00:01
So i see that you need help with this question and it states that a media researcher wanted to see if there was a difference in the ages of viewers of three late night tv talk shows.
00:14
The three random samples of viewers were selected.
00:18
At a 5 % level of significance, is there a difference in the mean ages of the viewers of these talk show hosts? so first of all, we're going to state the hypothesis and identify the claim.
00:30
So the null hypothesis is that there is no difference in the mean ages of viewers of the talk show hosts.
00:44
And then the alternative hypothesis is that there is a significant difference.
00:51
There is a difference in the mean ages of the viewers of the talk show hosts.
01:00
The first thing that we are going to do is, is calculate the p value.
01:15
So in order to calculate the p value, we have to calculate the mean of each one of the values.
01:23
So the mean of jimmy kimmel's is 50 .17 and then of stephen colbert is 48 .33 and of jimmy fallon is 35 .17.
01:42
And then what we have to do next is when we set up our nova table, you also have to calculate your standard deviation.
01:51
And so i'm going to put the standard deviations right here.
01:55
So for the first one, it's 4 .17.
01:59
I hate when the 4 does that.
02:00
4 .17.
02:03
And then it's 1 .86.
02:08
And then it's 4 .17.
02:14
Okay.
02:15
And then when you're doing this, i'm just going to insert my nova table.
02:24
And you can use any type of data out there to do this...