Statistics for Compensation
A Practical Guide to Compensation Analysis
Published on 7. February 2011
456 pages
978-0-470-94641-1 (ISBN)
Description
An insightful, hands-on focus on the statistical methods used bycompensation and human resources professionals in their everydaywork
Across various industries, compensation professionals work toorganize and analyze aspects of employment that deal with elementsof pay, such as deciding base salary, bonus, and commissionprovided by an employer to its employees for work performed.Acknowledging the numerous quantitative analyses of data that are apart of this everyday work, Statistics for Compensation provides acomprehensive guide to the key statistical tools and techniquesneeded to perform those analyses and to help organizations makefully informed compensation decisions.
This self-contained book is the first of its kind to explore theuse of various quantitative methods--from basic notions aboutpercents to multiple linear regression--that are used in themanagement, design, and implementation of powerful compensationstrategies. Drawing upon his extensive experience as a consultant,practitioner, and teacher of both statistics and compensation, theauthor focuses on the usefulness of the techniques and theirimmediate application to everyday compensation work, thoroughlyexplaining 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-stepprocedures clearly explain and demonstrate how to apply thepresented statistical techniques. Each chapter concludes with a setof exercises, and various case studies showcase the topic'sreal-world relevance. The book also features an extensive glossaryof key statistical terms and an appendix with technical details.Data for the examples and practice problems are available in thebook and on a related FTP site.
Statistics for Compensation is an excellent reference forcompensation professionals, human resources professionals, andother practitioners responsible for any aspect of base pay,incentive pay, sales compensation, and executive compensation intheir organizations. It can also serve as a supplement forcompensation courses at the upper-undergraduate and graduatelevels.
Reviews / Votes
"As an experienced compensation manager for a publiclytraded Fortune 500 company, I have found this book to be anall-inclusive, highly useful and infor-mative desk reference.It certainly has been extremely valuable in helping me tocontribute to successful strategic decisions at mycompany." (Workspan, 1 January 2013)"The book can serve as a text for students specializing incompensation or human resources, or as a reference forpractitioners. He provides worked examples throughout." (Booknews,1 June 2011)More details
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Book
04/2011
Wiley
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02/2011
Wiley
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Person
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 1000-size 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.
Content
Preface.
Chapter 1 Introduction.
1.1 Why Do Statistical Analysis?
1.2 Statistics.
1.3 Numbers Raise Issues.
1.4 Behind Every Data Point, There is a Story.
1.5 Aggressive Inquisitiveness.
1.6 Model Building Framework.
1.7 Data Sets.
1.8 Prerequisites.
Chapter 2 Basic Notions.
2.1 Percent.
2.2 Percent Difference.
2.3 Compound Interest.
Practice Problems.
Chapter 3 Frequency Distributions and Histograms.
3.1 Definitions and Construction.
3.2 Comparing Distributions.
3.3 Information Loss and Comprehensive Gain.
3.4 Category Selection.
3.5 Distribution Shapes.
Practice Problems.
Chapter 4 Measures of Location.
4.1 Mode.
4.2 Median.
4.3 Mean.
4.4 Trimmed Mean.
4.5 Overall Example and Comparison.
4.6 Weighted and Unweighted Average.
4.7 Simpson's Paradox.
4.8 Percentile.
4.9 Percentile Bars.
Practice Problems.
Chapter 5 Measures of Variability.
5.1 Importance of Knowing Variability.
5.2 Population and Sample.
5.3 Types of Samples.
5.4 Standard Deviation.
5.5 Coefficient f Variation.
5.6 Range.
5.7 P90/P10.
5.8 Comparison and Summary.
Practice Problems.
Chapter 6 Model Building.
6.1 Prelude to Models.
6.2 Introduction.
6.3 Scientific Method.
6.4 Models.
6.5 Model Building Process.
Practice Problems.
Chapter 7 Linear Model.
7.1 Examples.
7.2 Straight Line Basics.
7.3 Fitting the Line to the Data.
7.4 Model Evaluation.
7.5 Summary of Interpretations and Evaluation.
7.6 Cautions.
7.7 Digging Deeper.
7.8 Keep the Horse Before the Cart.
Practice Problems.
Chapter 8 Exponential Model.
8.1 Examples.
8.2 Logarithms.
8.3 Exponential Model.
8.4 Model Evaluation.
Practice Problems.
Chapter 9 Maturity Curve Model.
9.1 Maturity Curves.
9.2 Building the Model.
9.3 Comparison of Models.
Practice Problems.
Chapter 10 Power Model.
10.1 Building the Model.
10.2 Model Evaluation.
Practice Problems.
Chapter 11 Market Models and Salary Survey Analysis.
11.1 Introduction.
11.2 Commonalities of Approaches.
11.3 Final Market-Based Salary Increase Budget.
11.4 Other Factors Influencing the Final Salary Increase Budget Recommendation.
11.5 Salary Structure.
Practice Problems.
Chapter 12 Integrated Market Model - Linear.
12.1 Gather Market Data.
12.2 Age Data to a Common Date.
12.3 Create an Integrated Market Model Interpretations.
12.4 Compare Employee Pay with Market Model.
Practice Problems.
Chapter 13 Integrated Market Model - Exponential.
Practice Problems.
Chapter 14 Integrated Market Model - Maturity Curve.
Practice Problems.
Chapter 15 Job Pricing Market Model - Group of Jobs.
Practice Problems.
Chapter 16 Job Pricing Market Model - Power Model.
Practice Problems.
Chapter 17 Multiple Linear Regression.
17.1 What It Is.
17.2 Similarities and Differences with Simple Linear Regression.
17.3 Building the Model.
17.4 Model Evaluation.
17.5 Mixed Messages in Evaluating a Model.
17.6 Summary of Regressions.
17.7 Digging Deeper.
Practice Problems.
Appendix.
A.1 Value Exchange Theory.
A.2 Factors Determining a Person's Pay.
A.3 Types of Numbers.
A.4 Significant Figures.
A.5 Scientific Notation.
A.6 Accuracy and Precision.
A.7 Compound Interest - Additional.
A.8 Rule of 72.
A.9 Normal Distribution.
A.10 Linear Regression Technical Note.
A.11 Formulas for Regression Terms.
A.12 Logarithmic Conversion.
A.13 Range Spread Relationships.
A.14 Statistical Inference in Regression.
A.15 Additional Multiple Linear Regression Topics.
Glossary.
References.
Answers to Practice Problems.
Index.
