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Pscyh_7_Notes_11_24_09 - 2

Pscyh_7_Notes_11_24_09 - 2 - P ageJ ofJ Page 2 ofJ the two...

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PageJ ofJ The Graph of the Regression line is: 0' 12000 j" g 1ססoo l .e 8000 I : 6000 I fti 4000 t (f) 1 •••. :; 2000 I ~ c L. __ ~ 0 1000 2000 3000 4000 5000 0000 AUra.Uvenos5 lOOt) 2060 3000 4000 5000 6000 AureC11venDGS 12000 § 10000 ... !!. 8000 I .. 00 'ii (tJ 'tooo 'ii ~ 2000 :t G G We demonstrated ihis in class with the case of rating the attractiveness ofH. & M. clearks and the amount,ofsales that they register in a year. Here's a table and the equation that we get from correlatm the two variables. X is the independent variable (or covariate) e is ·the error term (left over). •• Ii .. !j "" "l 3.5 '.0 M 05 JG 15 Hellll11 ·Page 2 ofJ This tells us that the self-esteem value is predicted by the height of the person. But, of course, it doesn't mean that height causes someone to have certain self-esteem. It could be that other factors are lurking in the background that are the true causcs of changes in self-esteem. These confounding variables are generally not observable in a iwo variable siudy. That's why researchers typically measure more than two variables to see how they all relate and which
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