Announcing the Publication of the 2025 Release of Business Analytics: Communicating with Numbers, by Jaggia, Kelly, Lertwachara, and Chen

[Leida Chen]

Dear Colleagues,

If you teach Business or Data Analytics, you may be interested in the
recently published new edition of the popular textbook, *Business
Analytics: Communicating with Numbers*, authored by Jaggia, Kelly,
Lertwachara, and Chen, published by McGraw-Hill. The text was named Product
of the Year for McGraw-Hill and widely adopted by business/data analytics
courses at both the undergraduate and graduate levels.

The 2025 release of the textbook continues to reinforce and expand six core
features that were well-received in earlier editions: 1) holistic approach
to data analytics, 2) integrated introductory cases, 3) integration of
popular software solutions, 4) writing with big data, 5) emphasis on data
mining and machine learning, and 6) comprehensive pedagogical tools (McGraw
Hill’s Connect) for teaching and learning effectiveness. The new edition
includes the following new features: 1) complete integration of Python
instructions throughout the book, 2) expanded chapter on data wrangling and
visualization, and 3) a new section on text analytics. In addition, two
capstone data cases are provided online through McGraw Hill’s Connect
platform.

Using a project-based pedagogical approach, this text seamlessly threads
the topics of data wrangling, descriptive analytics, predictive analytics,
data mining and machine learning, prescriptive analytics, and data
storytelling into a cohesive whole. Hands-on instructions for Excel,
Analytic Solver (Excel Add-in), R, and Python are included in each chapter.
In addition to detailed analytics cases for illustrating the concepts and
techniques, each chapter comes with over 50 hands-on exercise problems with
datasets and Writing with Big Data cases. Please see the product flyer (
https://cpslo-my.sharepoint.com/:b:/g/personal/lchen24_calpoly_edu/Ecqpn71C32ZOtU-ZytpZK9cB9BRFp2Xj3YUg-d12m3Oo7g?e=RWcs4h)
for an overview of the features of the text and the Preface (
https://cpslo-my.sharepoint.com/:b:/g/personal/lchen24_calpoly_edu/ESgAPa0W04FCkbzIemnvyjcBF1lvfp6ltpTl2kDzj5uwqA?e=OJjCjN)
for a detailed Table of Contents.

If you are interested in reviewing the text or getting access to
McGraw-Hill’s Connect digital course and instructor resources for this
text, please contact your McGraw-Hill rep or use the following links to
request a desk copy:
https://www.mheducation.com/highered/product/Business-Analytics-Jaggia.html?viewOption=instructor&release=2025+Release.


Please also feel free to reach out to McGraw-Hill analytics product team (
Kristen.Salinas at mheducation.com) or the author team (lchen24 at calpoly.edu)
for questions and comments. We welcome your questions and feedback about
the text.

Below is a brief TOC for the text:

Chapter 1: Introduction to Business Analytics
Chapter 2: Data Management and Wrangling
Chapter 3: Summary Measures
Chapter 4: Data Visualization
Chapter 5: Probability and Probability Distributions
Chapter 6: Statistical Inference
Chapter 7: Regression Analysis
Chapter 8: More Topics in Regression Analysis
Chapter 9: Logistic Regression
Chapter 10: Forecasting with Time Series Data
Chapter 11: Introduction to Data Mining
Chapter 12: Supervised Data Mining: k-Nearest Neighbors and Naïve Bayes
Chapter 13: Supervised Data Mining: Decision Trees
Chapter 14: Unsupervised Data Mining: Cluster Analysis and Association Rules
Chapter 15: Spreadsheet Modeling
Chapter 16: Risk Analysis and Simulation
Chapter 17: Optimization: Linear Programming
Chapter 18: More Applications in Optimization
Appendixes
Appendix A: Big Data Sets: Variable Description and Data Dictionary
Appendix B: Getting Started with Excel and Excel Add-Ins
Appendix C: Getting Started with R

Appendix D: Getting Started with Python
Appendix E: Answers to Selected Exercises


Dr. Leida Chen

Professor and Chair of Management, HR, and IS

Orfalea College of Business

Cal Poly, San Luis Obispo, CA

(805)756-1768

lchen24 at calpoly.edu
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