Business Analytics, BS
The Business Analytics joint concentration between the OID and STAT departments is designed to build deep competency in the skills needed to implement and oversee data-driven business decisions, including (i) collecting, managing, and describing datasets, (ii) forming inferences and predictions from data, and (iii) making optimal and robust decisions. Business analytics makes extensive use of statistical analysis, and the applications of business analytics span all functional areas.
Students choosing the Business Analytics concentration are ideally suited for the growing set of careers broadly defined under the header of “data science” with responsibilities for managing and analyzing data. In addition, the concentration provides an excellent complement to students who choose to focus on one of the functional areas of business (e.g., accounting, finance, marketing, operations).
For more information: https://oid.wharton.upenn.edu/programs/undergraduate/business-analytics-joint-concentration/
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.
Other Wharton Requirements
| Code | Title | Course Units |
|---|---|---|
| First-Year Foundations | ||
| BEPP 1000 | Introductory Economics for Business Students 1 | 1 |
| MATH 1400 | Calculus, Part I | 1 |
| or MATH 1070 | Mathematics of change, Part I | |
| Critical Writing Seminar | 1 | |
WRIT 0020, 0110, or 0120-0990 | ||
| Business Fundamentals | ||
| Leadership Journey | ||
| WH 1010 | Business and You | 0.5 |
| WH 2010 | Business Communication for Impact | 0.5 |
| or WH 2011 | Global Business Communication for Impact | |
| MGMT 3010 | Teamwork and Interpersonal Influence | 0.5 |
| Senior Capstone | One course with attribute WUCP required 2 | 0.5 |
Please visit https://undergrad-inside.wharton.upenn.edu/senior-capstone for more information. | ||
| Fundamentals 3 | ||
| ACCT 1010 | Accounting and Financial Reporting | 1 |
| ACCT 1020 | Strategic Cost Analysis | 1 |
| BEPP 2500 | Managerial Economics (or Honors) | 1 |
| FNCE 1000 | Corporate Finance (or Honors) | 1 |
| FNCE 1010 | Monetary Economics and the Global Economy (or Honors) | 1 |
| LGST 1000 | Ethics and Social Responsibility (or Honors) | 1 |
| or LGST 1010 | Law and Social Values | |
| MGMT 1010 | Introduction To Management | 1 |
| MKTG 1010 | Introduction to Marketing (or Honors) | 1 |
| OIDD 1010 | An Introduction to Operations, Information and Decisions | 1 |
| STAT 1010 | Introductory Business Statistics (or Honors) 4 | 1 |
| or STAT 4300 | Probability | |
| or ESE 3010 | Engineering Probability | |
| STAT 1020 | Introductory Business Statistics (or Honors) | 1 |
| or STAT 4310 | Statistical Inference | |
| or ESE 4020 | Statistics for Data Science | |
| Flex Fundamentals | ||
Global Economy, Business & Society | ||
| One course unit with attribute WUGE required | 1 | |
Technology, Innovation & Analytics | ||
| One course unit with attribute WUTI required | 1 | |
| Liberal Arts & Sciences | 7 | |
Foreign Language Requirement | ||
Two semesters at the beginner level of a language other than English or demonstration of equivalent proficiency required 5 | ||
Humanities | ||
Natural Science, Math & Engineering | ||
Social Science | ||
Flexible Gen Ed | ||
Three course units of approved undergraduate coursework taken outside of Wharton required | ||
Cross-Cultural Perspectives | ||
Three course units with substantial cross-cultural content required 6 | ||
| Business Breadth | ||
| Three upper-level course units from three different Wharton departments outside of the student's concentration required. Please visit https://undergrad-inside.wharton.upenn.edu/business-breadth/ for details. | 3 | |
| Unrestricted Electives | ||
| Five course units required 7 | 5 | |
| Total Course Units | 33 | |
- 1
For students who take ECON 0100 Introduction to Micro Economics and ECON 0200 Introductory Economics: Macro in place of BEPP 1000 Introductory Economics for Business Students: one of these courses can be used to satisfy BEPP 1000 on the degree audit. The second course may be used to fulfill a Liberal Arts & Sciences or Unrestricted Elective requirement.
- 2
Beginning with capstones offered in Fall 2027, all students must complete all business fundamentals as a prerequisite for the senior capstone, in addition to the Leadership Journey courses and any other required prerequisite course(s).
- 3
Course numbers for honors business fundamentals are: BEPP 2508 Managerial Economics, FNCE 1008 Corporate Finance (Honors), FNCE 1018 Monetary Economics and the Global Economy (Honors), LGST 1008 Ethics and Social Responsibility, LGST 1018 Law and Social Values, MKTG 1018 Introduction to Marketing, STAT 1018 Introductory Business Statistics, and STAT 1028 Introductory Business Statistics.
- 4
Dual-degree students majoring in SSE (Systems Science Engineering) and EE (Electrical Engineering) must take ESE 3010 Engineering Probability and ESE 4020 Statistics for Data Science.
- 5
Courses taken at Penn that satisfy the Foreign Language requirement may double-count as Humanities or Flexible Gen Ed.
- 6
Up to one course may be on U.S. cultural diversity. Please see course attribute WUCN for a list of non-U.S. courses and WUCU for a list of U.S. courses. Two CCP course units may double-count as Humanities; Natural Science, Math & Engineering; Social Science; or Flexible Gen Ed.
- 7
Students pursuing a second concentration may apply three course units of concentration courses to Unrestricted Electives.
| Code | Title | Course Units |
|---|---|---|
| Complete one course unit of Advanced Data Analysis competency 1 | 1 | |
| Forensic Analytics | ||
| Applied Data Analysis | ||
| Applied Machine Learning 2 | ||
| Machine Learning 2 | ||
| Big Data Analytics | ||
or CIS 5450 | Big Data Analytics | |
| Computational Text Analysis for Communication Research | ||
| Foundations of Data Science | ||
| Deep Learning: A Hands-on Introduction | ||
| Financial Derivatives | ||
| Data Science for Finance | ||
| FinTech | ||
| Healthcare Data and Analytics | ||
| People Analytics | ||
| Data and Analysis for Marketing Decisions | ||
| Analytics and AI in Digital Marketing and Social Media | ||
| Models for Marketing Strategy | ||
| Experiments for Business Decision Making (Center Special Topic) | ||
| Applied Probability Models in Marketing | ||
| Operations Management Analytics | ||
| Analytics and the Digital Economy | ||
| Artificial Intelligence, Business, and Society | ||
| Enabling Technologies | ||
| Databases for Analytics | ||
| Advanced Decision Systems: Evolutionary Computation | ||
OIDD 3250 | ||
| Information Strategy and Economics | ||
| Introduction to Python for Data Science | ||
| Thinking with Models: Business Analytics for Energy and Sustainability | ||
| Real Estate Data Analytics | ||
| Statistical Computing with R | ||
| Predictive Analytics for Business | ||
| Applied Machine Learning in Business | ||
| Statistical Inference | ||
| Forecasting Methods for Management | ||
| Introduction to Bayesian Data Analysis | ||
| Data Analytics and Statistical Computing | ||
| Modern Data Mining | ||
| Sample Survey Design | ||
| Introduction to Python for Data Science | ||
| Applied Econometrics I | ||
| Complete one course unit of Data Collection competency | 1 | |
| Forensic Analytics | ||
| Database and Information Systems | ||
| Big Data Analytics | ||
| Computational Text Analysis for Communication Research | ||
| Data Science for Finance | ||
| Healthcare Data and Analytics | ||
| People Analytics | ||
| Experiments for Business Decision Making (Center Special Topic) | ||
| Analytics in Excel VBA | ||
| Analytics and the Digital Economy | ||
| Artificial Intelligence, Business, and Society | ||
| Enabling Technologies | ||
| Databases for Analytics | ||
| Advanced Decision Systems: Evolutionary Computation | ||
OIDD 3250 | ||
| Information Strategy and Economics | ||
| Introduction to Python for Data Science | ||
| Thinking with Models: Business Analytics for Energy and Sustainability | ||
| Real Estate Data Analytics | ||
| Statistical Computing with R | ||
| Data Collection and Acquisition: Strategies and Platforms | ||
| Predictive Analytics for Business | ||
| Forecasting Methods for Management | ||
| Data Analytics and Statistical Computing | ||
| Modern Data Mining | ||
| Sample Survey Design | ||
| Introduction to Python for Data Science | ||
| Complete one course unit of Optimization competency | 1 | |
| Deep Learning: A Hands-on Introduction | ||
| Introduction to Optimization Theory | ||
| Investment Management | ||
| Financial Derivatives | ||
| Operations Management Analytics | ||
| Optimization and Analytics | ||
| Scaling Operations in Technology Ventures: Linking Strategy and Execution | ||
| Analytics and the Digital Economy | ||
OIDD 3250 | ||
OIDD 3530 | ||
| Thinking with Models: Business Analytics for Energy and Sustainability | ||
| Forecasting Methods for Management | ||
| Complete one additional course unit from above BUAN electives or the equivalent from the following: | 1 | |
| Engineering Probability | ||
| Big Data, Big Responsibilities: Toward Accountable Artificial Intelligence | ||
| Optimization and Analytics | ||
| Advanced Decision Systems: Evolutionary Computation | ||
| Operations Analytics Practicum | ||
| Probability | ||
| Stochastic Processes | ||
| Other Wharton Requirements | 33 | |
| Total Course Units | 37 | |
- 1
Students may select at most 1 CU outside of Wharton.
- 2
Students can count only one of the two courses (CIS 4190/5190 or CIS 5200) towards the Business Analytics concentration.