Im just saying they do something. they may even increase your likelyhood of getting the flu. all we are not testing if they are actually good. we are just saying are they different than doing nothing. so like we did with all of our hypothesis tests, lets just assume the null . we are going to assume the null and given that assumption, figure out the problems. figure out if the likelyhood of getting data like this or more extreme is really low. and if it is really low, and if it is really low, we reject it. and in this test like in every hypothesis test, we need a significance level and the significance level we care about for whatever reason is 10% or 0.10 thats the significance level we care about. now to do this we need to calculate a chi square statistic for this contingency table. and to do this, we do something very similiar with what we did with the restaurant situation. we figure out assuming the null hypothesis, the expected results in each of these cells in each of these entries as a cell, thats what we do in excel. each of the entries in excel. each of the entries in a table. we figure out what each of the values would have been if you do assume the null hypothesis, we find the square distance from that expected value and you normalize it by the expected value ,take the sum of all those differences and if the square differences are really big, the probability of getting it would be really small and maybe we can reject the null hypothesis so lets just figure out how you can get the expected number . so we are assuming that the herbs do nothing. so if the herbs do nothing, we can just figure out that this whole population had nothing happen to them and the herbs were useless and so we can use this population sample,i shouldnt call this a population sample. we can use this sample right here to figure out the expected number of people who would get sick or not sick so over here, we have 80 out of 380 did not get sick. i should be careful here. i just said population but we havent sampled the whole universe of people taking this herb so this is a sample. i dont want to confuse you . i am using population in more of a conversational sense rather than a statistical sense. any way in all of our sample, we are using all of the data because we are assuming that there is no difference so we might aswell use all of the data to find the frequency of getting sick and not getting sick so 80 divided by 380 didnot get sick so thats 21 percent. 