input: Write a function to perform linear regression and predict the value of y for a given dataset X and Y. The function should return the predicted value for a new input.
  assert perform_linear_regression([1,2,3,4,5], [3,5,7,9,13], 7)==11.0
  assert perform_linear_regression([1,3,5,7,9], [2,4,6,8,10], 6)==6.0
  assert perform_linear_regression([0,1,2,3,4], [1,3,5,7,9], 5)==11.0
  assert perform_linear_regression([2,4,6,8,10], [1,2,3,4,5], 9)==5.5
  assert perform_linear_regression([1,2,3,4,5], [2,4,6,8,10], 3)==6.0
output: def perform_linear_regression(X, Y, new_input):
      n = len(X)
      sum_x = sum(X)
      sum_y = sum(Y)
      sum_xy = sum(x * y for x, y in zip(X, Y))
      sum_x2 = sum(x ** 2 for x in X)
      
      m = (n * sum_xy - sum_x * sum_y) / (n * sum_x2 - sum_x ** 2)
      b = (sum_y - m * sum_x) / n
      
      return m * new_input + b