Business Analytics Joint Concentration

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.

Business analytics has emerged in recent years as a powerful and required capability for firms in competitive markets. The quantity, quality and diversity of available data have never been greater, which has created new and significant opportunities for organizations to use data to improve their decisions with respect to both internal resources as well as external interactions with suppliers and customers.

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).

Concentration Requirements

Beyond core course requirements in OID (OIDD 1010) and STAT (STAT 1010 and STAT 1020), students must complete 4 credit units from the set of approved courses listed below. Furthermore, among the set of selected courses, there must be at least 1 CU that provides competency for each of the following three fundamental skills in business analytics:

  1. Data collection (c): methods for acquiring and manipulating data
  2. Advanced data analysis (a): working with data sets in a computing environment
  3. Optimization (o): computer-based prescriptive decision making

Some courses provide competency in more than one of the above skills. Some courses are approved electives that do not focus on the set of fundamental skills but are nevertheless relevant for the management and implementation of business analytics. The skills provided by each course are indicated below with a “c”, “a” or “o”.

Students may select at most 1 CU outside of Wharton. Courses below are 1 CU unless otherwise noted.

Approved Undergraduate Courses

ACCT2700 (a, c): Predictive Analytics Using Financial Disclosures

BEPP2800 (a): Applied Data Analysis and Causality for Business and Public Policy

BIOL 447 (a): Biological Data Analysis

CIS3990: The Science of Data Ethics

+CIS4190/5190 (a): Introduction to Machine Learning

CIS4500 (c): Database and Information Systems

+CIS5200 (a): Machine Learning

CIS5450 (a, c): Big Data Analytics

COMM 3130 (a, c): Computational Text Analysis for Communication Research

ESE3010: Engineering Probability

ESE3050 (a): Foundations of Data Science

ESE4020/5420 (a): Statistics for Data Science

ESE5030 (o): Simulations, Modeling, and Analysis

ESE5040 (o): Introduction to Linear, Nonlinear and Integer Optimization

ESE5060 (o): Introduction to Optimization Theory

FNCE2050 (o): Investment Management

FNCE2170 (a,o): Financial Derivatives

FNCE2370 (a,c): Data Science for Finance

FNCE2800 (a): Fin-Tech

HCMG3570 (a,c): Health Care Data and Analytics

LGST2420: Big Data, Big Responsibilities: The Law and Ethics of Business Analytics

MGMT2930 (a, c): People Analytics

MKTG2120 (a): Data and Analysis for Marketing Decisions

MKTG2710 (a): Models for Marketing Strategy

MKTG3090 (a, c): Experiments for Business Decision Making

MKTG3520 (a, c): Marketing Analytics

MKTG4760 (a): Applied Probability Models in Marketing

OIDD1050 (c): Developing Tools for Data Access and Analysis

OIDD2010 (o): Technology Management, Information and the Digital Economy

OIDD2150 (a,c): Intro to Analytics and the Digital Economy

OIDD2200 (a,o): Introduction to Operations Management

OIDD2240 (o): Analytics for Service Operations

OIDD2360 (o): Scaling Operations in Technology Ventures

OIDD2450 (a, c, o): Advanced Analytics and the Digital Economy

OIDD2550 (a, c): A.I., Data, and Society

OIDD3110 (c): Business Computer Languages

OIDD3140 (c, a): Enabling Technologies

OIDD3150 (a, c): Databases for Analytics

OIDD3190 (a, c): Advanced Decision Systems

OIDD3210 (o): Management Science

OIDD3250 (a,c,o): Thinking with Models

OIDD3530 (o): Mathematical Models in Finance

OIDD4690 0(a,c): Advanced Information Strategy and Economics

OIDD5250 (a,c,o): Thinking with Models: Business Analytics for Energy and Sustainability

STAT4050 (a,c): Statistical Computing with R (0.5 CU course)

STAT4100 (c): Data Collection & Acquisition

STAT4220 (a,c): Predictive Analytics (0.5 CU course)

STAT4300: Probability

STAT4310 (a): Statistical Inference

STAT4330: Stochastic Processes

STAT4350 (a,c): Forecasting Methods for Management (Note: STAT 435 will not be offered in Fall 2022)

STAT4420 (a): Bayesian Data Analysis

STAT4700 (a,c): Data Analytics and Statistical Computing

STAT4710 (a,c): Modern Data Mining

STAT4740 (a): Modern Regression for the Social, Behavioral and Biological Sciences

STAT4750 (a,c): Sample Survey Design

STAT/OIDD4770 (a,c): Intro to Python for Data Science

STAT5200 (a): Applied Econometrics I


+ Students can count only one of the two courses (CIS4190/5190 or 5200) towards the Business Analytics concentration.

Business Analytics Joint Concentration Advisors

Prof. Sergei Savin (OIDD)  –  JMHH 570  –  215-898-1175  –
Prof. Richard Waterman (STAT) – JMHH 443 –

See the Wharton Customer Analytics Initiative ( for a collaborating venture, which offers opportunities for students with Business Analytics skills.