IniziaInizia gratis

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.

Questo esercizio fa parte del corso

Customer Analytics and A/B Testing in Python

Visualizza il corso

Istruzioni dell'esercizio

  • 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.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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)
Modifica ed esegui il codice