For simple linear regression, the Y best estimate (a.k.a. "Y-hat") will be the same as your correlation value. (For multiple regression, it will be the beta value.) Essentially, that is a measure of how well your data fit your model (i.e. how close you are/how much error). The higher, the better estimator and less amount of error.
Good day. How close should we be with Y best estimate? Is there a range plus/minus we shoot for?
For simple linear regression, the Y best estimate (a.k.a. "Y-hat") will be the same as your correlation value. (For multiple regression, it will be the beta value.) Essentially, that is a measure of how well your data fit your model (i.e. how close you are/how much error). The higher, the better estimator and less amount of error.
Thanks. Great video.
Then how can I calculate to get y-hat
How can you calculate x
X and y are usually given
so is N the number of sample data points?
Yes