Use the following four data sets for problem 1. Be aware that this is a very interesting series of data sets with some special properties. I do not have data files for these data, so you'll need to enter it by hand. If you want to challenge yourself, try to copy and paste this data into an excel sheet or text file and then bring it in through SPSS.
Y X Y X Y X Y X
(a) For each of the four data sets separately: Calculate the Pearson r and the regression equation, = b_{0} + b_{1}X; Calculate R^{2} and associated test of significance. Test b_{1} for significance. Briefly write what you would conclude about the comparison of these datasets from these analyses.
(b) For data set 1 and data set 3, compute the outlier diagnostics. Are there are any outliers? If so, please explain.
(c) Comment on what lessons have you learned (or should have learned) from this problem. That is, why did I pick these data and ask you to specifically do steps a, &b? When looking at the data analysis as a whole, what lesson should this question teach?