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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.

Cet exercice fait partie du cours

Customer Analytics and A/B Testing in Python

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Instructions

  • Find the number of paywall views in the dataset using .count(). Store this in n.
  • Calculate a quantity we will call v by finding the conversion_rate times the rate of not converting.
  • Now find our variance, var, by dividing v by n. This is the variance of our conversion rate estimate.
  • Finally the square root of var has been taken and stored as the variable se for you. This is the standard error of our estimate.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de 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)
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