00:01
So we're going to suppose a researcher is trying to understand whether people who purchase fast food hamburgers would be willing to pay more if the hamburger comes with a free whistle.
00:10
Prior research suggests the mean amount of customers say they are willing to pay for a hamburger as mu is 3 .68 and the population standard deviation is 0 .7.
00:24
And the researcher plans to conduct a study very similar to the prior research by selecting a sample of customers and asking them how much they're willing to pay for their.
00:32
Hamburger.
00:32
And before asking, however, he will tell the customer about the free whistle that will come with a hamburger.
00:38
And so this is the key part.
00:40
The researchers, null hypothesis, so the null hypothesis is that the mean amount the customers are willing to pay when they are told about the free whistle is no different than the amount customers are willing to pay when they are not told they will receive a free whistle.
00:58
So we've got the mean, we'll say free whistle.
01:06
Mean of the f.
01:06
No difference means they're equal, would mean the mean nf, no free whistle, that they're the same.
01:13
That means the alternative is the thing we're testing for is that these means are not equal.
01:27
Statistics has lots of subscript that just help us identify what the variables mean.
01:31
So nf means no free whistle, the mean with no free whistle.
01:38
And so the researchers sample of 49 customers, that's the n sample size, which is 49.
01:45
Has a sample mean of 4 .04.
01:48
You might see this as x bar sometimes.
01:52
And the test statistic for the sample mean is 3 .6.
01:56
And so what this is, this is the z value.
02:07
It's a test statistic and it's z because we know the population, same deviation.
02:11
And using the significance level of alpha of 0 .05, which of the following is the most appropriate statement of the result? and this is a two -tailed test.
02:23
And the reason for that is because this, we're saying the null hypothesis, the alternative hypothesis is not equal.
02:31
So it could be less, it could be more.
02:32
We're not really claiming which, just above or below, some significant amount.
02:37
So it tells us this critical region is plus or minus 1 .96.
02:41
So what that means, here's our normal curve.
02:46
And these are our critical values, negative 1 .96 and 1 .96.
02:51
These are the z scores.
02:56
And so what it means is the area to the left of the negative 1 .96 is 0 .025.
03:03
And the area to the right of 1 .96 is 0 .25 as well...