So, what is a hypothesis? Well, it really is a statement about a population parameter or a sample statistic subject to verification. We have to go out, collect data points, analyze that and verify a question, and it is really about putting your research questions into clear perspective. Is there a difference between drug A and placebo? Is there a difference in means between patients in group A or group B? Now, prior to gathering any data, analyzing any kind of data, we really must be impartial. We must be neutral. We must state that there is no difference between the effects of drug A and placebo. There is no difference between the means of patients in group A and group B, and that is what we call the Null hypothesis. Now, as opposed to that we have the alternative hypothesis or the test hypothesis. That's when we say yes, there is a difference between the effects of drug A and placebo. Yes, there is a difference in the means. Between patients in group A, and patients in group B. Now, the short explanation of this. If we have a significant level of say 0.05, if we find a value of larger than 0.05, we do not reject the null hypothesis. You in fact accept the null hypothesis, you can't prove it. You just do not reject the null hypothesis, so your statement of neutrality stands. There is no difference in the use of drug A or placebo. There is no difference in the means between patients in group A and patients in group B. If you find a p-value that's less than your level of significance say this is 0.05. Then you reject that null hypothesis, and you accept the alternative hypothesis. Yes, drug 'A' is statistically significantly better than placebo. Yes there is a statistically significant difference between the mean and for patients in group A and group B. Now, really what happens there if we do reject the null hypothesis and accept the alternative hypothesis It's just that we found a result which has a low likelihood of having occurring. Remember our results that we get or the results from the study is just one of many others and it would be one that would occur very infrequently as opposed to ones that occur much more frequently, that's what we're after. Now, after stating the research question in hypothesis. That is when we consider the data points that need to be gathered to answer that, not before. That hypothesis is stated beforehand, before we go out and do collection. And we're going get to why that is so important, especially when it comes to calculating our p-value. Then we analyze those results and we get samples statistics which we then infer to a population so that we can use those results on a patient that we see in a hospital or in a clinic. We got quite a bit more to say about this alternative hypothesis. There are ways to state your alternative hypothesis. Which is very important and I reiterate, must be done before any data collection or any data analysis.