from sklearn.linear$\_$model import LinearRegression

regr $=$ LinearRegression$()$

regr.fit$($genre$\_$dummies, gross$[\text{'}$inflation$\_$adjusted$\_$gross'$])$

action $=$ regr.intercept$\_$

adventure $=$ regr.coef$\_[[0]][0]$

print$(($action$,$ adventure$))$

Next, we will compute $95\%$ confidence intervals for the intercept and coefficients. The $95\%$ confidence intervals for the intercept and coefficient means that the intervals have a probability of $95\%$ to contain the true value and coefficient respectively. If there is a significant relationship between a given genre and the adjusted gross, the confidence interval of its coefficient should exclude $0.$ We will calculate the confidence intervals using the pairs bootstrap method.

# Import a module

import numpy as np

# Create an array of indices to sample from

inds $=...$ #CODE HERE

# Initialize $500$ replicate arrays

size $=500$

bs$\_$action$\_$reps $=...$#CODE HERE

bs$\_$adventure$\_$reps $=...$#CODE HERE