GRP – C3E: Quantitative Principles in Compensation Management (originally GR2)

Quantitative Principles in Compensation Management (Certification Exam C3E)

Master HR statistics with Excel. This course focuses on general quantitative concepts, basic statistical tools and the mathematics of compensation design and administration. You will learn how to consider data from numerous sources with an emphasis on problem solving and decision making

• Learn basic quantitative concepts and the four levels of measurement.
• Examine how to define and compare percents, market index and compa-ratios.
• Study the time value of money - including compound interest and the compound salary growth rate.
• Find out how to collect, analyse and accurately display statistical data.
• Learn how to determine central tendency and measures of central location.
• Discuss measures of variability.
• Gain an understanding of modeling and regression analysis.

What You Will Learn

Statistics - Data, Information and Levels of Measurement
• Why collect and use data
• Five key questions to ask about the variable of interest
• Levels of measurement

Percents and Related Issues
• Percents
•Compa-ratio (individual and department)
• Market index
• Percent difference
• Developing salary ranges

Time Value of Money
• Present and future value
• Compound interest and compound salary growth rate
• Constant midpoint progression
• Annuity payments

Statistics - Collecting, Organising, Grouping and Displaying Data
• Populations and samples
• Frequency distributions

Statistics 一 Lying with Statistics, Graphs and Displays
• Recognising distorted data
• Avoiding mistakes that distort data

Statistics - Measures of Central Tendency and/or Location
• Measures of central tendency
• Measures of location
• Percentile bar

Statistics - Shapes of Distributions
• Interpreting distributions
• Normal distribution

Regression Analysis
• Regression models In a compensation environment
• Developing a regression model
• Cautions in the interpretation of correlations
• Multiple regression

Measures of Variability
• Measures of variability
• Z-scores