end of chapter 8

HW:  Ch. 8 #31, 32, 36

Notes from today in class:

• What the heck is a "line of best fit"?
  
• Its real name is: Least Squares Regression Line!
  
• Or:  LSRL
  
• Least squares? least squares of what?
  
• The sum of all the residuals squared is as small as possible!
  
• Regression?  What does that word mean?
  
• r tells us how much to regress to the mean (example…)
  
• And speaking of mean:
  
• (x-bar, y-bar) is on the line (duh!).
  
• And btw:  the residuals always add up to zero.
• You should also note that if you switch x and y, the correlation does not change, but the LSRL does.
• You should never use a LSRL to predict x using y.  It is not created to minimize the predictions for x, only for y.