Statistics Definitions > Central Tendency
What is Central Tendency?
Central tendency (sometimes called “measures of location,” “central location,” or just “center”) is a way to describe what’s typical for a set of data. Central tendency doesn’t tell you specifics about the individual pieces of data, but it does give you an overall picture of what is going on in the entire data set. There are three major ways to show central tendency: mean, mode and median.
Central Tendency Measures
The mean is the average of a set of numbers. Add up all the numbers in a set of data and then divide by the number of items in the set. For example, the mean of 2 3 5 9 11 is:
(2 + 3 + 5 + 9 + 11) / 5 = 30 / 5 = 6.
For more examples of finding the mean, see:
What is a mean?
The median is the middle of a set of numbers. Think of it like the median in a road (that grassy area in the middle that separates traffic). Place your data in order, and the number in the exact center of a list is the median. For example:
1 2 3 4 5 6 7
The median is 4 because it’s in the center, with three numbers either side.
For more about the median, see:
What is a median?
The mode is the most common number in a set of data. For example, the mode of 1 2 2 3 5 6 is 2. Some data sets have no mode, like this one: 1 2 3 4 5 6. Others have multiple modes, like this one: 1 1 2 3 3.
For more on finding modes, see:
What is a Mode?
Outliers are extremely high or extremely low values. Outliers can affect central tendency, especially the mean. For example, if you got paid three weeks in a row but took vacation in the fourth week, your paychecks might be: $300 $300 $300 $0. Your four week mean would be ($300 + $300 + $300 + $0) / 4 = $900/4 = $225. That outlier of zero dollars brought your mean down very low.
For more on outliers, see:
What are outliers?
Skewed Distribution is a visual way to show the central tendency of a set of data.
What is Skewness?
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