**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.**

Make sure that Xlist is ,
Ylist is
and frequency is 1. Select .
Then arrow down to **Calculate,** then press **ENTER. **

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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