input: Write a function to perform linear regression for predicting the numbers in a given dataset. The function should take two lists X and Y as input, where X is the list of independent variables and Y is the list of dependent variables. The function should return the predicted value for a new input X_new.
  
  
  def predict_linear_regression(X, Y, X_new):
      import numpy as np
      from sklearn.linear_model import LinearRegression
  
      X = np.array(X).reshape(-1, 1)
      Y = np.array(Y)
  
      model = LinearRegression()
      model.fit(X, Y)
  
      return model.predict([[X_new]])
  
  # Test cases
  assert predict_linear_regression([1,2,3,4,5], [3,5,7,9,13], 7)[0]==13
  assert predict_linear_regression([1,2,3,4,5], [3,5,7,9,13], 6)[0]==11
  assert predict_linear_regression([1,2,3,4,5], [3,5,7,9,13], 5)[0]==9
  
output: def predict_linear_regression(X, Y, X_new):
      import numpy as np
      from sklearn.linear_model import LinearRegression
  
      X = np.array(X).reshape(-1, 1)
      Y = np.array(Y)
  
      model = LinearRegression()
      model.fit(X, Y)
  
      return model.predict([[X_new]])