input: Write a function to create a Linear Regression model using the given data of living area and number of rooms to predict housing prices. The function should take the training data (X) and target values (y) as input and return the trained model. Additionally, the function should provide a prediction for a new data point given as [2200, 3].
  
  assert create_housing_price_model([[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]], [75000, 43000, 59000, 32000, 85000]) == 65200.0
output: def create_housing_price_model(X, y):
      from sklearn.linear_model import LinearRegression
      model = LinearRegression()
      model.fit(X, y)
      prediction = model.predict([[2200, 3]])
      return prediction[0]