Adjusted R-Squared from Summary Statistics

Problem

Return the adjusted R-squared 1 - (1 - R^2)*(n - 1)/(n - p - 1), where p is the number of predictors. Return 0.0 when n - p - 1 <= 0.

Hint

The adjustment penalizes each additional predictor.

case 1

in: [0.8,100,2]

expected: 0.7958762886597939

case 2

in: [0.5,10,1]

expected: 0.4375

case 3

in: [0.9,20,5]

expected: 0.8642857142857143

case 4

in: [0.5,3,2]

expected: 0

case 5

in: [0.6,5,3]

expected: -0.6000000000000001

Starter codePython

def adjusted_r_squared(r2, n, p):
    # Your code here
    pass

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