Hi group,

I have done my green belt certification one year back and un fortunately i couldn't impletment most of the tols learned during the training.

I want to know, how to use the regression analysis for optimization atleast for three variables)

Regards,

Satheesh Thevar

And using co relation method fopr optimization.

Hi Sateesh,

The Regression equation is nothing but an effort to predict the output when your X's i.e. variables takes a certain set of values. You assign values to the variables and you have the predicted result as Y.

So, with the equation provided, if you have control on your Xs (Variables) you can estimate your Ys..

Coming to Correlation, It just gives out if 2 variables are positively/negatively correlated i.e. related. Eg : In cricket Spin Balls vs Runs scored for a player. If negative correlation, you may choose not to select the player for a spin friendly pitch and vice versa...

Hope it helps...

 

Dear Satheesh,

Regression model is nothing but a relationship between your input(s) and your output. It is primarily used when your input(s) and output are continuous. Typically, we build a linear model between the input(s) and output.

If you have one input and one output, we use simple regression of the form Y = m*X + c. Where, X is your input and Y is your output.

For your question, if I understand it correctly, you have three inputs, X1, X2, X3, in which case, we would use multiple regression where the model would be:

Y = m1*X1 + m2*X2 + m3*X3 + c

Once you build a regression model and check that you have a decent model between your inputs and output, then you can use this for prediction or optimization. Make sure you check the adjusted R^2 values, the appropriate P-values, and also make sure that you check the model assumptions are satisfied. One of the most important requirements is that X1, X2, and X3 should not be co-linear.

Once you have a model, you can then use it for optimization by adding additional constraints on X1, X2, and X3 (if appropriate). This optimization can be done using Linear Programming (LP) - a reference to LP is shown below.

Reference: http://en.wikipedia.org/wiki/Linear_programming.

Hope this helps,

SJ