Normality of groups
Now that you've established equal variance, the next condition to check for is normality of the funding in each industry.
In this exercise, you'll visualize and compare data with and without normality. Although these visualizations can be created with plt.hist()
, for this exercise, you'll practice using the .plot()
argument on a DataFrame, with the arguments kind
and alpha
.
The three DataFrames you created (biotech_df
, enterprise_df
and ecommerce_df
) have been loaded for you. The packages pandas as pd
, NumPy as np
, Matplotlib as plt
, and the stats
package from SciPy have all been loaded as well.
This exercise is part of the course
Foundations of Inference in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Plot a histogram of the funding for each industry
____.plot(kind=____, alpha=____)
____.plot(____)
____.plot(____)
plt.show()