00:01
For this problem, the appropriate test is going to be a one -sided, one -sample, t -test.
00:17
I'll note that because we have a very large n at this point, it's close enough that we won't get significantly different results if we used a z or z distribution instead, but technically we should use a t -test because the population standard deviation for the population of interest is unknown.
00:34
I'll note that our hypotheses are as follows.
00:39
The null hypothesis would be that there is no negative impact, so that would be that the mean value for our group of interest, the prematurely born children, that the mean value is equal to that of the general population, mu equals 100.
00:54
Our alternate hypothesis will be the one -sided or left -tailed alternate, mu is less than 100.
01:00
We choose that because we're told that the investigator is interested only in the potential negative impact of premature birth.
01:07
So we know that we were told that our sample mean value is equal to 95 .8, our sample standard deviation is equal to 17 .5, and our sample size is equal to 100.
01:29
So using that, we calculate, well, or actually what i'll do is first i'll calculate my critical t value.
01:36
It does not specify a level of significance, but or actually let's see here, later on it starts talking about it for p less than 0 .05 and so on, so i'll say that we're going to be testing at alpha equals 0 .05 as our level of significance, and let's see here, it does actually seem like we're intended to use the p -value method rather than the critical value method...