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[学科前沿] Excel 2019 for Advertising Statistics_A Guide to Solving Practical Problems, 2/E [推广有奖]

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Excel 2019 for Advertising Statistics: A Guide to Solving Practical Problems, 2nd Edition
by Thomas J. Quirk (Author), Eric Rhiney (Author)

About the Author
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.

About this book
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.

Brief Contents
1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 1
    1.1 Mean 1
    1.2 Standard Deviation 2
    1.3 Standard Error of the Mean 3
    1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 4
    1.5 Saving a Spreadsheet 13
    1.6 Printing a Spreadsheet 14
    1.7 Formatting Numbers in Currency Format (Two Decimal Places) 15
    1.8 Formatting Numbers in Number Format (Three Decimal Places) 17
    1.9 End-of-Chapter Practice Problems 17
    References 21
2 Random Number Generator 23
    2.1 Creating Frame Numbers for Generating Random Numbers 23
    2.2 Creating Random Numbers in an Excel Worksheet 27
    2.3 Sorting Frame Numbers into a Random Sequence 28
    2.4 Printing an Excel File So That All of the Information Fits onto One Page 31
    2.5 End-of-Chapter Practice Problems 36
3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing 39
    3.1 Confidence Interval About the Mean 39
    3.2 Hypothesis Testing 50
    3.3 Alternative Ways to Summarize the Result of a Hypothesis Test 60
    3.4 End-of-Chapter Practice Problems 61
    References 66
4 One-Group t-Test for the Mean 67
    4.1 The Seven STEPS for Hypothesis-Testing Using the One-Group t-Test 67
    4.2 One-Group t-Test for the Mean 72
    4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? 77
    4.4 End-of-Chapter Practice Problems 78
    References 81
5 Two-Group t-Test of the Difference of the Means for Independent Groups 83
    5.1 The Nine STEPS for Hypothesis-Testing Using the Two-Group t-Test 84
    5.2 Formula #1: Both Groups Have More Than 30 People in Them 92
    5.3 Formula #2: One or Both Groups Have Less Than 30 People in Them 99
    5.4 End-of-Chapter Practice Problems 105
    References 109
6 Correlation and Simple Linear Regression 111
    6.1 What Is a “Correlation?” 111
    6.2 Using Excel to Compute a Correlation Between Two Variables 118
    6.3 Creating a Chart and Drawing the Regression Line onto the Chart 122
    6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page 132
    6.5 Finding the Regression Equation 134
    6.6 Adding the Regression Equation to the Chart 142
    6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table 145
    6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet 146
    6.9 End-of-Chapter Practice Problems 148
    References 154
7 Multiple Correlation and Multiple Regression 155
    7.1 Multiple Regression Equation 155
    7.2 Finding the Multiple Correlation and the Multiple Regression Equation 158
    7.3 Using the Regression Equation to Predict FIRST-YEAR GPA 162
    7.4 Using Excel to Create a Correlation Matrix in Multiple Regression 162
    7.5 End-of-Chapter Practice Problems 166
    References 171
8 One-Way Analysis of Variance (ANOVA) 173
    8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) 175
    8.2 How to Interpret the ANOVA Table Correctly 177
    8.3 Using the Decision Rule for the ANOVA F-Test 178
    8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test 179
    8.5 End-of-Chapter Practice Problems 184
    References 191
Appendices 193
    Appendix A: Answers to End-of-Chapter Practice Problems 193
    Appendix B: Practice Test 227
    Appendix C: Answers to Practice Test 240
    Appendix D: Statistical Formulas 250
    Appendix E: t-Table 252
Index 253

Pages: 254
Publisher: Springer; 2 edition (March 2, 2020)
Language: English
ASIN: B085DM81W9

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