Newly revised for Excel 2019, this text is a step-by-step guide for students taking a first course in statistics for advertising and for advertising managers and practitioners who want to learn how to use Excel to solve practical statistics problems in the workplace, whether or not they have taken a course in statistics. Excel 2019 for Advertising Statistics explains statistical formulas and offers practical examples for how students can solve real-world advertising statistics problems. Each chapter offers a concise overview of a topic, and then demonstrates how to use Excel commands and formulas to solve specific advertising statistics problems. This book demonstrates how to use Excel 2019 in two different ways: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel's drop-down formula menus (e.g., simple linear regression, multiple correlation and multiple regression, and one-way ANOVA). Three practice problems are provided at the end of each chapter, along with their solutions in an appendix. An additional practice test allows readers to test their understanding of each chapter by attempting to solve a specific practical advertising statistics problem using Excel; the solution to each of these problems is also given in an appendix. This latest edition features a wealth of new end-of-chapter problems and an update of the chapter content throughout.

Autorentext

Prof. Thomas J. Quirk is currently a Professor Emeritus of Marketing in The Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA) where he taught Marketing Statistics, Marketing Research, and Pricing Strategies. He has published 20+ articles in professional journals and presented 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 currently an Associate Professor of Marketing in The Walker School of Business & Technology at Webster University in St. Louis, Missouri (USA) where he teaches Research Design, Marketing Research and Marketing Strategies. He holds a BSBA with an Emphasis in Marketing from the 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 he has presented his 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.

Inhalt

Preface.- Acknowledgements.- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean.- 2Random Number Generator.- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing.- 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.