Do These Factors Predict Home Prices? A Regression Analysis of 150 Transactions

In order to determine if a model can explain statistically significant variation in the prices of homes, a regression analysis would need to be conducted. The analysis would involve fitting a multiple linear regression model with the response variable being the price of the home and the four candidate explanatory variables being the number of square feet, number of bathrooms, lot size, and median household income.

The regression analysis would provide information on the coefficients of each variable and their corresponding p-values. If the p-values are less than 0.05, it would indicate that the variable is statistically significant in explaining the variation in home prices. Additionally, the overall model would be evaluated using the F-test, which tests if at least one of the variables in the model is statistically significant.

Without conducting the regression analysis, it is not possible to determine if the model explains statistically significant variation in the prices of homes.