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May 2013
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Using Statistics in Compensation

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Overview

Overview : Compensation professionals use "descriptive statistics" to convey the characteristics of data used in the development and management of pay programs. 

In this webinar, David J. Wudyka will describe a series of statistical concepts used by Compensation practitioners. The concepts to be covered include ideas such as pay structure development; "control points" in pay ranges, including minimums, midpoints and maximums; weighted and unweighted averages; means, medians and modes; weighted and unweighted averages; regression and correlation analysis; standard deviations and data ranges; compa-ratios, and independent and dependent variables. All of these concepts will be explained in the context of their application in pay programs, including building a pay structure (i.e. sets of pay ranges), analyzing pay survey data, predicting base pay rates from one or more independent variables, making associations in pay data between independent and dependent variables, and using compa-ratios in merit pay programs and their budgeting. 

Why should you attend: Participants in this program will be able to: 

  • Apply a wide range of statistical concepts to their Compensation programs
  • Build a pay structure that is statistically sound
  • Make an informed decision about whether to use weighted averages or medians in the development of their pay structures
  • Apply control points effectively in pay range development
  • Learn how to predict Executive base pay rates from one independent variable
  • Lean about the importance of measures of central tendency, and how they are applied in pay program analysis
  • How one statistical measure can be used to analyze pay survey data quality
  • Why on-line pay data may not be appropriate for use in pay data analysis


Who Will Benefit:

  • Human Resource Managers
  • Compensation Analysts
  • Compensation Managers
  • Financial Managers of HR Departments

 

Price: $145.00
Contact:
Russel Stuart
Phone: 1800-385-1627
E-Mail: webinars@trainhr.com
Registration link: http://bit.ly/ZzLBYV

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