The purpose of this course is to give students a thorough introduction to applied probability. The focus is on teaching probability so that students will have the proper background and understanding to progress into statistical inference. Topics that will be covered include discrete and continuous random variables, distributions such as the binomial, the geometric, the negative binomial, Poisson, uniform, beta, normal, exponential, gamma, chi-square, t and F distributions. Topics such as transformations of variables, joint distributions, bivariate normal, expectations, conditional distributions and conditional expectations, moment generating functions, distribution of sum and ratios of random variables and the central limit theorem will also be developed.

This course provides a thorough understanding of linear and non-linear regression models. Some of the topics that will be covered are Analysis of Variance (Single Factor, Two Factors (balanced and unbalanced cases), Random Effects Models), Analysis of Covariance, Nonlinear Regression, Logistical Regression, and Simultaneous Equations. The course will be a mix of theory and applications.

This course provides a comprehensive survey of widely used multivariate statistical methods intended for the user of advanced statistical methodology. The multivariate normal distribution and related distributions, including Hotelling T2 and Wishart distribution, are introduced and their use illustrated in statistical estimation and hypothesis testing in multivariate normal models. Additional topics introduced and applied include multivariate analysis of variance and covariance, canonical correlation, principal component analysis, factor analysis, discriminant analysis, and cluster analysis.

This course is intended to develop the intuitive and formal mathematical structure of microeconomic theory. Topics covered include utility maximization, expected utility and risk aversion, the economics of information, game theory, production functions, perfect competition, monopoly, imperfect competition, factor markets and income distribution, externalities and public goods, and public choice theory.

This seminar reviews the main methodological issues in using research for studying individual behavior, particularly in marketing applications. It puts an emphasis on the experimental method for the collection of data, and the general linear model for data analysis. The seminar covers the following topics: relationship between theory and specification of empirical tests for a theory; translation of constructs into variables, including principles and strategies for manipulation and measurement, validity and reliability; degrees of control, including experimental, quasi-experimental and correlational research; specific experimental designs, including the analysis, representation, and interpretation of results.

The objective of this course is to introduce students to the academic research process, from inception to publication. This includes exposure to the relevant practices, processes, and intellectual and scholarly skills necessary for success in academia and in marketing. This course familiarizes students with different domains of marketing research, particularly those in which departmental faculty are involved and socializes students into the process of developing research ideas, undertaking original research, and publishing articles based on the research.

The objectives of this course are to (1) familiarize students with research in cognitive psychology, social psychology, behavioral decision theory and marketing that may help them to understand consumer behavior and (2) to give students a strong foundation for critical thinking in the area of consumer behavior. Therefore, the focus is on understanding current theoretical and methodological approaches to various aspects of consumer behavior, as well as advancing this knowledge by developing testable hypotheses and theoretical perspectives that build on the current knowledge base. The readings represent past and present work in consumer behavior and related disciplines.

This course prepares students to read, appreciate, and critique the major streams of research in quantitative marketing. We will learn the science and art of building "lean and testable" models that capture the essence of real marketing phenomena and that can be falsified using data. We will extensively analyze the model implications and examine their robustness to the underlying modeling assumptions.

This course combines a module focusing on the history of marketing thought and a module focusing on theory and theory development in marketing. The first module will provide students with an historical perspective on the field of marketing. It will trace the evolution of marketing thought beginning with scholars in the early twentieth century and continuing through the current managerial and consumer behavior schools. Particular emphasis will be placed on analyzing changes in the basic paradigms underlying our evolving definition(s) of marketing. The second module will concentrate on skill development with the specific objective of teaching students to analyze, evaluate, and develop theory. Students will read background material from marketing as well as other social sciences in order to gain an understanding of the formal elements of theory. They will then apply this foundation to analyze the underlying theoretical structure of current articles in the Journal of Marketing, the Journal of Marketing Research, and the Journal of Consumer Research. Finally, students will practice developing theories of their own in a variety of topical areas. Particular attention will be paid to the structural aspects of theory such that this module should serve to complement other courses that deal primarily with content.