How do I compute the test value in the hypothesis setting?
There are 3 ways to know, and or the first 2 it depends on whether you know what the population variance is.
If the population variance is known, z-test is always used. If n is greater than or equal to 30, z-test must also always be used.
If n30, z-test will only be used if the population standard deviation is known.
On the other hand, if n30 and population standard deviation is unknown then you must use the t-test.
Are there other ways to compute the test value?
There is also a third way, it is called the Central Limit Theorem.
Unlike the other methods, Central Limit Theorem may be used even if the population is not normally or nearly normally distributed.
Does the sample size need to be large?
Yes. It does not apply if the if the sample size is small. This is because there must be a stricter assumption on the population to give the test validity
So if n is greater than or equal to 30, then z-test will be used. And if n30 then it will be determined on whether the population standard deviation is known.
If it is known, z-test will be used. If it is not, then t-test will be used.
As long as the sample size is large enough, Central Limit Theorem can be used.
It is mostly used, however, if the population is not evenly distributed.
Sukurta daugiau nei 30 milijonų siužetinių lentelių