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WorldatWork Updated C3E Exam Blueprint, Syllabus and Topics

Quantitative Principles in Compensation Management

Last Update May 18, 2024
Total Questions : 54

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WorldatWork C3E Exam Overview :

Exam Name Quantitative Principles in Compensation Management
Exam Code C3E
Exam Registration Price $2200
Official Information https://www.worldatwork.org/product/certification/Quantitative-Principles-in-Compensation-Management
See Expected Questions WorldatWork C3E Expected Questions in Actual Exam
Take Self-Assessment Use WorldatWork C3E Practice Test to Assess your preparation - Save Time and Reduce Chances of Failure

Worldatwork C3E Exam Topics :

Section Weight Objectives
Statistics: Data, Information and Levels of Management  
  • Discover why HR professionals collect and use data and learn key questions to ask about the variable of interest. Learn about the levels of measurement.
Percents and Related Issues  
  • Dive into percents, individual compa-ratio, department compa-ratio, market index, percent difference, developing salary ranges and percents in compensation management.
Time Value of Money  
  • Understand how the time value of money is directly related to compensation, along with present and future value, compound interest and compound salary growth rate, constant midpoint progression and annuity payments.
Statistics: Collecting, Organizing, Grouping and Displaying Data  
  • Learn about populations and samples as well as frequency distributions, including how to organize group and display data.
Statistics: Lying with Statistics, Graphs and Displays  
  • Recognize distorted data and commonly used mistakes that distort data.
Statistics: Measure of Central Tendency and/or Location  
  • Gain insights on measures of central tendency, measures of location and percentile bars.
Measure of Variability  
  • Understand measure of variability including range, interquartile range and standard deviation. Also learn about z-scores, including 2-sigma and 3-sigma rules.
Statistics: Shapes of Distributions  
  • Interpret distributions of data and understand the application (both good and poor) of normal distribution.
Regression Analysis  
  • Learn about regression models within the compensation environment, how to develop a regression model, cautions in the interpretation of correlations and multiple regression.

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