Sales price explained 28.8% by living area; other factors still influence 71.2%.
The proportion of the variance in sales price that can be explained by its linear relationship with living area is 0.2879, which is 28.79% rounded to four decimal places. This means that 28.79% of the variation in sales price can be explained by the linear relationship between sales price and living area. The remaining 71.21% of the variation in sales price is due to other factors, such as location, amenities, and condition of the property.
The RStudio output you provided shows the results of a regression analysis of the linear relationship between sales price and living area. The coefficient of determination, R^2, is 0.2879, which means that 28.79% of the variation in sales price can be explained by the linear relationship between sales price and living area. The p-value of the t-statistic for the coefficient of living area is less than 0.001, which means that the relationship between sales price and living area is statistically significant.
The intercept of the regression line is 4550.1, which means that the predicted sales price for a property with a living area of 0 square feet is $4550.10. The slope of the regression line is 91.4, which means that the predicted sales price increases by $91.40 for each additional square foot of living area.
Overall, the results of the regression analysis suggest that there is a positive linear relationship between sales price and living area. However, it is important to note that other factors, such as location, amenities, and condition of the property, also play a role in determining sales price.