# Kam Hamidieh

• Senior Lecturer in Statistics and Data Science

## Contact Information

265 South 37th Street

## Current Courses

• ### 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.

STAT613001 ( Syllabus )

STAT613002 ( Syllabus )

STAT613003 ( Syllabus )

## Past Courses

• ### STAT101 - 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.

• ### STAT102 - INTRO BUSINESS STAT

Continuation of STAT 101. A thorough treatment of multiple regression, model selection, analysis of variance, linear logistic regression; introduction to time series. Business applications. This course may be taken concurrently with the prerequisite with instructor permission.

• ### STAT422 - PREDICTIVE ANALYTICS

This course follows from the introductory regression classes, STAT 102, STAT 112, and STAT 431 for undergraduates and STAT 613 for MBAs. It extends the ideas from regression modeling, focusing on the core business task of predictive analytics as applied to realistic business related data sets. In particular it introduces automated model selection tools, such as stepwise regression and various current model selection criteria such as AIC and BIC. It delves into classification methodologies such as logistic regression. It also introduces classification and regression trees (CART) and the popular predictive methodology known as the random forest. By the end of the course the student will be familiar with and have applied all these tools and will be ready to use them in a work setting. The methodologies can all be implemented in either the JMP or R software packages. This course may be taken concurrently with the prerequisite with instructor permission.

• ### 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.

• ### STAT722 - PREDICTIVE ANALYTICS

This course follows from the introductory regression classes, STAT 102, STAT 112, and STAT 431 for undergraduates and STAT 613 for MBAs. It extends the ideas from regression modeling, focusing on the core business task of predictive analytics as applied to realistic business related data sets. In particular it introduces automated model selection tools, such as stepwise regression and various current model selection criteria such as AIC and BIC. It delves into classification methodologies such as logistic regression. It also introduces classification and regression trees (CART) and the popular predictive methodology known as the random forest. By the end of the course the student will be familiar with and have applied all these tools and will be ready to use them in a work setting. The methodologies can all be implemented in either the JMP or R software packages. This course is formerly STAT 622.

## Awards and Honors

• Wharton Teaching Excellence Award, 2020

## Knowledge@Wharton

How to Increase Interest in Government Benefits

Americans would be more likely to claim billions in untapped federal aid if they felt psychological ownership over those benefits, according to a new study from Wharton’s Wendy De La Rosa.

Knowledge @ Wharton - 9/14/2021
The Fed, Inflation and Interest Rates: What’s Ahead?

Federal Reserve Chairman Jerome Powell sent “three significant messages” on the U.S. economic outlook in his address last month in Jackson Hole, Wyoming, according to Wharton’s Christina Parajon Skinner.

Knowledge @ Wharton - 9/14/2021
Confronting Ethical and Moral Dilemmas: Don’t Go It Alone

In this Nano Tool for Leaders, Wharton’s G. Richard Shell explains how “the power of two” can help when you are faced with a moral or ethical dilemma at work.

Knowledge @ Wharton - 9/14/2021