The use of weighted averages is common in many different applications, especially in the fields of accounting and various tasks that involve analysis and mathematical evaluations. Essentially a weighted average involves the assignment of different levels of importance or weights to various components that are used to arrive at a final answer or solution to a question or problem. This is in contrast to the practice of assigning a common mean value to each component that is relevant to the task at hand.
One of the easiest ways to understand the concept of a weighted average is to look at a common grading model used in many schools and colleges. At the discretion of the instructor, different types of work performed by the student will be assigned a value that will help determine the final grade earned for the course. Successful completion of homework assignments may account for a smaller percentage of the total grade, while one or two major tests may carry additional weight in the final grade earned. This concept of proportional relevance means that in the greater scheme of things, the tests carry more importance in making a good grade for the course, although the successful completion of both components will ensure earning the highest grade.
This same principle of a weighted average can be applied in other venues as well. Marketing strategists may develop a campaign that is aimed at primary and secondary consumer markets. While the main thrust of the campaign is directly relevant to the primary market, the same techniques are anticipated to be relevant to lesser degree to other markets. The result is a projection of revenue earned primarily from one sector of the consumer market, but still accounting for smaller percentages of revenue from one or more smaller sectors.
A weighted average is somewhat subjective, in that the individual or entity who sets the values for each component involved in the average usually does so with some preconceived ideas about those values. However, it is possible to adjust the criteria used for calculating a weighted average as more facts emerge that could impact the relative value of each component.
