In this analysis, we have gone through the steps of data cleaning, exploratory data analysis, building simple and multiple linear regression models, and performing model diagnostics. We utilized different variable selection methods and compared their performance using various criteria. The stepwise regression model was found to provide a good balance between model complexity and predictive accuracy. Further improvements could be made by exploring other types of models or incorporating additional features if more data is available. This analysis provides a foundation for predicting house prices and understanding the factors that influence them in the given dataset.

report 4

report 4