Unbiased Slope Estimate in Linear Regression

  • Thread starter Thread starter TranscendArcu
  • Start date Start date
  • Tags Tags
    Estimate Slope
TranscendArcu
Messages
277
Reaction score
0

Homework Statement



There is the suggestion to use an alternative estimate for the slope $$\beta$$ in the linear regression $$y_i=\alpha+\beta x_i+\epsilon_i$$which is formulated as $$B=(y_{max} -y_{min})/(x_{max} - x_{min})$$

Prove that such a formulation of $$B$$ is unbiased.

Homework Equations


The Attempt at a Solution



I'm actually having a very hard time with this problem and would appreciate the slightest nudge in the right direction. Can anyone assist me with this problem?
 
Physics news on Phys.org
TranscendArcu said:

Homework Statement



There is the suggestion to use an alternative estimate for the slope $$\beta$$ in the linear regression $$y_i=\alpha+\beta x_i+\epsilon_i$$which is formulated as $$B=(y_{max} -y_{min})/(x_{max} - x_{min})$$

Prove that such a formulation of $$B$$ is unbiased.

Homework Equations





The Attempt at a Solution



I'm actually having a very hard time with this problem and would appreciate the slightest nudge in the right direction. Can anyone assist me with this problem?

When you write ##y_{\min}##, etc., do you mean the ##y## value that accompanies ##x_{\min}## (that is, ##y_{\min} = f(x_{\min})##) or are ##x_{\min}## and ##y_{\min}## unrelated, each being the min in its own data set?
 
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...

Similar threads

Back
Top