I do not have your data.
However if you have a bunch of points (x1,y1) , (x2, y2) .... (xn,yn)
then you can fit a line of form y = m x + b
that "best" fits those points, the criterion being that the sum of the squares of distances from the points to the line is minimized.
I do not think I have to tell you how to find the equation of that line. If it is not in your text, then Google "least squares fit"
Now, there is some point (x,y) that they gave you that might be part of that data set. In a perfect world that point would lie on the line, but so would all the other points. I fact it probably lies somewhere near the line, but not on it.
I have all the data, I just need someone to tell me how to start xc Please! I've been working on this for 5 hours now!
8. Calculate the equation of the least squares regression line. Draw this line on your scatter plot. The point (x,y) should lie on the line. Does it? Plot and label this point.
I'm not sure what this is asking for!
3 answers
for example:
http://mathworld.wolfram.com/LeastSquaresFitting.html
http://mathworld.wolfram.com/LeastSquaresFitting.html
and here is a calculator for it:
http://www.neoprogrammics.com/linear_least_squares_regression/
http://www.neoprogrammics.com/linear_least_squares_regression/