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Applied Statistics

Applied Statistics is offered as a Minor field of study only. However, as a Minor field, it plays an important role in the doctoral program as empirical research is central to Accounting, Finance, and Marketing areas. Many students majoring in these areas choose to combine the fairly comprehensive statistical training provided in the area of Applied Statistics with those in their major. Thus, the Applied Statistics minor is designed to complement the strong emphasis on emprirical research in many of the functional areas. Since many faculty who teach in Applied Statistics area also teach in other areas, the integration of the functional fields with Applied Statistics is reflected in many of the courses offered at the Simon School.

Program

Although the program is not structured to produce purely theoretical statisticians, there is considerable interaction with the University of Rochester’s Program in Statistics and the Department of Biostatistics in terms of courses and faculty research interests. Thus, students who wish to pursue more theoretical topics for their thesis research may do so, even though Applied Statistics is not officially a major field at the Simon School. The courses in econometrics (APS 514, 515, 523 and 524) are offered jointly with the Department of Economics on a semester basis.

The First Year: Foundation

Students Minoring in Applied Statistics take the first year of the Economics Core and must pass the Core Exam given in June. The course of study may vary, depending upon candidates academic objectives, previous background, and Major field of study. The plan must be approved by the Applied Statistics Committee, which consists of faculty working in the area.

The Second Year: Depth

Applied Statistics Minors must obtain a grade of B or better in three electives from the following list: Applied Time Series Analysis (APS 420), Sampling Techniques (APS 528), Multivariate Methods (APS 529), Theory of Probability and Stochastic Processes I (MSM 504), or other Ph.D.-level courses covering probability, stochastic processes, statistics or econometrics. In addition, a research project that makes a substantive contribution to the theory or application of one of the above fields must be signed off by an assigned advisor by November 15 of the third year. This may be a stand alone project or part of a paper required to satisfy the requirements for a course or the Second-Year Paper. If one paper is used to satisfy multiple requirements, the student must obtain prior approval from all instructors or committees evaluating the paper.

Faculty & Research Interests

Simon School faculty research and instruct in the area of Applied Statistics include: Harry Groenevelt and G. William Schwert.

Courses & Descriptions

Listed below are titles of M.B.A.-level courses (for descriptions the Simon Information Guide), and descriptions of Ph.D.-level courses in Applied Statistics.

  • APS 411  Applied Statistics and Data Analysis
  • APS 420  Applied Time Series Analysis
  • APS 511  Introduction to Mathematical Statistics. The course provides an overview of mathematical statistics. The topics covered are: fundamentals of probability theory, random variables, distribution functions and moments, important univariate distributions, joint distributions, distributions of functions of random variables, sampling distributions, parametric point estimation, and hypotheses testing.
  • APS 514  Introduction to Econometrics (same as ECO 484, 2 credit hours, pre-requisites: AEC 505 and APS 511 or equivalent). The course is for students intending to do research in quantitative areas. Topics include estimation and hypothesis testing in the standard linear model, weighted least squares, transformations, constraints, analysis of variance and covariance, and problems of model specification.
  • APS 515  Elements of Econometrics (same as ECO 485, 4 credit hours, pre-requisite: APS 514). The study of the specification of econometric models in which economic theory, stochastic disturbances, and the link between conceptual variables and observable economic data are combined. Topics include estimation of single-equation linear and non-linear econometric models by least squares and other methods, and estimation of time-series models and simultaneous-equation models. Particular attention is given to specification problems, such as heteroskedasticity, multicolinearity, qualitative dependent variables, and specification error.
  • APS 523  Advanced Econometrics (same as ECO 517, 5 credit hours, pre-requisite: APS 515). The course covers asymtotic theory for econometrics; maximum likelihood and related estimators; estimation under misspecification; nonparametric estimation; Monte Carlo methods; small sample approximations.
  • APS 524  Topics in Macroeconometrics (same as ECO 518, 5 credit hours, pre-requisite: APS 523 or permission of instructor). Course content varies from year to year. Stationary and nonstationary processes, expectations, unobserved component models, Kalman filtering and volatility are possible topics discussed.
  • APS 528  Sampling Theory (same as BST 421, 4 credit hours, prerequisite: APS 411 and differential calculus, offered in alternate years). For students with primary interest in applied statistics or research in quantitative areas. Topics include design and analysis of random, stratified, and systematic sampling; multistage and multiphase sampling; nonresponse and measurement errors.
  • APS 529  Applied Multivariate Analysis (same as BST 441, 2 credit hours, pre-requisite: APS 514). Methodology and applications of multivariate regression and analysis of variance; classification and discrimination; principal components, clustering, and multidimensional scaling; use of statistical software.