Answer :
By using the learned slope and intercept from the squarefeet model, the RSS for the simple linear regression using squarefeet to predict prices on TRAINING data is between 1.1e+15 and 1.3e+15.
A code chunk that can be used for determining the Residual Sum of Squares (RSS) for the simple linear regression using squarefeet to predict prices on TRAINING data can be written in Python Programming language as follows;
get_residual_sum_of_squares (train_data["sqft_living"], train_data["price"], intercept, slope)
def inverse_regression_predictions (output, intercept, slope):
estimated_input = (output - intercept)/slope
return estimated_input
output = 1,201,918,356,321,968.0.
Therefore, the Residual Sum of Squares (RSS) for the simple linear regression using squarefeet to predict prices on TRAINING data is between 1.1e+15 and 1.3e+15.
Complete Question;
Using the learned slope and intercept from the squarefeet model, What is the RSS for the simple linear regression using squarefeet to predict prices on TRAINING data?
