This book shows the capabilities of Microsoft Excel in teaching human resource management statistics effectively. Similar to the previously published __Excel 2013 for Human Resource Management Statistics__, this book 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. However, __Excel 2016 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. 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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nexusstc/Excel 2016 for Human Resource Management Statistics: A Guide to Solving Practical Problems/2edced10c3131f8bd766a023bb430ee5.pdf

scihub/10.1007/978-3-319-40063-1.pdf

zlib/Mathematics/Thomas J. Quirk, Julie Palmer-Schuyler (auth.)/Excel 2016 for Human Resource Management Statistics: A Guide to Solving Practical Problems_2803292.pdf

Quirk, Thomas J., Palmer-Schuyler, Julie

Adobe InDesign CC 2015 (Windows)

Springer Nature Switzerland AG

Springer London, Limited

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

Excel for statistics, Switzerland :, 2016

Place of publication not identified, 2016

Excel for statistics, Cham, 2016

Switzerland, Switzerland

1st ed. 2016, 2016

sm59985756

producers:
Adobe PDF Library 15.0

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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 22
1.4.1 Using the Fill/Series/Columns Commands 22
1.4.2 Changing the Width of a Column 24
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 36
References 39
Chapter 2: Random Number Generator 40
2.1 Creating Frame Numbers for Generating Random Numbers 40
2.2 Creating Random Numbers in an Excel Worksheet 44
2.3 Sorting Frame Numbers into a Random Sequence 45
2.4 Printing an Excel File So That All of the Information Fits onto One Page 49
2.5 End-of-Chapter Practice Problems 52
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 TIME TO FILL 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 TIME TO FILL 59
3.2 Hypothesis Testing 67
3.2.1 Hypotheses Always Refer to the Population That You Are Studying 68
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis 69
3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used 69
3.2.3 The 7 Steps for Hypothesis-testing Using the Confidence Interval About the Mean 72
3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 73
3.2.3.2 STEP 2: Select the Appropriate Statistical Test 73
3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test 73
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,... 74
3.2.3.5 STEP 5: Decide on a Decision Rule 74
3.2.3.6 STEP 6: State the Result of Your Statistical Test 74
3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 74
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test 79
3.3.1 Different Ways to Accept the Null Hypothesis 80
3.3.2 Different Ways to Reject the Null Hypothesis 80
3.4 End-of-Chapter Practice Problems 80
References 86
Chapter 4: One-Group t-Test for the Mean 87
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test 87
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 88
4.1.2 STEP 2: Select the Appropriate Statistical Test 88
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test 88
4.1.3.1 Finding the Absolute Value of a Number 89
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test 89
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E 90
4.1.6 STEP 6: State the Result of Your Statistical Test 91
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 92
4.2 One-Group t-Test for the Mean 92
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? 98
4.4 End-of-Chapter Practice Problems 98
References 102
Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups 103
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test 104
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 104
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group 104
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test 106
5.1.4 STEP 4: Select the Appropriate Statistical Test 106
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test 106
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test 107
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E 107
5.1.7.1 Finding the Degrees of Freedom (df) for the Two-Group t-Test 107
5.1.8 STEP 8: State the Result of Your Statistical Test 108
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! 108
5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis 109
5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis 110
5.2 Formula #1: Both Groups Have A Sample Size Greater Than 30 113
5.2.1 An Example of Formula #1 for the Two-Group t-Test 114
5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30 121
5.4 End-of-Chapter Practice Problems 128
References 131
Chapter 6: Correlation and Simple Linear Regression 132
6.1 What Is a ``Correlation? ́ ́ 132
6.1.1 Understanding the Formula for Computing a Correlation 137
6.1.2 Understanding the Nine Steps for Computing a Correlation, r 137
6.2 Using Excel to Compute a Correlation Between Two Variables 139
6.3 Creating a Chart and Drawing the Regression Line onto the Chart 144
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points 146
6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart 150
6.3.1.2 Moving the Chart Below the Table in the Spreadsheet 152
6.3.1.3 Making the Chart ``Longer ́ ́ so That It Is ``Taller ́ ́ 153
6.3.1.4 Making the Chart ``Wider ́ ́ 153
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page 155
6.5 Finding the Regression Equation 157
6.5.1 Installing the Data Analysis ToolPak into Excel 157
6.5.1.1 Installing the Data Analysis ToolPak into Excel 2016 157
6.5.1.2 Installing the Data Analysis ToolPak into Excel 2013 158
6.5.1.3 Installing the Data Analysis ToolPak into Excel 2010 159
6.5.1.4 Installing the Data Analysis ToolPak into Excel 2007 160
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression 160
6.5.2.1 Finding the y-Intercept, a, of the Regression Line 164
6.5.2.2 Finding the Slope, b, of the Regression Line 164
6.5.3 Finding the Equation for the Regression Line 165
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value 165
6.6 Adding the Regression Equation to the Chart 166
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table 169
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet 169
6.8.1 Printing Only the Table and the Chart on a Separate Page 170
6.8.2 Printing Only the Chart on a Separate Page 170
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page 171
6.9 End-of-Chapter Practice Problems 171
References 178
Chapter 7: Multiple Correlation and Multiple Regression 179
7.1 Multiple Regression Equation 179
7.2 Finding the Multiple Correlation and the Multiple Regression Equation 182
7.3 Using the Regression Equation to Predict FIRST-YEAR GPA 187
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression 187
7.5 End-of-Chapter Practice Problems 191
References 196
Chapter 8: One-Way Analysis of Variance (ANOVA) 197
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) 199
8.2 How to Interpret the ANOVA Table Correctly 202
8.3 Using the Decision Rule for the ANOVA F-Test 203
8.4 Testing for the Difference Between Two Groups Using the ANOVA t-Test 204
8.4.1 Comparing Division B vs. Division C in Job Satisfaction Using the ANOVA t-Test 204
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test 205
8.4.1.2 Stating the Decision Rule for the ANOVA t-Test 206
8.4.1.3 Performing an ANOVA t-Test Using Excel Commands 206
8.5 End-of-Chapter Practice Problems 209
References 214
Appendices 215
Appendix A: Answers to End-of-Chapter Practice Problems 215
Appendix B: Practice Test 247
Appendix C: Answers to Practice Test 258
Appendix D: Statistical Formulas 268
Appendix E: t-Table 270
Index 271

This Book Shows The Capabilities Of Microsoft Excel In Teaching Human Resource Management Statistics Effectively. Similar To The Previously Published Excel 2013 For Human Resource Management Statistics, This Book 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.^ However, Excel 2016 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. Separately, There Is A Full Practice Test (with Answers In An Appendix) That Allows Readers To Test What They Have Learned. Includes 162 Illustrations In Color Suitable For Undergraduate And Graduate Students At The Beginning Of His Academic Career, Prof. Quirk Spent Six Years In Educational Research At The American Institutes For Research And Educational Testing Service.^ He Is Currently A Professor Of Marketing In The Walker School Of Business & Technology At Webster University Based 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 M.b.a. From The University Of Missouri-st. Louis. Prof. “j.p.” 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 And Organizational Behavior. She Received Her Mba From The University Of Nebraska-lincoln And Her Ph.d. From The University Of Missouri-columbia In Management. She Has Published Articles In Academy Of Business Disciplines Journal And Regional Business Review, And She Has Made Conference Presentations At The Academy Of Management And Society For Advancement Of Management. Introduction -- Sample Size, Mean, Standard Deviation, Standard Error Of The Mean -- Random Number Generator -- Confidence Interval About The Mean Using The Tinv Function And Hypothesis Testing -- One-group T-test For The Mean -- Two-group T-test Of The Difference Of The Means For Independent Groups -- Correlation And Simple Linear Regression -- Multiple Correlation And Multiple Regression -- One-way Analysis Of Variance (anova) -- Appendix A -- Appendix B -- Appendix C -- Appendix D -- Appendix E -- Index. By Thomas J. Quirk, Julie Palmer-schuyler.

This book shows the capabilities of Microsoft Excel in teaching human resource management statistics effectively. Similar to the previously published Excel 2013 for Human Resource Management Statistics, this book 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. However, Excel 2016 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. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. Includes 162 illustrations in color Suitable for undergraduate and graduate students At the beginning of his academic career, Prof. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He is currently a Professor of Marketing in the Walker School of Business & Technology at Webster University based 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 M.B.A. from The University of Missouri-St. Louis. Prof. zJ. P.y 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 and Organizational Behavior. She received her MBA from the University of Nebraska-Lincoln and her Ph. D. from the University of Missouri-Columbia in Management. She has published articles in Academy of Business Disciplines Journal and Regional Business Review, and she has made conference presentations at the 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 1-21
Random Number Generator....Pages 23-36
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing....Pages 37-69
One-Group t-Test for the Mean....Pages 71-86
Two-Group t-Test of the Difference of the Means for Independent Groups....Pages 87-115
Correlation and Simple Linear Regression....Pages 117-163
Multiple Correlation and Multiple Regression....Pages 165-182
One-Way Analysis of Variance (ANOVA)....Pages 183-200
Back Matter....Pages 201-258

2016-11-20