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.