An insightful, hands-on focus on the statistical methods used by compensation and human resources professionals in their everyday work Across various industries, compensation professionals work to organize and analyze aspects of employment that deal with elements of pay, such as deciding base salary, bonus, and commission provided by an employer to its employees for work performed. Acknowledging the numerous quantitative analyses of data that are a part of this everyday work, Statistics for Compensation provides a comprehensive guide to the key statistical tools and techniques needed to perform those analyses and to help organizations make fully informed compensation decisions. This self-contained book is the first of its kind to explore the use of various quantitative methods--from basic notions about percents to multiple linear regression--that are used in the management, design, and implementation of powerful compensation strategies. Drawing upon his extensive experience as a consultant, practitioner, and teacher of both statistics and compensation, the author focuses on the usefulness of the techniques and their immediate application to everyday compensation work, thoroughly explaining major areas such as: * Frequency distributions and histograms * Measures of location and variability * Model building * Linear models * Exponential curve models * Maturity curve models * Power models * Market models and salary survey analysis * Linear and exponential integrated market models * Job pricing market models Throughout the book, rigorous definitions and step-by-step procedures clearly explain and demonstrate how to apply the presented statistical techniques. Each chapter concludes with a set of exercises, and various case studies showcase the topic's real-world relevance. The book also features an extensive glossary of key statistical terms and an appendix with technical details. Data for the examples and practice problems are available in the book and on a related FTP site. Statistics for Compensation is an excellent reference for compensation professionals, human resources professionals, and other practitioners responsible for any aspect of base pay, incentive pay, sales compensation, and executive compensation in their organizations. It can also serve as a supplement for compensation courses at the upper-undergraduate and graduate levels.
Autorentext
JOHN H. DAVIS, PhD, is a Certified Compensation Professional and President of Davis Consulting, where he has consulted on salary surveys, statistics, base pay programs, incentive programs, and performance management programs for numerous Fortune 1000size organizations. He has taught undergraduate and graduate statistics courses and, for the past three decades, has taught thousands of compensation and human resources professionals statistics and its application to common problems in their fields.
Inhalt
Preface xiii
Chapter 1 Introduction 1
1.1 Why do Statistical Analysis? 2
Example Analysis 3
1.2 Statistics 5
1.3 Numbers Raise Issues 6
1.4 Behind Every Data Point, There Is a Story 8
1.5 Aggressive Inquisitiveness 9
1.6 Model Building Framework 9
Example Model 10
1.7 Data Sets 10
1.8 Prerequisites 11
Chapter 2 Basic Notions 13
2.1 Percent 14
Graphical Displays of Percents 16
2.2 Percent Difference 21
2.3 Compound Interest 23
Future Value 24
Present Value 26
Translating 27
Practice Problems 28
Chapter 3 Frequency Distributions and Histograms 31
3.1 Definitions and Construction 41
Rules for Categories 43
3.2 Comparing Distributions 48
Absolute Comparison and Relative Comparison 48
Comparing More Than Two Distributions 50
3.3 Information Loss and Comprehension Gain 51
3.4 Category Selection 51
3.5 Distribution Shapes 54
Uniform Distribution 55
Bell-Shaped Distribution 55
Normal Distribution 56
Skewed Distribution 59
Bimodal Distribution 60
Practice Problems 62
Chapter 4 Measures of Location 67
4.1 Mode 67
4.2 Median 68
4.3 Mean 70
4.4 Trimmed Mean 73
4.5 Overall Example and Comparison 73
Comparison 75
4.6 Weighted and Unweighted Average 76
Which Measure to Use? 78
Application of Weighted Averages to Salary Increase Guidelines 80
4.7 Simpson's Paradox 82
4.8 Percentile 85
Reverse Percentile 88
4.9 Percentile Bars 90
Practice Problems 92
Chapter 5 Measures of Variability 95
5.1 Importance of Knowing Variability 95
5.2 Population and Sample 96
Examples of Populations 96
Examples of Samples and Populations 96
5.3 Types of Samples 97
5.4 Standard Deviation 98
Interpretations and Applications of Standard Deviation 100
5.5 Coefficient of Variation 107
Interpretations and Applications of Coefficient of Variation 108
5.6 Range 109
Interpretations and Applications of Range 109
5.7 P90/P10 110
Interpretations and Applications of P90/P10 111
5.8 Comparison and Summary 112
Practice Problems 115
Chapter 6 Model Building 119
6.1 Prelude to Models 119
6.2 Introduction 120
6.3 Scientific Method 122
6.4 Models 123
6.5 Model Building Process 126
Plotting Points 128
Functional Forms 132
Method of Least Squares 136
Practice Problems 138
Chapter 7 Linear Model 141
7.1 Examples 141
7.2 Straight Line Basics 143
Interpretations of Intercept and Slope 144
Using the Equation 145
7.3 Fitting the Line to the Data 147
What We Are Predicting 148
Interpretations of Intercept and Slope 149
7.4 Model Evaluation 149
Appearance 150
Coefficient of Determination 150
Correlation 152
Standard Error of Estimate 154
Common Sense 154
7.5 Summary of Interpretations and Evaluation 155
7.6 Cautions 155
7.7 Digging Deeper 158
7.8 Keep the Horse before the Cart 160
Practice Problems 164
Chapter 8 Exponential Model 167
8.1 Examples 167
8.2 Logarithms 168
Antilogs 170
Scales 170
Why Logarithms? 171
8.3 Exponential Model 172
8.4 Model Evaluation 176
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