input: Write a python function to perform simple linear regression and calculate the coefficients b0 and b1.
  assert simple_linear_regression([1, 2, 3, 4, 5], [2, 4, 5, 4, 5]) == (2.2, 0.6)
  assert simple_linear_regression([1, 2, 3, 4], [2, 3, 4, 5]) == (1.0, 1.0)
  assert simple_linear_regression([1, 2, 3], [2, 2, 2]) == (2.0, 0.0)
output: def simple_linear_regression(x, y):
      n = len(x)
      mean_x = sum(x) / n
      mean_y = sum(y) / n
      
      numerator = sum((x[i] - mean_x) * (y[i] - mean_y) for i in range(n))
      denominator = sum((x[i] - mean_x) ** 2 for i in range(n))
      
      b1 = numerator / denominator
      b0 = mean_y - b1 * mean_x
      
      return b0, b1