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Exercise

Comparing PDFs

In the previous exercise, we used CDFs to see if the distribution of income is lognormal. We can make the same comparison using a PDF and KDE. That's what you'll do in this exercise!

As before, the norm object dist is available in your workspace:

from scipy.stats import norm
dist = norm(mean, std)

Just as all norm objects have a .cdf() method, they also have a .pdf() method.

To create a KDE plot, you can use Seaborn's kdeplot() function. Here, Seaborn has been imported for you as sns.

Instructions

100 XP
  • Evaluate the normal PDF using dist, which is a norm object with the same mean and standard deviation as the data.
  • Make a KDE plot of the logarithms of the incomes, using log_income, which is a Series object.