Excel 2016 for Advertising Statistics : A Guide to Solving Practical Problems. 1st ed. 2017

種類:

電子ブック

責任表示:

by Thomas J. Quirk, Eric Rhiney

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2017

著者名:

• Quirk, Thomas J.
• Rhiney, Eric.
• SpringerLink (Online service)

シリーズ名:

Excel for Statistics ;

ISBN:

9783319721040 [3319721046]    

注記:

Preface -- Acknowledgements --  Ch 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- Ch 2     Random Number Generator --  Ch 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- Ch 4 One-Group t-Test for the Mean -- Ch 5 Two-Group t-Test of the Difference of the Means for Independent Groups -- Ch 6 Correlation and Simple Linear Regression -- Ch 7 Multiple Correlation and Multiple Regression -- Ch 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.
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 in the workplace, whether or not they have taken a course in statistics. Excel 2016 for Advertising Statistics explains statistical formulas and offers practical examples for how students can solve real-world advertising statistics problems. This book leaves detailed explanations of statistical theory to other statistics textbooks and focuses entirely on practical, real-world problem solving. Each chapter briefly explains a topic and then demonstrates how to use Excel commands and formulas to solve specific advertising statistics problems.  This book gives practice in using Excel 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

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