Emil Pitkin

All Courses

• STAT6130 - Regr Analysis For Bus

  This course provides the fundamental methods of statistical analysis, the art and science if extracting information from data. The course will begin with a focus on the basic elements of exploratory data analysis, probability theory and statistical inference. With this as a foundation, it will proceed to explore the use of the key statistical methodology known as regression analysis for solving business problems, such as the prediction of future sales and the response of the market to price changes. The use of regression diagnostics and various graphical displays supplement the basic numerical summaries and provides insight into the validity of the models. Specific important topics covered include least squares estimation, residuals and outliers, tests and confidence intervals, correlation and autocorrelation, collinearity, and randomization. The presentation relies upon computer software for most of the needed calculations, and the resulting style focuses on construction of models, interpretation of results, and critical evaluation of assumptions.

• STAT6210 - Acc Regression Analysis

  STAT 6210 is intended for students with recent, practical knowledge of the use of regression analysis in the context of business applications. This course covers the material of STAT 6130, but omits the foundations to focus on regression modeling. The course reviews statistical hypothesis testing and confidence intervals for the sake of standardizing terminology and introducing software, and then moves into regression modeling. The pace presumes recent exposure to both the theory and practice of regression and will not be accommodating to students who have not seen or used these methods previously. The interpretation of regression models within the context of applications will be stressed, presuming knowledge of the underlying assumptions and derivations. The scope of regression modeling that is covered includes multiple regression analysis with categorical effects, regression diagnostic procedures, interactions, and time series structure. The presentation of the course relies on computer software that will be introduced in the initial lectures. Recent exposure to the theory and practice of regression modeling is recommended.

• Wharton MBA Excellence in Teaching Award, 2021-2022
• Class of 2021 “Most Engaging Lecturer” Award, 2020-2021
• Wharton Teaching Excellence Award, 2020
• Wharton MBA Excellence in Teaching Award, 2019
• Helen Kardon Moss Anvil Award, 2018
• Wharton MBA Excellence in Teaching Award, 2018
• Goes Above and Beyond the Call of Duty award, 2018
• Wharton MBA Excellence in Teaching Award, 2017
• Goes Above and Beyond the Call of Duty award, 2017
• Wharton MBA Excellence in Teaching Award, 2016
• Goes Above and Beyond the Call of Duty award, 2016