00:01
Once again, welcome to new problem.
00:04
This time we're dealing with hypothesis testing.
00:09
We're dealing with hypothesis testing.
00:13
And when it comes to hypothesis testing, we have a one sample t test, and this is for means, one sample t test for means.
00:32
For one sample t test is x bar minus mu, s of a radical n, where mu is the hypothesized population mean, and n is the sample size, s is the sample, standard deviation.
01:11
And x bar is the sample mean.
01:18
We're looking at a new problem involving cancer survival times, and this is bronchial cancer.
01:27
And these are the days of survival after treatment.
01:36
So days of survival after treatment.
01:39
And in part a, we want to determine at alpha equals to .10 if these times are different from 200 days.
01:50
So that simply means that we're going to set up an nile hypothesis.
01:57
And then we're also going to set up the alternative hypotheses, which a claim is different.
02:06
It's different from 200 days.
02:15
And then the test statistic is x bar minus mu, s of radical n...