Regression to the Mean Prediction

Problem

With overall mean mean and correlation rho between two measurements, the predicted second measurement for a first measurement x regresses toward the mean:

prediction = mean + rho * (x - mean).

Return the prediction.

Hint

With perfect correlation the prediction stays at x; with zero correlation it collapses to the mean.

Test cases

case 1

in: [0,1,0.5]

expected: 0.5

case 2

in: [100,120,0.7]

expected: 114

case 3

in: [0,2,0]

expected: 0

case 4

in: [50,50,0.9]

expected: 50

Starter codePython

def regression_to_mean_prediction(mean, x, rho):
    # Your code here
    pass

4 test cases · run your code against them in the editor