The Anscombe data (strongly recommended): SAS data PW; input x1 y1 x2 y2 x3 y3 x4 y4; cards; 10 8.04 10 9.14 10 7.46 8 6.58 8 6.95 8 8.14 8 6.77 8 5.76 13 7.58 13 8.74 13 12.74 8 7.7 9 8.81 9 8.77 9 7.11 8 8.84 11 8.33 11 9.26 11 7.81 8 8.47 14 9.96 14 8.10 14 8.84 8 7.04 6 7.24 6 6.13 6 6.08 8 5.25 4 4.26 4 3.10 4 5.39 19 12.50 12 10.84 12 9.13 12 8.15 8 5.56 7 4.82 7 7.26 7 6.42 8 7.91 5 5.68 5 4.74 5 5.73 8 6.89 ; proc reg simple; A: model y1 = x1; plot y1 * x1; B: model y2 = x2; plot y2 * x2; C: model y3 = x3; plot y3 * x3; D: model y4 = x4; plot y4 * x4; run;
SPSS: Bring CORR_REGR.SAV (available at http://core.ecu.edu/psyc/wuenschk/SPSS/SPSS-Data.htm ) into SPSS. From the Data Editor, click Data, Split File, Organize Output by Groups, and scoot Set into the "Organize output by groups" box. Click Analyze, Regression, Linear. Scoot Y into the Dependent box and X into the Independent(s) box. Click Stat and ask for Descriptives (Estimates and Model Fit should already be selected). Click Continue, OK. Click Graphs, Scatter, Simple. Identify Y as the Y variable and X as the X variable. Click OK. Look at the output. For each of the data sets, the mean on X is 9, the mean on Y is 7.5, the standard deviation for X is 3.32, the standard deviation for Y is 2.03, the r is .816, and the regression equation is Y = 3 + .5X - but now look at the plots. In Set A, we have a plot that looks about like what we would expect for a moderate to large positive correlation. In set B we see that the relationship is really curvilinear, and that the data could be fit much better with a curved line (a polynomial function, quadratic, would fit them well). In Set C we see that, with the exception of one outlier, the relationship is nearly perfect linear. In set D we see that the relationship would be zero if we eliminated the one extreme outlier -- with no variance in X, there can be no covariance with Y. Also of possible interest: http://core.ecu.edu/psyc/wuenschk/StatHelp/Linear-Games.htm Cheers, Karl W. -----Original Message----- From: Mike Palij [mailto:[email protected]] Sent: Thursday, February 18, 2010 10:04 PM To: Teaching in the Psychological Sciences (TIPS) Cc: Mike Palij Subject: [tips] interpreting correlations On Thu, 18 Feb 2010 18:17:22 -0800, Blaine Peden wrote: >I am looking for an assignment or exercise in which there are >several correlation coefficients and the task is to interpret the >relationships between pairs of variables in the matrix. if you >have an exercise and data set to share, I would be most appreciative Do you mean something like the old Anscombe correlation dataset? The reference for the Anscombe article and the dataset as well as an old style SPSS syntax (the plot command no longer works) is available at this website from an old Ed-stat post: http://www.math.yorku.ca/Who/Faculty/Monette/Ed-stat/0151.html The author of the post might be able to give you more info. ;-) -Mike Palij New York University [email protected] --- You are currently subscribed to tips as: [email protected]. To unsubscribe click here: http://fsulist.frostburg.edu/u?id=13060.c78b93d4d09ef6235e9d494b3534420e&n=T&l=tips&o=708 or send a blank email to leave-708-13060.c78b93d4d09ef6235e9d494b35344...@fsulist.frostburg.edu --- You are currently subscribed to tips as: [email protected]. To unsubscribe click here: http://fsulist.frostburg.edu/u?id=13090.68da6e6e5325aa33287ff385b70df5d5&n=T&l=tips&o=710 or send a blank email to leave-710-13090.68da6e6e5325aa33287ff385b70df...@fsulist.frostburg.edu
