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. <i>
Excel 2019 for Advertising Statistics: A Guide to Solving Practical Problems (Excel for Statistics)
β Scribed by Thomas J. Quirk
- Publisher
- Springer
- Year
- 2020
- Tongue
- English
- Leaves
- 264
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 Excelβs drop-down formula menus (e.g., simple linear regression, multiple correlation and multiple regression, andone-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.
β
β¦ Table of Contents
Preface
Acknowledgements
Contents
Chapter 1: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
1.1 Mean
1.2 Standard Deviation
1.3 Standard Error of the Mean
1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
1.4.1 Using the Fill/Series/Columns Commands
1.4.2 Changing the Width of a Column
1.4.3 Centering Information in a Range of Cells
1.4.4 Naming a Range of Cells
1.4.5 Finding the Sample Size Using the =COUNT Function
1.4.6 Finding the Mean Score Using the =AVERAGE Function
1.4.7 Finding the Standard Deviation Using the =STDEV Function
1.4.8 Finding the Standard Error of the Mean
1.4.8.1 Formatting Numbers in Number Format (Two Decimal Places)
1.5 Saving a Spreadsheet
1.6 Printing a Spreadsheet
1.7 Formatting Numbers in Currency Format (Two Decimal Places)
1.8 Formatting Numbers in Number Format (Three Decimal Places)
1.9 End-of-Chapter Practice Problems
References
Chapter 2: Random Number Generator
2.1 Creating Frame Numbers for Generating Random Numbers
2.2 Creating Random Numbers in an Excel Worksheet
2.3 Sorting Frame Numbers into a Random Sequence
2.4 Printing an Excel File So That All of the Information Fits onto One Page
2.5 End-of-Chapter Practice Problems
Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
3.1 Confidence Interval About the Mean
3.1.1 How to Estimate the Population Mean
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean
3.1.3 Estimating the Confidence Interval for the Chevy Impala in Miles Per Gallon
3.1.4 Where Did the Number 1.96´´ Come From?
3.1.5 Finding the Value for t in the Confidence Interval Formula
3.1.6 Using ExcelΒ΄s TINV Function to Find the Confidence Interval About the Mean
3.1.7 Using Excel to Find the 95% Confidence Interval for a CarΒ΄s mpg Claim
3.2 Hypothesis Testing
3.2.1 Hypotheses Always Refer to the Population of People or Events That You Are Studying
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis
3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used
3.2.3 The Seven Steps for Hypothesis-Testing Using the Confidence Interval About the Mean
3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis
3.2.3.2 STEP 2: Select the Appropriate Statistical Test
3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test
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,...
3.2.3.5 STEP 5: Decide on a Decision Rule
3.2.3.6 STEP 6: State the Result of Your Statistical Test
3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English!
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test
3.3.1 Different Ways to Accept the Null Hypothesis
3.3.2 Different Ways to Reject the Null Hypothesis
3.4 End-of-Chapter Practice Problems
References
Chapter 4: One-Group t-Test for the Mean
4.1 The Seven STEPS for Hypothesis-Testing Using the One-Group t-Test
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis
4.1.2 STEP 2: Select the Appropriate Statistical Test
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test
4.1.3.1 Finding the Absolute Value of a Number
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E
4.1.6 STEP 6: State the Result of Your Statistical Test
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English!
4.2 One-Group t-Test for the Mean
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses?
4.4 End-of-Chapter Practice Problems
References
Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups
5.1 The Nine STEPS for Hypothesis-Testing Using the Two-Group t-Test
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test
5.1.4 STEP 4: Select the Appropriate Statistical Test
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E
5.1.7.1 Finding the Degrees of Freedom (df) for the Two-Group t-Test
5.1.8 STEP 8: State the Result of Your Statistical Test
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English!
5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis
5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis
5.2 Formula #1: Both Groups Have More Than 30 People in Them
5.2.1 An Example of Formula #1 for the Two-Group t-Test
5.3 Formula #2: One or Both Groups Have Less Than 30 People in Them
5.4 End-of-Chapter Practice Problems
References
Chapter 6: Correlation and Simple Linear Regression
6.1 What Is aCorrelation?´´
6.1.1 Understanding the Formula for Computing a Correlation
6.1.2 Understanding the Nine Steps for Computing a Correlation, r
6.2 Using Excel to Compute a Correlation Between Two Variables
6.3 Creating a Chart and Drawing the Regression Line onto the Chart
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points
6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart
6.3.1.2 Moving the Chart Below the Table in the Spreadsheet
6.3.1.3 Making the Chart Longer´´ So That It IsTaller´´
6.3.1.4 Making the Chart `Wider´´
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page
6.5 Finding the Regression Equation
6.5.1 Installing the Data Analysis ToolPak into Excel
6.5.1.1 Installing the Data Analysis ToolPak into Excel 2019
6.5.1.2 Installing the Data Analysis ToolPak into Excel 2016
6.5.1.3 Installing the Data Analysis ToolPak into Excel 2013
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression
6.5.2.1 Finding the y-Intercept, a, of the Regression Line
6.5.2.2 Finding the Slope, b, of the Regression Line
6.5.3 Finding the Equation for the Regression Line
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value
6.6 Adding the Regression Equation to the Chart
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet
6.8.1 Printing Only the Table and the Chart on a Separate Page
6.8.2 Printing Only the Chart on a Separate Page
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page
6.9 End-of-Chapter Practice Problems
References
Chapter 7: Multiple Correlation and Multiple Regression
7.1 Multiple Regression Equation
7.2 Finding the Multiple Correlation and the Multiple Regression Equation
7.3 Using the Regression Equation to Predict FIRST-YEAR GPA
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression
7.5 End-of-Chapter Practice Problems
References
Chapter 8: One-Way Analysis of Variance (ANOVA)
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA)
8.2 How to Interpret the ANOVA Table Correctly
8.3 Using the Decision Rule for the ANOVA F-Test
8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test
8.4.1 Comparing DierbergΒ΄s vs. Shopn Save in Their Prices Using the ANOVA t-Test
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test
8.4.1.2 Stating the Decision Rule for the ANOVA t-Test
8.4.1.3 Performing an ANOVA t-Test Using Excel Commands
8.5 End-of-Chapter Practice Problems
References
Appendices
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
π SIMILAR VOLUMES
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