FAQ: Variance - Average Distances

This community-built FAQ covers the “Average Distances” exercise from the lesson “Variance”.

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This exercise can be found in the following Codecademy content:

Learn Statistics With Python

FAQs on the exercise Average Distances

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1 Like

I didn’t get the point of this session - both of the result is 0, what does it mean?

import numpy as np

grades = [88, 82, 85, 84, 90]
mean = np.mean(grades)

difference_one = 88 - mean
difference_two = 82 - mean
difference_three = 85 - mean
difference_four = 84 - mean
difference_five = 90 - mean

#Part 1: Sum the differences
difference_sum = difference_one + difference_two + difference_three + difference_four + difference_five

#Part 2: Average the differences
average_difference = difference_sum / 5

print("The sum of the differences is " + str(format(difference_sum, "f")))
print("The average difference is " + str(format(average_difference, "f")))


the line

mean = np.mean(grades)

should actually be

mean = np.average(grades)

Hi there’s an issue with the + str(format(difference_sum, “f”))), the “f” Displays fixed point number (Default: 6), so if you want to see the true value i suggest to add “.16f” instead of the “f” or put the value in the exponential form “e” instead of “f” (I suggest the exponential format

1 Like

Thank you for the kind explanation! I understand that the point is, positive and negative values ​​cancel each other out, and the result of the sum becomes too small.

#1 Sum the five variables difference_one through difference_five and store the result in the variable difference_sum .

If you type this in…

# Part 1: Sum the differences
difference_sum = sum(grades)

Then you get a red check box with this message…

difference_sum should be the difference_one + difference_two + ... and so on.

The expected answer is…

difference_sum = difference_five + difference_four + difference_one + difference_three, difference_two

Since we are just getting the sum why is the first solution incorrect?

Hello @psmilliorn!

This step is looking for the sum of the grades, each subtracted by the mean, not the sum of the grades themselves.

difference_one has a different value than the first element of grades, difference_two has a different value than the second element of grades, etc.

If you wanted to use sum() on a list, you would have to first create a list of all the differences.