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And yaxis respec7vely label range of values for each

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Unformatted text preview: tween the two variables   Allows you to quickly see the direc7on (+/ ­), and (rela7ve) strength of the associa7on 3 11/13/13   Draw axes with one variable on x ­axis and other on y ­axis   Usually doesn’t ma`er which is on which axis ▪  BUT, if you consider one variable as “predictor” and one as “outcome,” then these should be placed on x ­axis and y ­axis, respec7vely   Label range of values for each variable on each axis   From low to high, usually 0 to highest possible value   Mark a dot for each pair of scores on the graph 4 11/13/13   Make a sca`er plot based on these data: Par1cipant ACendance (0 to 7) MC Test Score (0 to 25) ID01 7 23 ID02 5 18 ID03 1 7 ID04 1 10 ID05 3 14 ID06 4 16 ID07 6 24 ID08 2 9 Score on Mul1ple Choice (Out of 25 Ques1ons)) 25 20 15 10 5 0 0 1 2 3 4 5 6 7 ACendance (Number of classes aCended) 5 11/13/13   Linear correla1on: pa`ern of scores follow a rela7vely straight line   Curvilinear correla1on: scores follow a non ­ linear pa`ern   No correla1on: no systema7c rela7onship between the variables   Direc&on of linear correla7ons:   Posi1ve: As one variable increases, the other increases ▪  Highs with highs ▪  Lows with lows   Nega1ve: As one variable increases, the other decreases ▪  Highs with lows ▪  Lows with highs   Strength (or “degree”) of l...
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