Questions for further inquiry: What other factors contribute to the price change in a house? Does the square footage predict the price differently depending on the location? What could be a good independent variable to determine the possible listing price of different plots of land?

In conclusion, the linear regression equation Y = 79.11x +166649 is a model that will allow you to predict a house’s potential listing price based on its size in square feet. Although there are other factors that contribute to the price of the listing, the correlation is so strong that the use of this model makes sense. The results of this analysis met my expectations. If you are interested in developing a model to make better predictions, it would be helpful to use a larger set of data. Developing models for specific areas that are interested in making predictions is also an innovative idea. A regression model would be best suited for a less variability data set. For example, in the analysis I made of a single region earlier, r and r2 were much closer to 1. This means that more price variability could be predicted by size