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Exercise

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.

Instructions 1/3
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  • 1

    Compute and print a 99% confidence interval for 50 trials; does it contain the true proportion of a fair coin flip?

    • 2

      Adapt your code to generate a 90% confidence interval this time; does it contain the true proportion this time?

    • 3

      Repeat this process of sampling, computing the confidence interval, and printing the result 10 times using a loop.

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