Estimates of Variability
 Location is just one dimension in summarizing a feature, A second dimension variability, also referred to as dispersion, measures whether the data values are tightly clustered or spread out.
 At the heart of statistics:
 measuring it
 reducing it
 distinguishing random from real variability
 identifying various sources of real variability
 making decisions int the presence of it

Refer Here for the calculations of variability estimates

Exercise: Calculate the standard deviation and IQR for the gpa in the following dataset Refer Here
Exploring the Data Distribution
 Each of the estimates we’ve covered sum up the data in a single number to descirbe the location or variablility.
 It is also useful to explore how the data is distributed overall
 Box Plots
 Refer Here for the notebook.