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Scenario
> Neighborhood
> Explanation

Definitions
> Mean is...
> Mean is not...
> Median is...
> Mode is...

Example
> Height

> Works Cited

## Example 1: The Minnesota Timberwolves ('99-'00)

Let's test our newly acquired knowledge of "mean", "median", and "mode" with some real-world data. Below we see the heights of the basketball players on the Minnesota Timberwolves squad.

 Player Height Brandon 5'11" (71") Jackson 6'1" (73") Avery 6'2" (74") Peeler 6'4" (76") Mitchell 6'7" (79") Szczerbiak 6'7" (79") Sealy 6'8" (80") Hammonds 6'9" (81") Patterson 6'9" (81") Smith 6'10" (82") Garnett 6'11" (83") Garrett 6'11" (83") Nesterovic 7'0" (84")

Terrel Brandon is the shortest Timberwolve's player at 5'11" (71") while Radoslav Nesterovic stands 7'0" (84") tall. All of the other players fall between these values, but note that they are not evenly distributed. There are more tall players than short players (although even the "short" players are tall by most people's standards). Based on this knowledge of the height distribution, let's try to answer a few questions about the "mean", "median", and "mode."

#### Knowledge Check

1. The median height of the team is...

Hint: Remember that the "median" divides the data in half, while the "mean" lies closer to the "snails head" (i.e. towards the side with more extreme values).

2. The data has three modes (79", 81", & 83"). However, when the data is placed in bins (see histogram) we can be fairly confident that the most typical height is...

Hint: Remember that the "most typical" value occurs at the top of the "snails shell" (i.e. most frequent bin value), while the "mean" lies closer to the "snails head" (i.e. towards the side with more extreme values).