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March 20th, 2017, 06:03 PM  #1 
Newbie Joined: Nov 2016 From: England Posts: 2 Thanks: 0  Method of Least Squares
Hi, I've attached the question and my worked solution. I am confident I have the correct least squares straight line of best fit to the data to 2 d.p., but I'm unsure what is being asked in the next part. Am I to sub the xi values into the least squares straight line of best fit to acquire yi estimates? And if so, I know there will be variation. How would you explain the accuracy of such variation? 
March 29th, 2017, 09:10 PM  #2 
Newbie Joined: Nov 2013 Posts: 29 Thanks: 1 
Was this for some class?

March 29th, 2017, 10:16 PM  #3 
Senior Member Joined: Jul 2008 From: Western Canada Posts: 3,187 Thanks: 33 
The parameters that you calculated for your regression line look correct. Yes, that's how I understand the question. Not sure what they want you to comment on exactly. Sometimes, the data will fit the regression line very closely, and sometimes it won't. I'm not sure there's much more that you can say. If there were some outliers, you could comment on that, but I don't see any. 
March 29th, 2017, 10:20 PM  #4 
Senior Member Joined: Sep 2015 From: Southern California, USA Posts: 1,488 Thanks: 749 
you've estimated a linear model given this data. $y(x) = 8.71x + 31.91$ for each $x_i$ find $y(x_i) = 8.71x_i + 31.91$ Plot these points in one color and your actual data points in another. You'll find the data isn't particularly linear in this case. 
April 2nd, 2017, 04:08 PM  #5 
Senior Member Joined: Oct 2013 From: New York, USA Posts: 561 Thanks: 79  In order to provide as much help to ChrisHughes as possible, we need to know if he has studied regression that isn't linear.


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