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.