How can I use the expression for a in this problem

AI Thread Summary
To demonstrate the relationship between the means and sums in a bivariate distribution where the regression line of y on x passes through the origin, the key is to analyze the regression equation. When the intercept a is set to zero, the relationship simplifies to y being proportional to x. The expression for the slope b can be used to derive the desired equation, showing that if a equals zero, then the equality $$\bar y \sum^n_{r=1} x_r^2 = \bar x \sum^n_{r=1} x_r y_r$$ holds true. Understanding the implications of the regression line passing through the origin is crucial for solving the problem. This analysis leads to a clearer understanding of the bivariate relationship in the sample data.
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.
 
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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?
 
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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 ##​
.
 
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