What Is a Weighted Salary Average?
Weighted averages are used by both employers and surveyors determining average salary information in order to give a more accurate salary representation than a typical average salary.
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Benefits
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Policy makers use weighted average salaries to see disparities in salaries among employees. It gives a more accurate salary figure since it eliminates biases in information by giving all workers equal weight in determining an average salary figure. This also gives a more complete picture of total compensation since it typically includes benefits.
Weighted Averages
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Weighted averages are determined by summing all salaries and dividing by the number of incumbents so every worker is given equal treatment. Therefore, every salary has equal weight in the average to give a more accurate representation and eliminate disparities in salary surveys caused by differences in experience and training from the various employers.
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Example: Intro
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For example, take two companies: Company A and Company B. Company A employs 10 workers who are each paid $30,000 per year. Company B on the other hand employs 1,000 workers who each earn $25,000 a year.
Example: Average
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The true average of the companies would be $27,500 since $30,000 plus $25,000 divided by two is $27,500. This however does not give an accurate representation of the market since Company B employs so many more workers than Company A. An accurate figure, therefore should place more emphasis on the average salary of Company B.
Example: Weighted Average
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For a more accurate representation of the market, it is a good idea to take the weighted average. To do so, multiply the number of workers in each firm by the firm for that salary. Then all these figures together and divide by the total number of workers. For example, in this example, multiply $30,000 by 10 ($300,000) and $25,000 by 1000 ($25,000,000). Add these figures together ($25,300,000). Then divide by the total number of workers, which in this example is 1,010. This yields the weighted average of $25,050 which is much different and significantly more accurate than $27,500.
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References
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