A/B Testing A/B testing is a form of hypothesis testing that allows you to make comparisons between two distributions. You'll almost never be explicitly asked to perform an A/B test. Make sure you can identify situations where the test is appropriate and know how to correctly implement each step. The following statements are the unordered steps of an A/B hypothesis test: 1. Choose a test statistic (typically the difference in means between two categories) 2. Shuffle the labels of the original sample, find your simulated test statistic, and repeat many times 3. Find the value of the observed test statistic 4. Calculate the p-value based off your observed and simulated test statistics 5. Define a null and alternate model 6. Use the p-value and p-value cutoff to draw a conclusion about the null hypothesis Make an array called ab_test_order that contains the correct order of an A/B test, where the first item of the array is the first step of an A/B test and the last item of the array is the last step of an A/B test.