But there you have a probabilistically formulated null hypothesis (coin is fair, students perform at chance level). In the equids example, the null hypothesis is that the probability of sampling a zebra is 0, which is disproven by simply pointing out that you, in fact, sampled some zebras. It makes no sense to calculate a p-value.
I have no idea what Fisher’s test is supposed to do here. Show a correlation between the property of being a zebra and the property of being in the real, as opposed to the imaginary, sample? … That’s meaningless.
Agreed! Perhaps Fisher’s test was used because it can deal with small expected values in cells of contingency tables (where chi-square is flawed) but “small” must still > 0.
Which just made me think that it would have been hilarious if Dr. Yagami had realised this and continued by saying that because of it, and in order to make the statistical test applicable, he is going to add an amount of random noise.
But there you have a probabilistically formulated null hypothesis (coin is fair, students perform at chance level). In the equids example, the null hypothesis is that the probability of sampling a zebra is 0, which is disproven by simply pointing out that you, in fact, sampled some zebras. It makes no sense to calculate a p-value.
I have no idea what Fisher’s test is supposed to do here. Show a correlation between the property of being a zebra and the property of being in the real, as opposed to the imaginary, sample? … That’s meaningless.
Agreed! Perhaps Fisher’s test was used because it can deal with small expected values in cells of contingency tables (where chi-square is flawed) but “small” must still > 0.
Which just made me think that it would have been hilarious if Dr. Yagami had realised this and continued by saying that because of it, and in order to make the statistical test applicable, he is going to add an amount of random noise.