Least squares fit to a straight line?

[noname1]

I was wondering if someone could explain how to compute the Least squares fit to a straight line

 

[ehild]

You have N experimental points (xi,yi) and you want to fit a straight line y=ax+b across them so that the mean value of the square of the deviations y(xi)-yi is minimum with respect to the parameters a and b
.
S=\sum_1^N{(ax_i+b-y_i)^2} = minimum

For that, the partial derivatives of S have to be zero. This condition yields two equations for a and b.

\partial S /\partial a=\sum_1^N{2(ax_i+b-y_i)x_i}=0
\partial S /\partial b=\sum_1^N{2(ax_i+b-y_i)}=0

Rearranging the equations:

a\sum_1^N{x_i^2}+b\sum_1^N{x_i}=\sum_1^N{x_i y_i}

a\sum_1^N{x_i}+N b=\sum_1^N{y_i}

Solve for a and b.

ehild

 

[noname1]

i have solved it and got this

y = 46.3x+(-61.8)

my question is now, i plotted my points on a table on paper but how do i make the straight line?

 

[ehild]

Just calculate two points of your equation, put them onto the plot and connect them with a straight line :)

ehild

 

[noname1]

how didnt i think of that duhhh lol, one more question now how do i calculate g from the slope?