factory. Enter CATALOG and scroll down to “Diagnostic On.” Press ENTER twice. Now you are
ready to find r .
Assuming you have entered the x - and y -values in L1 and L2 , enter STAT CALC LinReg(a +bx)
[that’s STAT CALC 8 on the TI-83/84] and press ENTER . Then enter L1, L2 and press ENTER . You
should get a screen that looks like this (using the data from the Study Time vs. Score on Test study):(Note that reversing L1 and L2 in this operation—entering STAT CALC LinReg(a +bx) L2, L1 —
will change a and b but will not change r since order doesn’t matter in correlation.) If you compare
this with the computer output above, you will see that it contains some of the same data, including both
r and r 2 . At the moment, all you care about in this printout is the value of r .Correlation and Causation
Two variables, x and y , may have a strong correlation, but you need to take care not to interpret that as
causation. That is, just because two things seem to go together does not mean that one caused the other—
some third variable may be influencing them both. Seeing a fire truck at almost every fire doesn’t mean
that fire trucks cause fires.
example: Consider the following dataset that shows the increase in the number of Methodist
ministers and the increase in the amount of imported Cuban rum from 1860 to 1940.