How can I use the expression for a in this problem

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Homework Help Overview

The discussion revolves around a problem involving a bivariate distribution and the conditions under which the regression line of one variable on another passes through the origin. Participants are tasked with demonstrating a specific relationship involving sample means and sums of products.

Discussion Character

  • Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants express uncertainty about how to begin the problem and reference the regression line equation. Some question the implications of the intercept being zero, while others suggest considering the relationship between the variables.

Discussion Status

The discussion is ongoing, with participants exploring the implications of the regression line passing through the origin. Some guidance has been offered regarding the expressions for the coefficients, but no consensus has been reached on the next steps.

Contextual Notes

Participants note the importance of correctly interpreting the regression line's parameters and the implications of setting the intercept to zero. There is also a mention of formatting issues with mathematical expressions that have been addressed.

Faiq
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Homework Statement



A random sample of size ##n## from a bivariate distribution is denoted by ##(x_r,y_r), r=1,2,3,...,n##. Show that if the regression line of ##y## on ##x## passes through the origin of its scatter diagram then[/B]
$$\bar y \sum^n_{r=1} x_r^2=\bar x\sum^n_{r=1} x_r y_r$$ where ## (\bar x,\bar y)## is the mean point of the sample.

I don't really know how to begin. I am aware the line equation is $$b=\frac{y}{x}=\frac{\sum xy-\frac{\sum x\sum y}{n}}{\sum x^2-\frac{(\sum x)^2}{n}}$$

Not sure what to do next.
 
Last edited by a moderator:
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Faiq said:

Homework Statement



A random sample of size ##n## from a bivariate distribution is denoted by ##(x_r,y_r), r=1,2,3,...,n##. Show that if the regression line of ##y## on ##x## passes through the origin of its scatter diagram then[/B]
$$\bar y\sum^n_{r=1} x_r^2=\bar x\sum^n_{r=1} x_r y_r$$ where ## (\bar x,\ bar y)## is the mean point of the sample.

I don't really know how to begin. I am aware the line equation is $$b=\frac{y}{x}=\frac{\sum xy-\frac{\sum x\sum y}{n}}{\sum x^2-\frac{(\sum x)^2}{n}}$$

Not sure what to do next.
(1) Do not write ##\xbar##, write ##\bar{x}##. Right-click on the formula to see its TeX commands.
Mod note: Fixed the TeX in the original post and above.
(2) What can you say about the data if the least-squares line has intercept ##a## equal to zero?
 
Last edited by a moderator:
Y is proportional to X
 
Faiq said:
Y is proportional to X

That answer is not useful. Take the formula for ##a##, in terms of ##(x_i,y_i)##, and set it to zero. What do you get?
 
Faiq said:

Homework Statement


[/B]
A random sample of size ##n## from a bi-variate distribution is denoted by ##(x_r,y_r), r=1,2,3,...,n##. Show that if the regression line of ##y## on ##x## passes through the origin of its scatter diagram then
$$\bar y \sum^n_{r=1} x_r^2=\bar x\sum^n_{r=1} x_r y_r$$ where ## (\bar x,\bar y)## is the mean point of the sample.

The Attempt at a Solution


I don't really know how to begin. I am aware the line equation is $$b=\frac{y}{x}=\frac{\sum xy-\frac{\sum x\sum y}{n}}{\sum x^2-\frac{(\sum x)^2}{n}}$$ Not sure what to do next.
I suppose the that the linear model you are working with is: ##\ \displaystyle y=a+bx\ ##.

You have the correct expression for finding the linear coefficient, ##\ b\,.\ ##( Leave out the ##\ \displaystyle \frac yx\ ## ).

It seems to me that you must also consider the expression for ##\ a\,.\ ## Then show that if ##\ a=0\,,\ ## then you obtain the desired result:
##\displaystyle \bar y \sum^n_{r=1} x_r^2=\bar x\sum^n_{r=1} x_r y_r ##​
.
 
Last edited:

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