 Okay, I know several of you are struggling with this homework problem, and it really isn't meant to be that difficult and time consuming if you just slow down and use the tools that we've gone over. The first thing we have to do is use regression to get an equation for the units of brand A that are sold that is dependent upon the price of brand A and the price of brand B. So let's do that. We'll go to data, data analysis package, click on regression. Let me clean out that data there. The Y range, that's our result and that's going to be unit A sold. Our input X range is going to be both the price of A and the price of B. So I'll just highlight that range, click on labels since we have labels in the first row there and I'm just going to click on okay and you'll get a regression output that looks something like this and in it we see that it is significant of course, that's you know very small P there and we've got an intercept, we've got a negative slope of the coefficient of the price of A and a positive slope or coefficient of the price of B and so you would just construct an equation from those values. The number of A sold is equal to this intercept minus this coefficient times the units of A sold, I'm sorry, the price of A plus this coefficient times the price of B and that's all there is to it. Then we go back in to our data and we will run the second regression, regression and this time I've got to change that area, this time we want the unit to be so for our Y and get rid of that and our X range again the price of A and the price of B. Click on labels, click okay and we get another regression output again with a coefficient, I'm sorry an intercept, a coefficient of the price of brand A and a negative coefficient or slope on the price of brand B and again you convert that into equation. Then you use those two equations in the model that I showed you earlier, hope this helps.