There is an introductory example of two datasets with equal R^2
(and possibly with equal coefficients?) but with
markedly different residuals. I can't for the life of me
remember the author's name that is associated with these
data, or where to find them.
Any help would be appreciated.
Bruce
[EMAIL PROTECTED] wrote:
There is an introductory example of two datasets with equal R^2
(and possibly with equal coefficients?) but with
markedly different residuals. I can't for the life of me
remember the author's name that is associated with these
data, or where to find them.
found the data ... entered it ... here is some stuff on it
===
Row X1 Y1 X2 Y2 X3 Y3 X4 Y4
1 108.04 10 9.14 107.46 86.58
2 86.95 8 8.14 86.77 85.76
3 137.58 13
Colleagues: Here are the 4 pairs of X,Y variables from Anscombe's 1973
American Statistician paper.
(The columns, in order, are X1, Y1, X2, Y2, etc. Calculate the means and
SDs for each variable, and r for each pair. This is a nice example to
emphasize the importance of plotting data before
These data can be found, with SAS code to describe them, at the bottom of my
CorrRegr program on the page at:
http://core.ecu.edu/psyc/wuenschk/SAS/SAS-Programs.htm
++ Karl L. Wuensch, Department of Psychology, East
I would like to enter the arena.
I see the original question as two questions, one about
probability in a general sense, and the second about probability as used within
Bayes Theorem. This is in line with the historical arguments.
Most statisticians (from Fisher down to the present)