Measures of central tendency are descriptive statistics. This is my kind of statistics because it is mean, median, and mode. I learned how to do each of these methods in third grade, so I feel confident in writing this section of my data analysis. It is called measures of central tendency because the question is how often does the data show up in the center, or at least centered, and not all over the map.
The mean is the average that is calculated by adding up all of the values of the responses and dividing by the number of responses. It is important to include this in your doctoral work, and I’m positive you know how to do it. Of course, the data must be able to be added and then divided, which means it must be numerical in nature.
The median is the middle of the data. If you line up all of your data lowest to highest and split it into two equal parts, the median represents the point where half are larger and half are smaller. Suppose you have an odd number of data. The number in the middle is your median – simple. If you have an even number of data, then you have two in the middle. Now you have to do a mean calculation to get to the median. It is still not that hard, only one extra step. The median does not show the outliers as much as the mean, so if you have a couple of survey responses throwing off your data, then the median is more useful.
The mode is the most frequent response that shows up in the data. I remember this with another word game. Mode is for the most. If I see a certain number the MOST, that is the MODE. This is useful to share what is popular in your sample to your population.
What examples do you see where one or more of these measures of central tendency have made a big difference in reporting data?
Next time, distributions and measures of spread.