00:01
So for the first part of the problem here, we're basically trying to answer why might r equals 0 .72 not be significant, we can figure out we can figure this out using a table of critical values.
00:39
So if we look at our table of critical values, we can see that, for instance, at four degrees of freedom, even 0 .729, or pardon me, we could say that at four degrees of freedom, with a zero point or with a 0 .1 level of significance, 0 .72 is not sufficient to be considered significant.
01:07
In fact, we would have to go up to let's see here, we'd have to go up to 10 degrees of freedom, in order for it to be guaranteed significant.
01:20
So we can say that we can only that r equals 0 .72 is only guaranteed to be significant, if alpha is greater than or equal to 0 .01.
01:49
And our sample size n is greater than or equal to 12.
01:56
Below that threshold, we cannot guarantee that 0 .72 is significant.
02:05
So for instance, ie, if n was equal to nine, and alpha is equal to 0 .02, for a two tailed test, then the critical r value is 0 .75.
02:24
Therefore, r equals 0 .72 is not significant, joel just abbreviate as sig.
02:34
So that would be one example for how we might have a relatively high correlation value, which is considered to not be significant.
02:43
Then, alternatively, we have r equals 0 .32, leading to a result that is significant...