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EDF 5400. Albert Oosterhof September 27 and October 2. Create the scatterplot for these scores, then plot the regression line.... Supplement 8. Adding the regression line to the scatterplot. A scatterplot and regression line typically involves more than five cases.
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EDF 5400 Albert OosterhofSeptember 27 and October 2
Create the scatterplot for these scores, then plot the regression line....Supplement 8
A scatterplot and regression line typically involves more than five cases...
Here is the regression equation for predicting posttest scores from pretest scoresSupplement 9
We will switch to z-scores to show how the slope (b) and intercept (a) are determinedSupplement 9
Interpret predicted Y scores with respect to standard deviations from the mean?
What would we predict Y to beif the correlation had been....... r = .50 and X was 1.0 SD above the mean? r = .50 and X was 2.0 SDs above the mean? r = .50 and X was 3.0 SDs above the mean? r = .50 and X was 1.0 SD below the mean? r = .50 and X was 3.0 SDs below the mean? r = .50 and X was 0.5 SDs above the mean? r = .50 and X was 0.0 SDs above the mean?
What would we predict Y to beif the correlation had been....... r = .10 and X was 1.0 SD above the mean? r = .10 and X was 3.0 SDs above the mean? r = .10 and X was 1.0 SD below the mean? r = .10 and X was 0.0 SDs above the mean?
What would we predict Y to beif the correlation had been....... r = 1.00 and X was 1.0 SD above the mean? r = 1.00 and X was 3.0 SDs above the mean? r = 1.00 and X was 1.0 SD below the mean? r = 1.00 and X was 0.0 SDs above the mean?
Redundant: What would we predict Y to beif the correlation had been....... • r = .50 and X was 1.0 SD above the mean?
Redundant: What would we predict Y to beif the correlation had been....... r = .50 and X was 1.0 SD above the mean? What if
Redundant: What would we predict Y to beif the correlation had been....... r = .50 and X was 1.0 SD above the mean? What if r = .50 and X was 3.0 SDs above the mean? What if
What would we predict Y to be if ...... r = .10 and X was 1.0 SD above the mean? r = 1.00 and X was 1.0 SD above the mean? r = 1.00 and X was 3.0 SDs above the mean? r = 0.50 and X was 1.0 SD below the mean? r = 0.50 and X was 2.0 SDs above the mean? r = 0.50 and X was at the mean?
Regression towards the mean... +3 +3 …if r = +1.00 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +1.00 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +1.00 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +0.75 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +0.75 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +0.75 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +0.50 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +0.50 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
Regression towards the mean... +3 +3 …if r = +0.50 +2 +2 +1 +1 0 0 -1 -1 -2 -2 -3 -3
4 3 2 1 Z-score: WEIGHT 0 -1 -2 -3 -3 -2 -1 0 1 2 3 Z-score: HEIGHT What we have been doing!
For r = .75, sy = 4.47 and sx = 2.24, slope is adjusted from .75 to b = ?
For r = .75, sy = 4.47 and sx = 2.24, slope is adjusted from .75 to b = ?
If b = 1.5, a = ?Take advantage of what we know about regression…...
If b = 1.5, a = ?Take advantage of what we know about regression…... r = .75 and zx = .00, predicted zy = ? r = .75 and zx = .00, predicted zy = .00 r = 1.00 and zx = .00, predicted zy = ? r = 1.00 and zx = .00, predicted zy = .00 r = .00 and zx = .00, predicted zy = ? r = .00 and zx = .00, predicted zy = .00
If b = 1.5, a = ?Taking advantage of what we know about regression, and remembering that if zX = 0, predicted zY = .00Supplement 9, 2nd page – Example 1