Measures of Central Tendency
Measures of Central Tendency
1. What Do You Mean by Mean?
a) The mean of the salaries is calculated by adding up each individual salary and dividing it by the seven employees. The mean of the seven salaries is $43,814.29. The mean compares to the individual salaries because it shows the average of all the salaries together. The employees would use the average to negotiate with Dick for a higher salary, because by looking at the average you can see that Dick’s salary is an outlier compared to the mean.
b) The median of these seven salaries is $23,500. I got the median by first putting the numbers in order. Since it is an odd amount of numbers, I just find the center of the data after they were in order. This value does not really compare to all of the individual salaries; it has no relation other then it is just in the center. Dick’s salary does not compare to the median because it is the outlier, but mostly everyone else’s does because it is around the same amount.
c) The mean gives a fairer sense of the “average” salary because since Dick’s salary is an outlier so the median is automatically not appropriate to describe all the salaries. The mean sort of equally describes all the salaries because it is in the middle of each. The median describes the majority of the salaries, but not Dick’s because it is an outlier.
2. Better than Average Each measure of central tendency has strengths and weaknesses. Not every measure of central tendency can equally describe a problem; usually one of the measures gives a better description of the list of data. All in all, it is best to know the three measures strengths and weaknesses so you can properly use each one for a problem given. The mean equally describes all the numbers. It is “the most widely used and most generally understood way of describing the central tendency or central location of a set of data” (Hamburg 47). The mean is used with dealing with a set amount over a period. In statistics, the
1. What Do You Mean by Mean?
a) The mean of the salaries is calculated by adding up each individual salary and dividing it by the seven employees. The mean of the seven salaries is $43,814.29. The mean compares to the individual salaries because it shows the average of all the salaries together. The employees would use the average to negotiate with Dick for a higher salary, because by looking at the average you can see that Dick’s salary is an outlier compared to the mean.
b) The median of these seven salaries is $23,500. I got the median by first putting the numbers in order. Since it is an odd amount of numbers, I just find the center of the data after they were in order. This value does not really compare to all of the individual salaries; it has no relation other then it is just in the center. Dick’s salary does not compare to the median because it is the outlier, but mostly everyone else’s does because it is around the same amount.
c) The mean gives a fairer sense of the “average” salary because since Dick’s salary is an outlier so the median is automatically not appropriate to describe all the salaries. The mean sort of equally describes all the salaries because it is in the middle of each. The median describes the majority of the salaries, but not Dick’s because it is an outlier.
2. Better than Average Each measure of central tendency has strengths and weaknesses. Not every measure of central tendency can equally describe a problem; usually one of the measures gives a better description of the list of data. All in all, it is best to know the three measures strengths and weaknesses so you can properly use each one for a problem given. The mean equally describes all the numbers. It is “the most widely used and most generally understood way of describing the central tendency or central location of a set of data” (Hamburg 47). The mean is used with dealing with a set amount over a period. In statistics, the
Cited: Hamburg, Morris. Basic Statistics: A Modern Approach. New York: Harcourt Brace Jovanovich, 1974. Print. Wine, R. Lowell. "Chapter 3: Statistical Measures." Beginning Statistics. Cambridge, MA: Winthrop, 1976. 37-38. Print.