Business Analytics, 4/e (AE-Paperback)
暫譯: 商業分析，第4版 (AE-平裝本)

● 新增章節強調數據與分析使用中的法律與倫理問題。第1章包含一個新的章節，針對與數據和分析使用相關的常見法律與倫理問題進行探討。這個新的法律與倫理章節討論了近期的數據隱私法以及分析模型的實務者和消費者應考慮的倫理問題。

● 實用且相關的問題幫助學生掌握概念和實作技能。來自各個功能業務領域的應用，包括財務、行銷和運營，提供了不同難度層級的重要練習。大多數練習和案例都有節省時間的數據集可供使用。

● 修訂的數據挖掘章節提供更清晰的概念呈現。作者已重新組織並更新本版的數據挖掘章節，以確保學生能夠徹底理解內容的呈現。描述性數據挖掘章節（第5章）現在位於機率章節之後，這樣數據挖掘的討論可以直接將機率的概念整合到解釋中。

● 逐步指導說明重要的分析步驟。清晰的指導說明學生如何使用各種領先的軟體程序來執行文本中討論的分析。

● 新的作業問題和案例強調數據挖掘和累積知識。本版的數據挖掘章節包含更多不需要專業軟體的問題。這使您能夠靈活地介紹這些重要主題，即使您不希望學生學習額外的軟體來解決問題。本版還在文本中引入了許多額外的案例，包括整合多個章節主題的案例，以強調各種分析主題如何相互作用並相互建立。

● 在線數據檔案和模型檔案節省時間。所有用作範例和學生練習的數據集均可在線提供，方便學生下載。DATA檔案是包含與文本中給出的範例和問題相對應的數據的檔案。MODEL檔案包含額外的建模功能，突顯了Excel公式的廣泛使用或其他軟體的使用。

● 新的在線附錄介紹如何使用Tableau進行數據視覺化。這個全新的在線附錄詳細說明了如何最大化Tableau在數據視覺化中的功能。作者運用他們經過驗證的逐步呈現方法，清晰地指導學生使用這個強大的軟體來製作有用的分析圖表。

● 實用且相關的問題幫助學生掌握概念和實作技能。來自各個功能業務領域的應用，包括財務、行銷和運營，提供了不同難度層級的重要練習。大多數練習和案例都有節省時間的數據集可供使用。

Dr. Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Business Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, he served on the faculty of the University of Cincinnati. He has also served as a visiting scholar at Stanford University and as a visiting Professor of Business Administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 40 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in numerous professional journals, including Science, Management Science, Operations Research and Interfaces. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of Interfaces. In 2016, Dr. Camm received the George E. Kimball Medal for service to the operations research profession and in 2017 he was named an INFORMS Fellow.

James J. Cochran is Associate Dean for Research, Professor of Applied Statistics and the Rogers-Spivey Faculty Fellow at The University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S., and M.B.A. from Wright State University and his Ph.D. from the University of Cincinnati. He has been at The University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 40 papers in the development and application of operations research and statistical methods. He has published in several journals, including Management Science, The American Statistician, Communications in Statistics—Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, Interfaces and Statistics and Probability Letters. He received the 2008 INFORMS Prize for the Teaching of Operations Research Practice, 2010 Mu Sigma Rho Statistical Education Award and 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005, was named a Fellow of the American Statistical Association in 2011 and was named a Fellow of INFORMS in 2017. He received the Founders Award in 2014, the Karl E. Peace Award in 2015 from the American Statistical Association and the INFORMS President’s Award in 2019. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, Dr. Cochran has chaired teaching effectiveness workshops around the globe. He has served as operations research consultant to numerous companies and not-for-profit organizations.

Michael J. Fry is Professor of Operations, Business Analytics, and Information Systems (OBAIS) and Academic Director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a B.S. from Texas A&M University, and M.S.E. and Ph.D. degrees from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department chair and has been named a Lindner Research Fellow. He has also been a visiting professor at the Samuel Curtis Johnson Graduate School of Management at Cornell University and the Sauder School of Business at the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IIE Transactions, Critical Care Medicine and Interfaces. His research interests focus on applying analytics to the areas of supply chain management, sports and public-policy operations. He has worked with many different organizations for his research, including Dell, Inc., Starbucks Coffee Company, Great American Insurance Group, the Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals and the Cincinnati Zoo & Botanical Garden. He was named a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, and he has been recognized for both his research and teaching excellence at the University of Cincinnati. In 2019 he led the team that was awarded the INFORMS UPS George D. Smith Prize on behalf of the OBAIS Department at the University of Cincinnati.

Jeffrey W. Ohlmann is Associate Professor of Business Analytics and Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a B.S. from the University of Nebraska, and M.S. and Ph.D. degrees from the University of Michigan. He has taught at the University of Iowa since 2003. Dr. Ohlmann’s research on the modeling and solution of decision-making problems has produced more than two dozen research papers in journals, such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science and European Journal of Operational Research. He has collaborated with companies such as Transfreight, LeanCor, Cargill and the Hamilton County Board of Elections as well as three National Football League franchises. Because of the relevance of his work to the industry, he was bestowed the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

Dr. **Jeffrey D. Camm** 是維克森林大學商學院的 Inmar 總統椅及商業分析副院長。他出生於俄亥俄州辛辛那提，擁有俄亥俄州的 Xavier University 的學士學位及克萊姆森大學的博士學位。在加入維克森林大學的教職之前，他曾在辛辛那提大學任教。他也曾擔任史丹佛大學的訪問學者，以及達特茅斯學院 Tuck 商學院的商業管理訪問教授。Camm 博士在應用於運營管理和市場營銷問題的優化領域發表了超過 40 篇論文。他的研究發表在多個專業期刊上，包括《Science》、《Management Science》、《Operations Research》和《Interfaces》。Camm 博士曾被評選為辛辛那提大學的 Dornoff 教學卓越獎得主，並於 2006 年獲得 INFORMS 運營研究實踐教學獎。他堅信實踐所教，曾擔任多家企業和政府機構的運營研究顧問。從 2005 年到 2010 年，他擔任《Interfaces》的主編。2016 年，Camm 博士因對運營研究專業的貢獻獲得 George E. Kimball 獎章，並於 2017 年被評選為 INFORMS Fellow。

**James J. Cochran** 是阿拉巴馬大學的研究副院長、應用統計學教授及 Rogers-Spivey 教職研究員。他出生於俄亥俄州代頓，獲得 Wright State University 的學士、碩士及工商管理碩士學位，並在辛辛那提大學獲得博士學位。自 2014 年以來，他一直在阿拉巴馬大學任教，並曾擔任史丹佛大學、塔爾卡大學、南非大學及倫納德·德·文西大學的訪問學者。Cochran 博士在運營研究和統計方法的開發與應用方面發表了超過 40 篇論文。他的研究發表在多個期刊上，包括《Management Science》、《The American Statistician》、《Communications in Statistics—Theory and Methods》、《Annals of Operations Research》、《European Journal of Operational Research》、《Journal of Combinatorial Optimization》、《Interfaces》和《Statistics and Probability Letters》。他於 2008 年獲得 INFORMS 運營研究實踐教學獎，2010 年獲得 Mu Sigma Rho 統計教育獎，並於 2016 年獲得美國統計協會的 Waller 傑出教學生涯獎。Cochran 博士於 2005 年當選為國際統計學會會員，2011 年被評選為美國統計協會的 Fellow，2017 年被評選為 INFORMS Fellow。他於 2014 年獲得創始人獎，2015 年獲得美國統計協會的 Karl E. Peace 獎，並於 2019 年獲得 INFORMS 會長獎。Cochran 博士強烈支持有效的運營研究和統計教育，以改善對實際問題的應用質量，並在全球主持教學有效性研討會。他曾擔任多家企業和非營利組織的運營研究顧問。

**Michael J. Fry** 是辛辛那提大學 Carl H. Lindner 商學院的運營、商業分析和資訊系統 (OBAIS) 教授及商業分析中心的學術主任。他出生於德克薩斯州基林，獲得德克薩斯 A&M 大學的學士學位，以及密西根大學的碩士工程學位和博士學位。自 2002 年以來，他一直在辛辛那提大學任教，曾擔任系主任並被評選為 Lindner 研究員。他也曾擔任康奈爾大學 Samuel Curtis Johnson 研究生管理學院及英屬哥倫比亞大學 Sauder 商學院的訪問教授。Fry 博士在《Operations Research》、《M&SOM》、《Transportation Science》、《Naval Research Logistics》、《IIE Transactions》、《Critical Care Medicine》和《Interfaces》等期刊上發表了超過 25 篇研究論文。他的研究興趣集中在將分析應用於供應鏈管理、體育和公共政策運營等領域。他曾與許多不同的組織合作進行研究，包括 Dell, Inc.、星巴克咖啡公司、大美國保險集團、辛辛那提消防局、俄亥俄州選舉委員會、辛辛那提孟加拉虎隊和辛辛那提動物園及植物園。他曾被提名為 Daniel H. Wagner 運營研究實踐卓越獎的決賽入圍者，並因其在辛辛那提大學的研究和教學卓越而受到認可。2019 年，他領導的團隊代表辛辛那提大學 OBAIS 系獲得 INFORMS UPS George D. Smith 獎。

**Jeffrey W. Ohlmann** 是愛荷華大學 Tippie 商學院的商業分析副教授及 Huneke 研究員。他出生於內布拉斯加州的瓦倫丁，獲得內布拉斯加大學的學士學位，以及密西根大學的碩士和博士學位。自 2003 年以來，他一直在愛荷華大學任教。Ohlmann 博士在決策問題建模和解決方面的研究已在《Operations Research》、《Mathematics of Operations Research》、《INFORMS Journal on Computing》、《Transportation Science》和《European Journal of Operational Research》等期刊上發表了超過二十篇研究論文。他曾與 Transfreight、LeanCor、Cargill 和漢密爾頓縣選舉委員會等公司合作，並與三個國家橄欖球聯盟特許經營隊合作。由於他的工作與行業的相關性，他獲得了 George B. Dantzig 論文獎，並被提名為 Daniel H. Wagner 運營研究實踐卓越獎的決賽入圍者。

1. Introduction.
2. Descriptive Statistics.
3. Data Visualization.
4. Probability: An Introduction to Modeling Uncertainty.
5. Descriptive Data Mining.
6. Statistical Inference.
7. Linear Regression.
8. Time Series Analysis and Forecasting.
9. Predictive Data Mining.
10. Spreadsheet Models.
11. Monte Carlo Simulation.
12. Linear Optimization Models.
13. Integer Linear Optimization Models.
14. Nonlinear Optimization Models.
15. Decision Analysis.
Multi-Chapter Case Problems
                  Capital State University Game-Day Magazines
                  Hanover Inc.
Appendix A: Basics of Excel.
Appendix B: Database Basics with Microsoft Access.
Appendix C: Solutions to Even-Numbered Questions (MindTap Reader).

1. Introduction.

2. Descriptive Statistics.

3. Data Visualization.

4. Probability: An Introduction to Modeling Uncertainty.

5. Descriptive Data Mining.

6. Statistical Inference.

7. Linear Regression.

8. Time Series Analysis and Forecasting.

9. Predictive Data Mining.

10. Spreadsheet Models.

11. Monte Carlo Simulation.

12. Linear Optimization Models.

13. Integer Linear Optimization Models.

14. Nonlinear Optimization Models.

15. Decision Analysis.

Multi-Chapter Case Problems

                  Capital State University Game-Day Magazines

                  Hanover Inc.

Appendix A: Basics of Excel.

Appendix B: Database Basics with Microsoft Access.

Appendix C: Solutions to Even-Numbered Questions (MindTap Reader).