00:01
In this exercise, we're given a hypothesis test for a population mean, where the no hypothesis is that the mean is 10.
00:08
The alternative hypothesis is that it is greater than 10.
00:12
We're also told that the standard deviation of the population is unknown, and that a sample has been taken from this population of size 15.
00:21
And for each of a, b, and c, we're asked to approximate the p value given a specific test statistic from the sample.
00:32
So in a, we're told to assume that the test statistic was 2 .05.
00:41
Now, examining the alternative hypothesis, we can see that this is a one -tailed or upper -tailed test, which would mean that the p -value is equal to the probability that we were to get a test statistic bigger than 2 .05.
01:03
And we can look this up in a t -table.
01:05
First thing we'll do is note that the degrees of freedom is going to be 14, and so we can look up 2 .05 in the roll for 14 degrees of freedom.
01:18
It's going to come between these two cells, which means that the upper -tailed area is going to be between 0 .025 and 0 .05.
01:49
Then for part b, i told that the test statistic is minus 1 .84.
02:09
So if we return to the t -table, well, before we do that, the t -table has positive, values in it.
02:19
So we can also say that this is equal to the probability that t is less than positive 1 .84...