In this course, I learn how to use SQL in order analyze a dataset from Yelp.
Write a query and table creation statement to make final_assignments_qa look like the final_assignments table. If you discovered something missing in part 1, you may fill in the value with a place holder of the appropriate data type.
Use the final_assignments table to calculate the order binary for the 30 day window after the test assignment for item_test_2 (You may include the day the test started)
Use the final_assignments table to calculate the view binary, and average views for the 30 day window after the test assignment for item_test_2. (You may include the day the test started)
Use the https://thumbtack.github.io/abba/demo/abba.html to compute the lifts in metrics and the p-values for the binary metrics ( 30 day order binary and 30 day view binary) using a interval 95% confidence.
Use Mode’s Report builder feature to write up the test. Your write-up should include a title, a graph for each of the two binary metrics you’ve calculated. The lift and p-value (from the AB test calculator) for each of the two metrics, and a complete sentence to interpret the significance of each of the results.
View Binary
We can say with 95% confidence that the lift value is 2% and the p_value is 0.2.
There is not a significant difference in the number of views within 30days of the assigned treatment date between the two treatments.
Order binary
There is no detectable change in this metric. The p-value is 0.86
meaning that there is a no significant difference in the number of orders within 30days of the assigned treatment date between the two treatments.