Standard error
Previously we observed how to calculate the standard deviation using the .std() method. In this exercise, you will explore how to calculate standard deviation for a conversion rate, which requires a slightly different procedure. You will calculate this step by step in this exercise.
Loaded for you is our inner merged dataset purchase_data as well as the computed conversion_rate value.
This exercise is part of the course
Customer Analytics and A/B Testing in Python
Exercise instructions
- Find the number of paywall views in the dataset using
.count(). Store this inn. - Calculate a quantity we will call
vby finding theconversion_ratetimes the rate of not converting. - Now find our variance,
var, by dividingvbyn. This is the variance of our conversion rate estimate. - Finally the square root of
varhas been taken and stored as the variablesefor you. This is the standard error of our estimate.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Find the number of paywall views
n = purchase_data.purchase._____
# Calculate the quantitiy "v"
v = _____ * (1 - conversion_rate)
# Calculate the variance and standard error of the estimate
var = _____ / _____
se = var**0.5
print(var)
print(se)