Specifying a null hypothesis refers to a statistical hypothesis that claims there is no statistical significance in a collection of data between characteristics of a population or data-generating population. The alternative hypothesis specifies there is a difference between the two variables. It states that a population parameter does not equal a specified value. The benefit of being so specific about these hypotheses is that we know what we are looking for and what we want to see happen in the experiment. We want a good outcome in the end. Having a hypothesis can determine the focus and direction of research and this helps formulate the reason for the experiment. It is better for a business to reject the null hypothesis. The null hypothesis is not always "true", you are making an assumption, a good guess on what you think may happen. It may not be the outcome of the experiment, but you are just assuming based on your own thoughts. The alternative is better since there is proof there is a relationship between the variables.

What do you thing are the disadvantages to setting up a statistical hypothesis?