In this article which explains types of t-tests
for “Independent Two-Sample t-test” example:
We can confirm that the t-statistic is again less than the t-critical value so we fail to reject the null hypothesis. Hence, we can conclude that there is no difference between the mean screen size of both samples.
Null hypothesis was that the average screen size of the sample does not differ from 10 cm.
Alternate hypothesis was that the average screen size differs. And also the data is only about sizes of screens.
Why can't null hypothesis be that the average screen size differs. and alternate hypothesis, that the average screen size doesn't differ.
Not just this example, in every article I have read, every author only told what was chosen for null and alternate hypothesis. But, no one talked about why they chose what they chose. I always think that, why can’t the statement chosen for alternate hypothesis be chosen for null hypothesis and vice versa. And the data won’t have much information too. It’s always up to the article writer to what to choose for null and alternate hypothesis.
So, my question is, are there some set of rules, that have to be followed to choose a statement/condition for hypothesis. Or what actually causes a particular statement to be chosen for hypothesis. Or am I missing something.
