Fundamentals of Compensation Quantitative Methods

SUMMARY

Human Resources administration requires the day-to-day use of many quantitative methods.

Basic Mathematical Operations

In planning and administering salary and benefit programs, you will often use addition and subtraction. But beware, these two functions are the sources of most computation errors.

Subtraction is the inverse of addition, just as division is the inverse of multiplication. Always remember to perform multiplication and division first in your math equations, unless parentheses indicate a sub-operation should take precedence or exponents or square roots need to be calculated (after any sub-operations in parentheses).

Types of Measurements

Different types of measurement systems are appropriate to different Human Resources tasks.

• Nominal measurements: These are scales used to identify items. No useful mathematical computations can be performed with these types of measurements. In fact, these types of numbers could be replaced with letters or symbols. Social Security numbers, zip codes, and names are examples.
• Ordinal measurements: These are used for ranking qualitatively, not quantitatively. For example, you might rank employees as 1^st, 2^nd, and 3^rd in sales performance, but that would NOT mean Salesperson #3 sold 1/3 as much as Salesperson #1.
• Interval measurements: This type of ranking uses an equal-unit scale. The distance between two units on an interval scale are equal, even if the numbers on the scale are not equally spaced. The following salesperson commission scale is an example.
  
  

  SALES ($)	BROKER'S COMMISSION ($)	SALES COMMISSION ($)
  20,000	0	0
  40,000	500	300
  60,000	1,500	900
  120,000	4,500	2,700

• Ratio measurements: These use a scale with an absolute zero, below which no value can be assigned.

Quantitative Tools

You'll use these measurement types to make comparisons. Percentages and percentiles are also useful, as are graphical representations of HR data. In this course, you reviewed how to draw line graphs and calculate points on a line, given any two other points.

Surveys

As part of your Human Resources operations, you may wish to conduct surveys to gather data. For example, you may wish to survey your employees to find out what additional benefit would best motivate them. You could survey all employees (the entire population) OR just take a sample. Random sampling assures that no single observation selected for inclusion in the sample is favored over any other observation. Each observation in the population has an equal chance of being included in the sample. When one or another observation is favored for inclusion in the sample, the sample is no longer considered random and is NOT representative of the population. It is then said to be biased.A good sample will have zero or low bias and a quantifiable degree of random error.

Histograms

After you've collected your data, you need to analyze it. Histograms let you view the center and variation in a dataset. They show you distribution of the data and outliers, observations that lie far from the main body of the distribution.

Statistical Tests

After analyzing your data, you must test any conclusions you have drawn. Statistical tests let you deduce reality from a limited amount of data. They allow you to test hypotheses through the use of a null hypothesis. Here you try to disprove what you want to prove. For example, if you wish to prove that women work more overtime than men, then you'd use the following null hypotheses. "No difference exists between amount of overtime worked by men and women."

Future Courses

Now that you have completed this course on basic quantitative methods, you're ready for the following intermediate and advanced courses in this series:

• DLC Course 19: Quantitative Methods Used in Salary Administration
• DLC Course 49: Regression Analysis Used in Compensation Administration

For more information on how to conduct your own survey, please see DLC Course 73: Analyzing Salary Surveys.