year Seminar.An introduction to DNA - its structure, function, and importance. Includes topics from computational, organizational and statistical tools for unlocking the secrets of life. Provan.

STOR 151 BASIC CONCEPTS OF STATISTICS AND DATA ANALYSIS (3)
Prerequisite: MATH 110 (or exemption). Elementary introduction to statistical reasoning, including sampling, elementary probability, statistical inference, and data analysis. Fall, Spring, Summer. Staff. STOR 151 may not be taken for credit by students who have credit for ECON 400 or PSYC 210.

STOR 155 INTRODUCTORY STATISTICS (3)
Data analysis: Visual measures, histogram, scatterplot, etc; Quantitative measures, central tendency and dispersion, correlation;Simple linear regression; Exploratory data analysis, outliers, leverage. Sampling, estimation of parameters; Probability: Basic rules; Conditional probability, independence; Random variables, distributions, expected values, variance; Binomial and normal distributions.  Sampling Distributions: Distribution of sample mean; Central limit theorem.  Inference: Hypothesis testing; Confidence intervals for population mean, binomial proportion; Regression parameters.

STOR 105 Models for Decision Making (3) -
Operations Research is the science of formulating and solving problems in decision making using mathematical models. Includes topical examples and introduction to concepts such as optimal allocation of a limited resource, decisions under uncertainty, risk, and expected return. Three lecture hours per week. Spring. Staff.

STOR 122 Decision Models for Business -
An Introduction to the basic quantitative models of business with linear and non-linear functions of single and multiple variables. Linear and non-linear optimization models and decision models under uncertainty will be covered.

STOR 113 Decision Models for Economics -
An Introduction to multi-variable quantitative models in economics. Mathematical techniques for formulating and solving optimization and equilibrium problems will be developed, including elementary models under uncertainty.

STOR 215 Introduction to the Decision Sciences (3) -
Prerequisite, Math 10 or exemption. Introduction to basic concepts and techniques of decision-making and information management in business, economics, social and physical science. Topics include discrete optimization, discrete probability, networks, decision trees, games, Markov chains. Fall. Staff. General College/B.A. -level Mathematical Science Perspective.

STOR 582 Neural Network Models for the Decision and Cognitive Science (3) -
Prerequisite, one of Phil 21, Math 31, Stat 23, Psyc 30, OR 14. The interactions between cognitive science and the decision sciences are explored via neural networks. The history of these networks in neuroscience is reviewed and their adaptation to other fields such as psychology, linguistics and operations research is presented. Spring. Tolle.

STOR 497 Undergraduate Reading and Research in Operations Research (3) -
Permission of director of undergraduate studies required. This course is intended mainly for students working on honors projects. No one may receive more than three semester hours credit for this course. Fall and Spring.

STOR 305 Mathematical Models for Decision Making (3) -
Prerequisite: MATH 81. The use of mathematics to describe and analyze large-scale decision problems. Situations involving the allocation of resources, making decisions in a competitive environment, and dealing with uncertainty are modeled and solved using suitable software packages. Fall. Wagner.

STOR 372 Long Term Actuarial Models (3) -
(Math 161, Stat106). Prerequisite, Math 32, OR 31 or Stat 31. Probability models for long-term insurance and pension systems that involve future contingent payments and failure-time random variables. Introduction to survival distributions and measures of interest and annuities-certain. Fall. Dunn.

STOR 472 Short Term Actuarial Models (3) -
(Math 162, Stat107). Prerequisite, Stat 126. Short term probability models for potential losses and their applications to both traditional insurance systems and conventional business decisions. Introduction to stochastic process models of solvency requirements. Spring. Dunn.

STOR 415 Deterministic Models in Operations Research -
(MATH 151, STAT 181) (3). Prerequisite: MATH 147. Linear, integer, nonlinear and dynamic programming, classical optimization problems, network theory. Fall. Pataki, Provan.

STOR 445 Stochastic Models in Operations Research (3) -
Prerequisite: BIOS 160 or STAT 126. Introduction to Markov chains, Poisson process, continuous-time Markov chains, renewal theory. Applications to queueing systems inventory, and reliability, with emphasis on systems modeling, design, and control. Spring. Kulkarni, Stidham.

STOR 515 Computational Mathematics for Decision Sciences (3) -
Prerequisite: permission of instructor. Reviews basic mathematical and computational theory required for analyzing models that arise in operations research, management science, and other policy sciences. Solution techniques that integrate existing software into student-written computer programs will be emphasized. Fall. Tolle.

STOR 355-STATISTICAL METHODS I (3)
Prerequisite: STOR 155 or equivalent. Some familiarity with matrix algebra recommended, but not required. This course presents regression analysis and related techniques, and is recommended for students throughout the natural and social sciences who are interested in applying regression analysis in their research and/or understanding the statistical concepts underlying the methodology. The topics include simple and multiple linear regression, matrix representation of the regression model, statistical inferences for regression model, diagnostics and remedies for multicollinearity, outlier and influential cases, polynomial regression and interaction regression models, model selection, weighted least square procedure for unequal error variances, and ANOVA model and test. Statistical software SAS will be used throughout the course to demonstrate how to apply the techniques on real data. The main purposes of this courses is to let students know how to use regression methods properly in data analysis and lay the foundation for more advanced studies in statistics. Fall. Zhu.

STOR 356- STATISTICAL METHODS II (3)
Prerequisite: STOR 355. Topics selected from: design of experiments; sample surveys; nonparametrics; time-series; multivariate analysis; contingency tables; logistic regression; simulation. Use of statistical software packages. Spring. Piparis, Smith.

STOR 358- SAMPLE SURVEY METHODOLOGY (BIOS 664) (3)
Prerequisite: STOR 356 or equivalent. Principles and methods associated with survey sampling, including simple random sampling, stratified sampling and cluster sampling. Questionnaire design, problems of nonresponse, sources of nonsampling errors.Design, execution, and analysis of an actual survey. Spring. Kalsbeek. (3)

STOR 435- INTRODUCTION TO PROBABILITY (MATH 535) (3)
Prerequisite: MATH 233. Introduction to mathematical theory of probability covering random variables, moments, binomial, Poisson, normal and related distributions, generating functions, sums and sequences of random variables, and statistical applications. Fall and Spring. Budhiraja, Nobel.

STOR 555- MATHEMATICAL STATISTICS (3)
Prerequisite, STOR 435 or equivalent. Functions of random samples and their probability distributions; introductory theory of point and interval estimation and of hypothesis testing; elementary decision theory. Fall and Spring. Carlstein, Kelly.