This is the first book to show 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. However, __Excel 2016 for Marketing Statistics: A Guide to Solving Practical Problems__ is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.
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.

lgli/K:\!genesis\!repository8\sp\10.1007%2F978-3-319-43376-9.pdf

lgrsnf/K:\!genesis\!repository8\sp\10.1007%2F978-3-319-43376-9.pdf

nexusstc/Excel 2016 for Marketing Statistics: A Guide to Solving Practical Problems/5e1821109681087b57f2e4f1a3570522.pdf

scihub/10.1007/978-3-319-43376-9.pdf

zlib/Business & Economics/Thomas J. Quirk, Eric Rhiney (auth.)/Excel 2016 for Marketing Statistics: A Guide to Solving Practical Problems_2803675.pdf

Adobe InDesign CC 2015 (Windows)

Quirk, Thomas J., Rhiney, Eric

Thomas Joseph Quirk

Springer Nature Switzerland AG

Springer London, Limited

Excel for statistics, Cham, Switzerland, 2016

Springer Nature, Cham, 2016

1st ed. 2016, 2016-10-10

Switzerland, Switzerland

1st ed. 2016, PS, 2016

sm61806973

producers:
Adobe PDF Library 15.0

{"edition":"1","isbns":["331943375X","3319433768","9783319433752","9783319433769"],"last_page":242,"publisher":"Springer","series":"Excel for Statistics"}

Preface 8
Acknowledgments 12
Contents 14
Chapter 1: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 19
1.1 Mean 19
1.2 Standard Deviation 20
1.3 Standard Error of the Mean 21
1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 21
1.4.1 Using the Fill/Series/Columns Commands 22
1.4.2 Changing the Width of a Column 23
1.4.3 Centering Information in a Range of Cells 24
1.4.4 Naming a Range of Cells 26
1.4.5 Finding the Sample Size Using the =COUNT Function 27
1.4.6 Finding the Mean Score Using the =AVERAGE Function 27
1.4.7 Finding the Standard Deviation Using the =STDEV Function 28
1.4.8 Finding the Standard Error of the Mean 28
1.4.8.1 Formatting Numbers in Number Format (Two decimal places) 29
1.5 Saving a Spreadsheet 30
1.6 Printing a Spreadsheet 31
1.7 Formatting Numbers in Currency Format (Two decimal places) 33
1.8 Formatting Numbers in Number Format (Three decimal places) 35
1.9 End-of-Chapter Practice Problems 35
Reference 38
Chapter 2: Random Number Generator 39
2.1 Creating Frame Numbers for Generating Random Numbers 39
2.2 Creating Random Numbers in an Excel Worksheet 42
2.3 Sorting Frame Numbers into a Random Sequence 44
2.4 Printing an Excel File So That All of the Information Fits onto One Page 47
2.5 End-of-Chapter Practice Problems 52
Reference 53
Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing 54
3.1 Confidence Interval About the Mean 54
3.1.1 How to Estimate the Population Mean 54
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean 55
3.1.3 Estimating the Confidence Interval for the Chevy Impala in Miles Per Gallon 56
3.1.4 Where Did the Number ``1.96 ́ ́ Come From? 57
3.1.5 Finding the Value for t in the Confidence Interval Formula 58
3.1.6 Using Excel ́s TINV Function to Find the Confidence Interval About the Mean 59
3.1.7 Using Excel to Find the 95% Confidence Interval for a Car ́s mpg Claim 59
3.2 Hypothesis Testing 64
3.2.1 Hypotheses Always Refer to the Population of People or Events That You Are Studying 65
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis 66
3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used 66
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean 69
3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 69
3.2.3.2 STEP 2: Select the Appropriate Statistical Test 69
3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test 69
3.2.3.4 STEP 4: Draw a Picture of the Confidence Interval About the Mean, Including the Mean, the Lower Limit of the Interval,... 70
3.2.3.5 STEP 5: Decide on a Decision Rule 70
3.2.3.6 STEP 6: State the Result of Your Statistical Test 70
3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 70
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test 75
3.3.1 Different Ways to Accept the Null Hypothesis 75
3.3.2 Different Ways to Reject the Null Hypothesis 76
3.4 End-of-Chapter Practice Problems 76
References 81
Chapter 4: One-Group t-Test for the Mean 82
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test 82
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 83
4.1.2 STEP 2: Select the Appropriate Statistical Test 83
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test 83
4.1.3.1 Finding the Absolute Value of a Number 83
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test 84
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E 85
4.1.6 STEP 6: State the Result of Your Statistical Test 86
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 86
4.2 One-Group t-Test for the Mean 87
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? 91
4.4 End-of-Chapter Practice Problems 91
References 96
Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups 97
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test 98
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 98
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group 98
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test 100
5.1.4 STEP 4: Select the Appropriate Statistical Test 100
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test 100
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test 100
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E 101
5.1.7.1 Finding the Degrees of Freedom (df) for the Two-Group t-Test 101
5.1.8 STEP 8: State the Result of Your Statistical Test 102
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! 102
5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis 102
5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis 104
5.2 Formula #1: Both Groups Have More Than 30 People in Them 106
5.2.1 An Example of Formula #1 for the Two-Group t-Test 107
5.3 Formula #2: One or Both Groups Have Less Than 30 People in Them 113
5.4 End-of-Chapter Practice Problems 119
References 122
Chapter 6: Correlation and Simple Linear Regression 123
6.1 What Is a ``Correlation? ́ ́ 123
6.1.1 Understanding the Formula for Computing a Correlation 128
6.1.2 Understanding the Nine Steps for Computing a Correlation, r 128
6.2 Using Excel to Compute a Correlation Between Two Variables 130
6.3 Creating a Chart and Drawing the Regression Line onto the Chart 134
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points 136
6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart 140
6.3.1.2 Moving the Chart Below the Table in the Spreadsheet 142
6.3.1.3 Making the Chart ``Longer ́ ́ so That It Is ``Taller ́ ́ 142
6.3.1.4 Making the Chart ``Wider ́ ́ 143
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page 143
6.5 Finding the Regression Equation 145
6.5.1 Installing the Data Analysis ToolPak into Excel 146
6.5.1.1 Installing the Data Analysis ToolPak into Excel 2016 146
6.5.1.2 Installing the Data Analysis ToolPak into Excel 2013 147
6.5.1.3 Installing the Data Analysis ToolPak into Excel 2010 148
6.5.1.4 Installing the Data Analysis ToolPak into Excel 2007 148
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression 149
6.5.2.1 Finding the y-Intercept, a, of the Regression Line 153
6.5.2.2 Finding the Slope, b, of the Regression Line 153
6.5.3 Finding the Equation for the Regression Line 154
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value 154
6.6 Adding the Regression Equation to the Chart 155
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table 159
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet 159
6.8.1 Printing Only the Table and the Chart on a Separate Page 160
6.8.2 Printing Only the Chart on a Separate Page 160
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page 161
6.9 End-of-Chapter Practice Problems 161
References 165
Chapter 7: Multiple Correlation and Multiple Regression 166
7.1 Multiple Regression Equation 166
7.2 Finding the Multiple Correlation and the Multiple Regression Equation 168
7.3 Using the Regression Equation to Predict Annual Sales 172
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression 173
7.5 End-of-Chapter Practice Problems 176
References 181
Chapter 8: One-Way Analysis of Variance (ANOVA) 182
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) 184
8.2 How to Interpret the ANOVA Table Correctly 186
8.3 Using the Decision Rule for the ANOVA F-Test 186
8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test 187
8.4.1 Comparing Dierberg ́s vs. Shop `n Save in Their Prices Using the ANOVA t-Test 188
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test 189
8.4.1.2 Stating the Decision Rule for the ANOVA t-Test 189
8.4.1.3 Performing an ANOVA t-Test Using Excel Commands 190
8.5 End-of-Chapter Practice Problems 192
References 199
Appendices 200
Appendix A: Answers to End-of-Chapter Practice Problems 200
Appendix B: Practice Test 231
Appendix C: Answers to Practice Test 243
Appendix D: Statistical Formulas 253
Appendix E: t-Table 255
Index 256

This is the first book to show 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. However, Excel 2016 for Marketing Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. 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. Includes 167 illustrations in color Suitable for undergraduates or graduate students Prof. Tom Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He is Professor of Marketing in the Walker School of Business & Technology at Webster University in St. Louis, Missouri (USA). He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph.D. in Educational Psychology from Stanford University, and an MBA from The University of Missouri-St. Louis. Prof. Eric Rhiney is currently an Assistant 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 B.S.B.A. with an Emphasis in Marketing from University of Central Missouri, an M.B.A. with an Emphasis in Marketing from Webster University, and a Ph.D. 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 University of Missouri-St. Louis (UMSL) Digital Marketing Conference

This is the first book to show 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. However, Excel 2016 for Marketing Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. 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. Includes 167 illustrations in color Suitable for undergraduates or graduate students Prof. Tom Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He is Professor of Marketing in the Walker School of Business & Technology at Webster University in St. Louis, Missouri (USA). He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph. D. in Educational Psychology from Stanford University, and an MBA from The University of Missouri-St. Louis. Prof. Eric Rhiney is currently an Assistant 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 B.S.B.A. with an Emphasis in Marketing from University of Central Missouri, an M.B.A. with an Emphasis in Marketing from Webster University, and a Ph. D. 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 University of Missouri-St. Louis (UMSL) Digital Marketing Conference

Front Matter....Pages i-xvii
Sample Size, Mean, Standard Deviation, and Standard Error of the Mean....Pages 1-20
Random Number Generator....Pages 21-35
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing....Pages 37-64
One-Group t-Test for the Mean....Pages 65-79
Two-Group t-Test of the Difference of the Means for Independent Groups....Pages 81-106
Correlation and Simple Linear Regression....Pages 107-149
Multiple Correlation and Multiple Regression....Pages 151-166
One-Way Analysis of Variance (ANOVA)....Pages 167-184
Back Matter....Pages 185-242

Showing the capabilities of Microsoft Excel in teaching marketing statistics, this is a step-by-step exercise-driven guide for students and practitioners who need Excel to solve practical marketing problems (including quantitative analyses in marketing courses), even if they are not especially mathematically-inclined, or a bit wary of computers.

2016-11-20