Suppose you are interested in seeing whether the total number of days students are absent from high school correlates with their grades. You obtain school records that list the total absences and average grades (on a percentage scale) for 100 graduating seniors.

You decide to use the computational formula to calculate the Pearson correlation between the total number of absences and average grades. To do so, you call the total number of absences X and the average grades Y. Then, you add up your data values (X and Y), add up the squares of your data values (X and Y), and add up the products of your data values (XY). The following table summarizes your results:

X	460
Y	8,060
X	3,446
Y	659,226
XY	36,477

The sum of squares for the total number of absences is SSxx= _________.

The sum of squares for average grades is SSyy= ________.

The sum of products for the total number of absences and average grades is SP = .________

The Pearson correlation coefficient is r = __________.

Suppose you want to predict average grades from the total number of absences among students. The coefficient of determination is r = ________ , indicating that _________ of the variability in the average grades can be explained by the relationship between the average grades and the total number of absences.

When doing your analysis, suppose that, in addition to having data for the total number of absences for these students, you have data for the total number of days students attended school. You'd expect the correlation between the total number of days students attended school and the total number of absences to be ________ and the correlation between the total number of days students attended school and average grades to be __________ .