input: Write a python function to calculate the coefficients of a linear regression model.
  assert coefficients(np.array([1,2,3,4,5]), np.array([1,4,9,16,25])) == (-7.0, 6.0)
  assert coefficients(np.array([1,2,3]), np.array([1,4,9])) == (-2.333333333333333, 3.5)
  assert coefficients(np.array([1,2,3,4]), np.array([2,4,6,8])) == (0.0, 2.0)
output: import numpy as np
  
  def coefficients(x, y):
      n = len(x)
      x_mean = np.mean(x)
      y_mean = np.mean(y)
      
      numerator = np.sum((x - x_mean) * (y - y_mean))
      denominator = np.sum((x - x_mean) ** 2)
      
      b1 = numerator / denominator
      b0 = y_mean - b1 * x_mean
      
      return (b0, b1)