Question about multiple regression analysis

sigh1342
Messages
30
Reaction score
0

Homework Statement



My question is q.3 in the attachment. I don't really understand the scenario of the question.

The Attempt at a Solution



For (a), if X = 1, will the model become: y = (b_1)(E_1) + epsilon? So (b_i)'s are the slopes of the models? But what is the assumption of the model?

And for the rest of the question, I'm just looking for someone to explain to me a little bit more.
 

Attachments

  • IMG_20121118_151304.jpg
    IMG_20121118_151304.jpg
    45.6 KB · Views: 483
Physics news on Phys.org
sigh1342 said:

Homework Statement



My question is q.3 in the attachment. I don't really understand the scenario of the question.

The Attempt at a Solution



For (a), if X = 1, will the model become: y = (b_1)(E_1) + epsilon? So (b_i)'s are the slopes of the models? But what is the assumption of the model?

And for the rest of the question, I'm just looking for someone to explain me a little bit more.

The assumption of the model is that the errors are independent of the categories. For example, suppose there are two categories, called 'male' and 'female' and that there is some measured numerical aspect Y of a person. The model is saying that Ymale = mmale + ε and Yfemale = mfemale + ε, with possibly different means m but identical "noise" ε.

RGV
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
Back
Top