Preface.- Acknowledgements.- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean.- 2 Random Number Generator.- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing.- 4 One-Group t-Test for the Mean.- 5 Two-Group t-Test of the Difference of the Means for Independent Groups.- 6 Correlation and Simple Linear Regression.- 7 Multiple Correlation and Multiple Regression.- 8 One-Way Analysis of Variance (ANOVA).- Appendix A: Answers to End-of-Chapter Practice Problems.- Appendix B: Practice Test.- Appendix C: Answers to Practice Test.- Appendix D: Statistical Formulas.- Appendix E: t-table.- Index.
Prof. Thomas J. Quirk is a Professor Emeritus of Marketing in The Walker School of Business & Technology at Webster University based in St. Louis, Missouri (US) where he taught Marketing Statistics, Marketing Research, and Pricing Strategies. He has published over 20 articles in professional journals, and presented over 20 papers at professional conferences. He holds a BS in Mathematics from John Carroll University, both an MA in Education and a PhD in Educational Psychology from Stanford University, and an MBA from The University of Missouri-St. Louis.
Prof. Eric Rhiney is an Associate Professor of Marketing in The Walker School of Business at Webster University in St. Louis, Missouri (US) where he teaches Research Design, Marketing Research, and Marketing Strategies. He holds a BSBA with an Emphasis in Marketing from University of Central Missouri, an MBA with an Emphasis in Marketing from Webster University, and a PhD in Marketing and International Business from St. Louis University. He did marketing research professionally for over ten years, engaging in research for companies such as Pizza Hut, Monsanto, Chrysler and Hardee’s. He is involved in a number of quantitative research studies focused on in-group out-group orientation on consumer attitudes, digital marketing behavior, and cross-cultural marketing and has presented is work at a number of conferences including The American Marketing Association, the International Business Association, and the Marketing Management Association and the UMSL Digital Marketing Conference.
This book shows the capabilities of Microsoft Excel in teaching marketing statistics effectively. It is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical marketing problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically inclined, or if you are wary of computers, this is the right book for you.
Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in marketing courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Marketing Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.
In this new edition, each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand marketing problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned.