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Calculating confidence intervals

Now you will calculate the confidence intervals for the A/B test results.

The four values that have been calculated previously have been loaded for you (cont_conv, test_conv, test_size, cont_size) as variables with those names.

This exercise is part of the course

Customer Analytics and A/B Testing in Python

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Exercise instructions

  • Calculate the mean of the distribution of our lift by subtracting cont_conv from test_conv.
  • Calculate the variance of our lift distribution by completing the calculation. You must complete the control portion of the variance.
  • Find the standard deviation of our lift distribution by taking the square root of the lift_variance
  • Find the confidence bounds for our A/B test with a value equal to our lift_mean, a 0.95 confidence level, and our calculated lift_sd. Pass the arguments in that order.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Calculate the mean of our lift distribution 
lift_mean = ____ - ____ 

# Calculate variance and standard deviation 
lift_variance = (1 - test_conv) * test_conv /test_size + (____ - ____) * ____ / ____
lift_sd = ____**0.5

# Find the confidence intervals with cl = 0.95
confidence_interval = get_ci(____, ____, ____)
print(confidence_interval)
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