(There should be instructions, somewhere in the owners manual for your graphing calculator, for finding this information. A correlation value close to zero means that we're kidding ourselves if we think there's really a relationship (that is, an equation for the dots) of the type we're looking for. On the other hand, if the value is between −0.5 and 0.5 (or between −0.3 and +0.3, depending on the textbook), then the match is judged to be pretty poor. If the correlation value (being the " r" value that our calculators spit out) is between 0.8 and 1, or else between −1 and −0.8, then the match is judged to be pretty good. The closer these correlation values are to 1 (or to −1), the better a fit our regression equation is to the data values. The values for correlation evaluations are between −1 and +1. These diagnostic tools measure the degree to which the regression equation matches the scatterplot. If we're supposed to report how "good" a given regression is (that is, how well the equation you've generated matches the data points they gave you), then we'll want to figure out how to find the " r", " r 2", and/or " R 2" values in our calculators. (Consult your owners manual or calculator web sites for specific information on doing regressions with your particular calculator model.) If you're working by hand, you and your classmates will get slightly different answers if you're using calculators, you'll all get the same answer. The calculator will give you "the" regression line. Doing regressions properly is a difficult and technical process, but your graphing calculator has been programmed with the necessary formulas and has the memory to crunch the many numbers. Most likely, though, you'll be doing regressions in your calculator.
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