Question

Compute the difference between the original data and the estimated values of CO₂ concentration obtained using the quadratic regression. The difference is computed by subtracting the estimated values from the original data (data - estimation). The result has to be a NumPy array named error_quad, computed without using for statment.

Answer 1

To compute the difference between the original data and the estimated values of CO₂ concentration obtained using quadratic regression, subtract the estimated values from the original data using NumPy arrays.

Step-by-step explanation:

To compute the difference between the original data and the estimated values of CO₂ concentration obtained using quadratic regression, we can subtract the estimated values from the original data. This can be done using NumPy arrays without using a for statement.

Here's an example:

import numpy as np
# Assuming original data is stored in original_data array
# Assuming estimated values from quadratic regression is stored in estimated_values array
error_quad = np.subtract(original_data, estimated_values)

The resulting NumPy array, error_quad, will contain the difference between the original data and the estimated values of CO₂ concentration.