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<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">Dear Colleagues,<span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">If you teach Business or Data Analytics, you may be
interested in the recently published new edition of<span style="color:black"> the
popular textbook, <i>Business Analytics: Communicating with Numbers</i>, 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. <span></span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">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.<span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">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 (</span><a href="https://cpslo-my.sharepoint.com/:b:/g/personal/lchen24_calpoly_edu/Ecqpn71C32ZOtU-ZytpZK9cB9BRFp2Xj3YUg-d12m3Oo7g?e=RWcs4h" style="color:blue;text-decoration:underline"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">https://cpslo-my.sharepoint.com/:b:/g/personal/lchen24_calpoly_edu/Ecqpn71C32ZOtU-ZytpZK9cB9BRFp2Xj3YUg-d12m3Oo7g?e=RWcs4h</span></a><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">) for an overview of the features of the text and the Preface (</span><a href="https://cpslo-my.sharepoint.com/:b:/g/personal/lchen24_calpoly_edu/ESgAPa0W04FCkbzIemnvyjcBF1lvfp6ltpTl2kDzj5uwqA?e=OJjCjN" style="color:blue;text-decoration:underline"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">https://cpslo-my.sharepoint.com/:b:/g/personal/lchen24_calpoly_edu/ESgAPa0W04FCkbzIemnvyjcBF1lvfp6ltpTl2kDzj5uwqA?e=OJjCjN</span></a><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">) for a detailed Table of Contents.<span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">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: </span><a href="https://www.mheducation.com/highered/product/Business-Analytics-Jaggia.html?viewOption=instructor&release=2025+Release" style="color:blue;text-decoration:underline"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">https://www.mheducation.com/highered/product/Business-Analytics-Jaggia.html?viewOption=instructor&release=2025+Release</span></a><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">. <span> </span></span><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif"><span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">Please also feel free to reach out to McGraw-Hill
analytics product team (</span><a href="mailto:Kristen.Salinas@mheducation.com" style="color:blue;text-decoration:underline"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">Kristen.Salinas@mheducation.com</span></a><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">) </span><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">or
the author team (<a href="mailto:lchen24@calpoly.edu">lchen24@calpoly.edu</a>) for questions and comments. We welcome
your questions and feedback about the text.<span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif;color:black">Below is a brief TOC for the text:<span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">Chapter 1: Introduction to Business Analytics<br>
Chapter 2: Data Management and Wrangling<br>
Chapter 3: Summary Measures<br>
Chapter 4: Data Visualization<br>
Chapter 5: Probability and Probability Distributions<br>
Chapter 6: Statistical Inference<br>
Chapter 7: Regression Analysis<br>
Chapter 8: More Topics in Regression Analysis<br>
Chapter 9: Logistic Regression<br>
Chapter 10: Forecasting with Time Series Data<br>
Chapter 11: Introduction to Data Mining<br>
Chapter 12: Supervised Data Mining: k-Nearest Neighbors and Naïve Bayes<br>
Chapter 13: Supervised Data Mining: Decision Trees<br>
Chapter 14: Unsupervised Data Mining: Cluster Analysis and Association Rules<br>
Chapter 15: Spreadsheet Modeling<br>
Chapter 16: Risk Analysis and Simulation<br>
Chapter 17: Optimization: Linear Programming<br>
Chapter 18: More Applications in Optimization<br>
Appendixes<br>
Appendix A: Big Data Sets: Variable Description and Data Dictionary<br>
Appendix B: Getting Started with Excel and Excel Add-Ins<br>
Appendix C: Getting Started with R<span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 8pt;line-height:107%;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:12pt;line-height:107%;font-family:"Times New Roman",serif">Appendix D: Getting Started with Python<br>
Appendix E: Answers to Selected Exercises<br>
<br>
<br>
<span></span></span></p>
<p class="MsoNormal" style="margin:0in;line-height:normal;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:9pt;font-family:"Helvetica",sans-serif">Dr. Leida Chen</span><span style="font-size:12pt;font-family:"Times New Roman",serif"><span></span></span></p>
<p class="MsoNormal" style="margin:0in;line-height:normal;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:9pt;font-family:"Helvetica",sans-serif">Professor and Chair of
Management, HR, and IS</span><span style="font-size:12pt;font-family:"Times New Roman",serif"><span></span></span></p>
<p class="MsoNormal" style="margin:0in;line-height:normal;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:9pt;font-family:"Helvetica",sans-serif">Orfalea College of Business</span><span style="font-size:12pt;font-family:"Times New Roman",serif"><span></span></span></p>
<p class="MsoNormal" style="margin:0in;line-height:normal;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:9pt;font-family:"Helvetica",sans-serif">Cal Poly, San Luis Obispo, CA</span><span style="font-size:12pt;font-family:"Times New Roman",serif"><span></span></span></p>
<p class="MsoNormal" style="margin:0in;line-height:normal;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:9pt;font-family:"Helvetica",sans-serif">(805)756-1768</span><span style="font-size:12pt;font-family:"Times New Roman",serif"><span></span></span></p>
<p class="MsoNormal" style="margin:0in;line-height:normal;font-size:11pt;font-family:"Calibri",sans-serif"><span style="font-size:9pt;font-family:"Helvetica",sans-serif"><a href="mailto:lchen24@calpoly.edu">lchen24@calpoly.edu</a></span><span style="font-size:12pt;font-family:"Times New Roman",serif"><span></span></span></p>
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