Darin Kapanjie

Darin Kapanjie
  • Lecturer in Statistics and Data Science

Contact Information

  • office Address:

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

Teaching

Past Courses

  • STAT1010 - Intro Business Stat

    Data summaries and descriptive statistics; introduction to a statistical computer package; Probability: distributions, expectation, variance, covariance, portfolios, central limit theorem; statistical inference of univariate data; Statistical inference for bivariate data: inference for intrinsically linear simple regression models. This course will have a business focus, but is not inappropriate for students in the college. This course may be taken concurrently with the prerequisite with instructor permission.

  • 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.

In the News

Knowledge @ Wharton

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In the News

How AI Can Unlock Hybrid Creativity in the Workplace

Hybrid creativity combines the unique strengths of humans and AI to achieve more than they can alone, writes Wharton’s Cornelia Walther.…Read More

Knowledge @ Wharton - 2025/05/6
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