Applying confidence intervals
In practice, you aren't going to hand-code confidence intervals. Let's utilize the statsmodels package to streamline this process and examine some more tendencies of interval estimates.
In this exercise, we've generated a binomial sample of the number of heads in 50 fair coin flips saved as the heads variable. You'll compute a few different confidence intervals for this sample, and then scale your work for 10 similar samples.
The proportion_confint() function has already been imported to help you compute confidence intervals.
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Practicing Statistics Interview Questions in Python
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# Compute and print the 99% confidence interval
confidence_int = proportion_confint(heads, ____, ____)
print(____)