Metadata
Title
Statistics and Data Science, Minor
Category
undergraduate
UUID
eaf0b74224214696b8ed3003e0e40862
Source URL
https://catalog.upenn.edu/undergraduate/programs/statistics-data-science-minor/
Parent URL
https://catalog.upenn.edu/undergraduate/programs/
Crawl Time
2026-03-09T07:23:05+00:00
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Statistics and Data Science, Minor

Source: https://catalog.upenn.edu/undergraduate/programs/statistics-data-science-minor/ Parent: https://catalog.upenn.edu/undergraduate/programs/

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Statistics and Data Science, Minor

The aim of statistical modeling is to empower effective decision making, and the field's unique contribution is its ability to incorporate multiple levels of uncertainty in the framing of wise decisions. Over the last few years, the development of new computational tools and the unprecedented evolution of “big data” have propelled statistical modeling to new levels. Today, statistical modeling and machine learning have reached a level of impact that no large organization can afford to ignore. The information landscape is changing as it has never changed before.

For more information: https://statistics.wharton.upenn.edu/programs/undergraduate/statistics-minor/

Statistics and Data Science, Minor

This minor is for students outside of Wharton. Single-degree and dual-degree students with Wharton may pursue a statistics concentration instead.

Course List

 | Code | Title | Course Units |

| --- | --- | --- | | Three Required Courses | | | | | Calculus, Part II | 1 | | or  | Mathematics of change, Part II | | | or  | Honors Calculus | | | | Introductory Business Statistics | 1 | | or  | Introductory Business Statistics | | | or  | Introductory Statistics | | | or  | Statistical Inference | | | or  | Statistics for Data Science | | | or  | Econometric Methods and Models | | | | Probability | 1 | | or  | Engineering Probability | | | Additionally select 4 CU's from the following electives: | | 4 | | | Statistical Computing with R | | | | Data Collection and Acquisition: Strategies and Platforms | | | | Predictive Analytics for Business | | | | Applied Machine Learning in Business | | | | Text Analytics | | | | Mathematical Statistics | | | | Stochastic Processes | | | | Forecasting Methods for Management | | | | Introduction to Bayesian Data Analysis | | | | Data Analytics and Statistical Computing | | | | Modern Data Mining | | | | Data Science Using ChatGPT | | | | Sample Survey Design | | | | Applied Probability Models in Marketing | | | | Introduction to Python for Data Science | | | | Advanced Statistical Computing | | | | Convex Optimization for Statistics and Data Science | | | | Numerical Optimization for Data Science and Machine Learning | | | | Applied Econometrics I | | | | Applied Econometrics II | | | Total Course Units | | 7 |


The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2025 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.