Emil Pitkin

Emil Pitkin
  • Lecturer and Research Scholar in Statistics

Contact Information

  • office Address:

    329 Academic Research Building
    265 South 37th Street
    Philadelphia, PA 19104

Research

Teaching

Past Courses

  • STAT111 - INTRODUCTORY STATISTICS

    Introduction to concepts in probability. Basic statistical inference procedures of estimation, confidence intervals and hypothesis testing directed towards applications in science and medicine. The use of the JMP statistical package. Knowledge of high school algebra is required for this course.

  • STAT430 - PROBABILITY

    Discrete and continuous sample spaces and probability; random variables, distributions, independence; expectation and generating functions; Markov chains and recurrence theory.

  • STAT613 - 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.

  • STAT621 - ACC REGRESSION ANALYSIS

    STAT 621 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 613, 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.

Awards and Honors

  • Wharton Teaching Excellence Award, 2020
  • Helen Kardon Moss Anvil Award, 2018
  • Wharton MBA Excellence in Teaching Award, 2017
  • Wharton MBA Excellence in Teaching Award, 2016

Activity

Wharton Stories

Orientation in IrvineThe Story Behind Wharton Convocation and 7 Pieces of Advice to Begin Your Academic Journey

Think of Convocation as a bookend to Commencement — you walk together as a class for the first time through the doors of Irvine Auditorium and in two years, you’ll process out of the Palestra as Wharton graduates….

Wharton Stories - 08/06/2018
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