# Mean, Median, Mode

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Mean, median, and mode are differing values that furnish information regarding a set of observations. The mean is used when one desires to determine the average value for data ranked in intervals. The median is used to learn the middle of graded information, and the mode is used to summarize non-numeric data.
The mean is equal to the amount of all the data in a set divided by the number of values in that set. It is typically used with continuous figures. The result will probably not be one of the values in the data set, but is a representation of all those values. In other words, if I want to find the mean salary at a particular company, I would add together all the salaries and divide by the total number of salaries added: \$50,000 + \$56,000 + \$54,500 = \$53,500.
The problem with mean figures is they are easily slanted by one figure that stands far above or below the others. In the previous example, if I have three annual salaries of \$50,000, \$56,000, and \$54,500, and then the company president’s salary of \$260,000, I will derive an average salary of \$105,125. This mean is double the actual salaries of the lower paid workers. In this case it would be more appropriate to find the median salary. To find the median salary in the previous example, we arrange the data according to value: \$50,000, \$54,500, \$56,000, and \$260,000 and find the middle which would be \$55,250.
If I wanted to know the breakdown of salaries in the company, I would use mode. Using this method, I could compile data that reveals of the four persons working at the company, two earn \$46,000 to \$55,000; one earns \$56,000 to \$65,000; and one earns above \$66,000. Using mode, we could also measure how many of the four employees belong to a particular gender, race, and so

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