There are seveal ways we can describe the shape of a data distribution.

The most common terms that we will use are Symmetrical
Right/Left Skewed
and Uniform

If you were to fold the data at the median, the data would almost match.

Symmetrical

There is a tail on the right side where data drops.

Right Skewed

There is a tail on the left side where data drops.

Left Skewed

​The data values are consistent throughout.

Uniform

The data is distributed evenly. The mean and median and both found very near the center.

​​Symetrical

Tail on the right side. Data is heavily found on the left side. Median and Mean are pulled left (lesser).

Right Skewed

Tail on the left side. Data is heavily found on the right side. Median and mean are pulled right (greater)

Left Skewed

​Areas were data is not present

Gaps

Also the Mode of the data set. The highest point.

​​Peaks

​The area where data is heavily concentrated.
You can have multiple clusters.
**This example) The cluster is from 0 - 30.

Clusters

Find the range of the data set.
High - Low - Range.

This Example) 76 - 65 = a spread of 11.

​​Spread

Data values that are found far from the others.
Outliers can heavily impact your mean.

This example has an outlier of 21.

Outliers