Statistics for Compensation
Statistics for Compensation

Author: John H. Davis

Publisher: John Wiley & Sons

Published: 2011-08-24

Total Pages: 414

ISBN-13: 1118002067

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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.

Collecting Compensation Data from Employers
Collecting Compensation Data from Employers

Author: National Research Council

Publisher: National Academies Press

Published: 2013-03-01

Total Pages: 129

ISBN-13: 0309264111

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U.S. agencies with responsibilities for enforcing equal employment opportunity laws have long relied on detailed information that is obtained from employers on employment in job groups by gender and race/ethnicity for identifying the possibility of discriminatory practices. The U.S. Equal Employment Opportunity Commission (EEOC), the Office of Federal Contract Compliance programs of the U.S. Department of Labor, and the Civil Rights Division of the U.S. Department of Justice have developed processes that use these employment data as well as other sources of information to target employers for further investigation and to perform statistical analysis that is used in enforcing the anti-discrimination laws. The limited data from employers do not include (with a few exceptions) the ongoing measurement of possible discrimination in compensation. The proposed Paycheck Fairness Act of 2009 would have required EEOC to issue regulations mandating that employers provide the EEOC with information on pay by the race, gender, and national origin of employees. The legislation was not enacted. If the legislation had become law, the EEOC would have been required to confront issues regarding currently available and potential data sources, methodological requirements, and appropriate statistical techniques for the measurement and collection of employer pay data. The panel concludes that the collection of earnings data would be a significant undertaking for the EEOC and that there might be an increased reporting burden on some employers. Currently, there is no clearly articulated vision of how the data on wages could be used in the conduct of the enforcement responsibilities of the relevant agencies. Collecting Compensation Data from Employers gives recommendations for targeting employers for investigation regarding their compliance with antidiscrimination laws.

The WorldatWork Handbook of Compensation, Benefits and Total Rewards
The WorldatWork Handbook of Compensation, Benefits and Total Rewards

Author: WorldatWork

Publisher: John Wiley & Sons

Published: 2015-03-05

Total Pages: 864

ISBN-13: 1119104335

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Praise for The WorldatWork Handbook of Compensation, Benefits & Total Rewards This is the definitive guide to compensation and benefits for modern HR professionals who must attract, motivate, and retain quality employees. Technical enough for specialists but broad in scope for generalists, this well-rounded resource belongs on the desk of every recruiter and HR executive. An indispensable tool for understanding and implementing the total rewards concept, the WorldatWork Handbook of Compensation, Benefits, and Total Rewards is the key to designing compensation practices that ensure organizational success. Coverage includes: Why the total rewards strategy works Developing the components of a total rewards program Common ways a total rewards program can go wrong Designing and implementing a total rewards program Communicating the total rewards vision Developing a compensation philosophy and package FLSA and other laws that affect compensation Determining and setting competitive salary levels And much more

Quarterly Publications of the American Statistical Association
Quarterly Publications of the American Statistical Association

Author: American Statistical Association

Publisher:

Published: 1918

Total Pages: 898

ISBN-13:

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A scientific and educational journal not only for professional statisticians but also for economists, business executives, research directors, government officials, university professors, and others who are seriously interested in the application of statistical methods to practical problems, in the development of more useful methods, and in the improvement of basic statistical data.

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)
Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)

Author: Cheng Few Lee

Publisher: World Scientific

Published: 2020-07-30

Total Pages: 5053

ISBN-13: 9811202400

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This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.