2
Housing Price Prediction Model for D.M. Pan National Real Estate Company
Module Two Notes
Hello everyone, I am here today to provide intuitive analysis of how people can get a competitive advantage. Today I will be presenting Data of the South Atlantic Region. Now a days housing is the most thing that people must pay for. And it is very important that we help them in every way that we can. Price, location, square footage, build year, and so many other factors that can help predict the business environment and provide the best advice to their clients.
Regression Equation
The regression equation the Slope and Intercept are 123.3932032 and 111760.4876. Determine r
R correlation is 0.614026245, which has a Positive and strong correlation because it is closer to 1
and not negative. Examine the Slope and Intercepts
Slope and Intercept are 123.3932032 and 111760.4876. R-squared Coefficient
R-squared is 0.377027929, which is only R correlation squared. Conclusions
The regional sample that I created I also compared it to the National Statistics and Graphs; you can see how things have increased. 12339.32 is the price it goes up for every 100 square feet.
