July At The Multiplex Analysis
This means, more than likely, the accurate percentage of unhappy customers in your theater consortium’s area is at least 10%.
The null statement is different to our sample result. We have to point out, the first survey is not successful enough to prove the percentage is either smaller than 10%, or at least 10%
Type II Error in the First Survey
Even though the hypothesis test result shows the null statement is true, it still has the possibility that the null statement is not true. Technically, we call this kind of possibility Type II Error.
Here are two kinds of errors in hypothesis tests. They are Type I Error (α) and Type II Error (β). The Type I error will be discussed in the second survey’s conclusion.
Type II Error (β) is the possibility of wrongful accepting of the false null statement in a hypothesis test. Because the sample size is not actually the population, it’s a good possibility to get a polarized sample. So, Type II Error can always exist in the samplings whose sample size is much smaller than the