This book shows how Microsoft Excel is able to teach human resource management statistics effectively. Similar to the previously published __Excel 2010 for Human Resource Management Statistics__, it is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical human resource management 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 human resource management courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. __Excel 2013 for Human Resource Management Statistics: A Guide to Solving Practical Problems__ is the next 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 human resource management 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.

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Thomas J Quirk; Julie Palmer-Schuyler; SpringerLink (Online service)

Quirk, Thomas J., Palmer-Schuyler, Julie

Adobe InDesign CS6 (Windows)

Thomas Joseph Quirk

Springer International Publishing AG

Springer Nature Switzerland AG

Springer Nature (Textbooks & Major Reference Works), Cham, 2016

Excel for statistics, Switzerland, 2016

Switzerland, Switzerland

Mar 09, 2016

2, 20160308

lg1468459

producers:
Adobe PDF Library 10.0.1

{"edition":"1","isbns":["3319289810","3319289829","9783319289816","9783319289823"],"publisher":"Springer","series":"Excel for Statistics"}

Source title: Excel 2013 for Human Resource Management Statistics: A Guide to Solving Practical Problems (Excel for Statistics)

Preface 8
Acknowledgments 10
Contents 12
About the Authors 18
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 22
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 32
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
References 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 50
Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing 53
3.1 Confidence Interval About the Mean 53
3.1.1 How to Estimate the Population Mean 53
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean 54
3.1.3 Estimating the Confidence Interval for TIME TO FILL 55
3.1.4 Where Did the Number ``1.96 ́ ́ Come From? 56
3.1.5 Finding the Value for t in the Confidence Interval Formula 57
3.1.6 Using Excel ́s TINV Function to Find the Confidence Interval About the Mean 58
3.1.7 Using Excel to Find the 95% Confidence Interval for TIME TO FILL 58
3.2 Hypothesis Testing 65
3.2.1 Hypotheses Always Refer to the Population That You Are Studying 66
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis 67
3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used 67
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean 70
3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 71
3.2.3.2 STEP 2: Select the Appropriate Statistical Test 71
3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test 71
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,... 72
3.2.3.5 STEP 5: Decide on a Decision Rule 72
3.2.3.6 STEP 6: State the Result of Your Statistical Test 72
3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 72
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test 77
3.3.1 Different Ways to Accept the Null Hypothesis 78
3.3.2 Different Ways to Reject the Null Hypothesis 78
3.4 End-of-Chapter Practice Problems 78
References 83
Chapter 4: One-Group t-Test for the Mean 84
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test 84
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 85
4.1.2 STEP 2: Select the Appropriate Statistical Test 85
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test 85
4.1.3.1 Finding the Absolute Value of a Number 86
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test 86
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E 87
4.1.6 STEP 6: State the Result of Your Statistical Test 88
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 88
4.2 One-Group t-Test for the Mean 89
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? 95
4.4 End-of-Chapter Practice Problems 95
References 98
Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups 99
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test 100
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 100
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group 100
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test 102
5.1.4 STEP 4: Select the Appropriate Statistical Test 102
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test 102
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test 103
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E 103
5.1.7.1 Finding the Degrees of Freedom (df) for the Two-Group t-Test 103
5.1.8 STEP 8: State the Result of Your Statistical Test 104
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! 104
5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis 105
5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis 106
5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30 109
5.2.1 An Example of Formula #1 for the Two-Group t-Test 110
5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30 117
5.4 End-of-Chapter Practice Problems 123
References 126
Chapter 6: Correlation and Simple Linear Regression 127
6.1 What Is a ``Correlation? ́ ́ 127
6.1.1 Understanding the Formula for Computing a Correlation 131
6.1.2 Understanding the Nine Steps for Computing a Correlation, r 132
6.2 Using Excel to Compute a Correlation Between Two Variables 134
6.3 Creating a Chart and Drawing the Regression Line onto the Chart 139
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points 141
6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart 145
6.3.1.2 Moving the Chart Below the Table in the Spreadsheet 147
6.3.1.3 Making the Chart ``Longer ́ ́ So That It Is ``Taller ́ ́ 148
6.3.1.4 Making the Chart ``Wider ́ ́ 148
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page 149
6.5 Finding the Regression Equation 152
6.5.1 Installing the Data Analysis ToolPak into Excel 152
6.5.1.1 Installing the Data Analysis ToolPak into Excel 2013 152
6.5.1.2 Installing the Data Analysis ToolPak into Excel 2010 153
6.5.1.3 Installing the Data Analysis ToolPak into Excel 2007 154
6.5.1.4 Installing the Data Analysis ToolPak into Excel 2003 154
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression 155
6.5.2.1 Finding the y-Intercept, a, of the Regression Line 158
6.5.2.2 Finding the Slope, b, of the Regression Line 158
6.5.3 Finding the Equation for the Regression Line 159
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value 159
6.6 Adding the Regression Equation to the Chart 160
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table 163
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet 163
6.8.1 Printing Only the Table and the Chart on a Separate Page 164
6.8.2 Printing Only the Chart on a Separate Page 164
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page 165
6.9 End-of-Chapter Practice Problems 165
References 171
Chapter 7: Multiple Correlation and Multiple Regression 173
7.1 Multiple Regression Equation 173
7.2 Finding the Multiple Correlation and the Multiple Regression Equation 176
7.3 Using the Regression Equation to Predict FIRST-YEAR GPA 180
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression 180
7.5 End-of-Chapter Practice Problems 184
References 189
Chapter 8: One-Way Analysis of Variance (ANOVA) 190
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) 192
8.2 How to Interpret the ANOVA Table Correctly 194
8.3 Using the Decision Rule for the ANOVA F-Test 195
8.4 Testing For the Difference Between Two Groups Using the ANOVA t-Test 196
8.4.1 Comparing Division B vs. Division C in Job Satisfaction Using the ANOVA t-Test 197
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test 198
8.4.1.2 Stating the Decision Rule for the ANOVA t-Test 198
8.4.1.3 Performing an ANOVA t-Test Using Excel Commands 199
8.5 End-of-Chapter Practice Problems 201
References 206
Appendices 207
Appendix A: Answers to End-of-Chapter Practice Problems 207
Appendix B: Practice Test 241
Appendix C: Answers to Practice Test 251
Appendix D: Statistical Formulas 261
Appendix E: t-Table 263
Index 264

This book shows how Microsoft Excel is able to teach human resource management statistics effectively. Similar to the previously published Excel 2010 for Human Resource Management Statistics, it is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical human resource management problems. If understanding statistics isnĺlt 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 human resource management courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2013 for Human Resource Management 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 human resource management problems. Practice problems are provided at the end of each chapter with their solutions in an Appendix. Includes 162 illustrations in color Suitable for undergraduate and graduate students At the beginning of his academic career, Prof. Tom J. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He then taught Social Psychology, Educational Psychology, General Psychology, Marketing, Management, and Accounting at Principia College, and is currently a Professor of Marketing in the George Herbert Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA) where he teaches Marketing Statistics, Marketing Research, and Pricing Strategies. He has written 60+ textbook supplements in Marketing and Management, published 20+ articles in professional journals, and presented 20+ papers at professional meetings. 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 M.B.A. from The University of Missouri-St. Louis. Prof. ĺlJ.P.ĺl Palmer-Schuyler is currently an Associate Professor of Human Resource Management in the Walker School of Business and Technology at Webster University in St. Louis, Missouri, USA, where she teaches undergraduate Human Resource Management as well as Organizational Behavior at the Masterĺls and Doctoral level. She received her MBA from the University of Nebraska-Lincoln and her Ph. D. from the University of Missouri-Columbia in Management. Her teaching awards include the Donald K. Anderson Graduate Student Teaching Award at the University of Missouri and the William T. Kemper Award at Webster University. She is also a graduate of the Program for Excellence in Teaching at the University of Missouri. Her pedagogical research over the past 12 years includes articles in Academy of Business Disciplines Journal and Regional Business Review, and she has made conference presentations at the Organizational Behavior Teaching Conference, Academy of Management, Society for Industrial and Organizational Psychology, Southwest Academy of Management, Western Academy of Management, and Society for Advancement of Management

Front Matter....Pages i-xvii
Sample Size, Mean, Standard Deviation, and Standard Error of the Mean....Pages 1-20
Random Number Generator....Pages 21-34
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing....Pages 35-65
One-Group t-Test for the Mean....Pages 67-81
Two-Group t-Test of the Difference of the Means for Independent Groups....Pages 83-110
Correlation and Simple Linear Regression....Pages 111-156
Multiple Correlation and Multiple Regression....Pages 157-173
One-Way Analysis of Variance (ANOVA)....Pages 175-191
Back Matter....Pages 193-252

2016-03-14