This basic-level course focuses on general quantitative concepts, basic statistical tools,
the mathematics of total compensation design and administration, mathematical modeling, and
regression analysis. Participants learn 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
• Understand 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, analyze and accurately display statistical data
• Learn how to determine central tendency and measures of central location
• Discuss measures of variability
• Explore shapes of distribution
• Gain an understanding of modeling and regression analysis

Who Should Attend
This course is intended for those individuals who are relatively new to the field as well as experienced practitioners who seek a basic treatment for applying statistics in total compensation management. It is assumed that they have had no formal exposure to statistics, but have taken a basic algebra course.

What You Will Learn

Statistics—Data, Information and Levels of Measurement

• Why HR professionals collect and use data
• Five key questions to ask about the variable of interest
• Levels of measurement

Percents and Related Issues

• Percents
• Individual compa-ratio
• Department compa-ratio
• Market index
• Percent difference
• Developing salary ranges
• Percents in benefits management

Time Value of Money

• Compound interest and compound salary growth rate
• Constant midpoint progression
• Annuity payments

Statistics—Collecting, Organizing, Grouping and Displaying Data

• Populations and samples
• Frequency distributions
• Organize, group and
• display data

Statistics—Lying with Statistics, Graphs and Displays

• Recognizing distorted data
• Mistakes that distort data

Statistics— Measures of Central Tendency and/or Location

• Measures of central tendency
• Measures of location
• Percentile bars

Measures of Variability

• Range
• Interquartile range
• Standard deviation
• Z-scores

Statistics— Shapes of Distributions

• Interpreting distributions
• Normal distribution

Regression Analysis

• Regression models in an HR environment
• Developing a regression model
• Cautions in the interpretation of correlations
• Multiple regression