1. How to Build
Regression Models in
Excel
Ashutosh Nandeshwar
@n_ashutosh
Advancement Services track sponsored by
Blackbaud
Follow the Better Together Conference on Twitter #CASEV+VI
14. Today’s session
evaluations
will be e-mailed to you.
Session handouts are available at
www.casefive.org/conference/presentations/
Username: CASEV-VI | Password: Chicago 2012
@n_ashutosh
Follow the Better Together Conference on Twitter by using the #CASEV+VI hashtag when you tweet!
Editor's Notes
. For segmentation, quick scoring, modeling, giving, easier options, forecasting, predicting, any analyst worth his money should ask why and so what?
We won’t go in all details here, but we can talk about a few things.
At its essence, linear regression is about minimizing the distance between the predicted value of an observation and the actual value of an observation, the technique is called least-squares
If you want to use Excel, then all the variables should be numeric or coded as numeric. You have enough data, but not a whole lot of data. You are just getting started in modeling.
If your data is quite skewed or the parameters have non-linearity , or you suspect that variables are quite similar.
This is the exciting or not-so exciting part, where you actually learn how to do this.
Missing data, lots of variables, low accuracy, R2 < 0.5, unable to take advantage of various newer methods, variable selection is manual.
