input: def linear_regression_predict(X: List[float], Y: List[float]) -> float:
      """
      Perform linear regression on the given dataset and predict the value of y for a given x.
      X and Y are lists of numbers representing the input dataset.
      The function returns the predicted value of y for x = 7.
  
      >>> linear_regression_predict([1, 2, 3, 4, 5], [3, 5, 7, 9, 13])
      [15.0]
      """
output:     n = len(X)
      sum_x = sum(X)
      sum_y = sum(Y)
      sum_xy = sum([X[i] * Y[i] for i in range(n)])
      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 * 7 + b