Linear Regression is a process by which the formula of a line of "best fit" is found for a set of data. The correlation coefficient is a measure of the "goodness" of the fit. The correlation coefficient can be tested for significance. Consider the data set shown below and test for correlation significance at the 5% level, letting:
:
:
| x | 0 | 1 | 2 | 3 | 5 |
| y | 3 | 4 | 8 | 9 | 10 |
First enter the x's in 
and the y's in 
.
Next press STAT, right arrow to TESTS, down arrow to E:LinRegTTest.
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Make sure that Xlist is ,
Ylist is
and frequency is 1. Select .
Then arrow down to Calculate, then press ENTER.
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The first result screen shows that p
= 0.0236, and by pressing the down arrow, we see that r
= 0.9264. Since p = 0.0235 < 0.05, we can reject .
Thus there is a significant linear relationship between x and y.
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