How to State the Null Hypothesis in Statistics: Part Two

In the previous post on How to State the Null Hypothesis, I explained how to convert a word problem into a hypothesis statement if you have an idea about what the result will be (i.e. you think you know if the mean will be greater or smaller). But how do you state the null hypothesis if you have no idea about the experiment outcome?

Sample Problem: A researcher is studying the effects of radical exercise program on knee surgery patients. There is a good chance the therapy will improve recovery time, but there’s also the possibility it will make it worse. Average recovery times for knee surgery patients is 8.2 weeks.

Step 1: State what will happen if the experiment doesn’t make any difference. That’s the null hypothesis–that nothing will happen. In this experiment, if nothing happens, then the recovery time will stay at 8.2 weeks.

H0: μ = 8.2

Broken down into English, that’s H0 (The null hypothesis): μ (the average) =(is equal to) 8.2

Step 2: Figure out the alternate hypothesis. The alternate hypothesis is the opposite of the null hypothesis. In other words, what happens if our experiment makes a difference?

H1: μ ≠ 8.2

In English again, that’s H1 (The  alternate hypothesis): μ (the average) ≠ (is not equal to) 8.2

That’s it!

3 thoughts on “How to State the Null Hypothesis in Statistics: Part Two”

1. Angie Widdows

Even with the example, I still have problems with these types of questions. I think I might be trying to read to much into how to do it.

2. Vanessa DuBarry

I agree with Angie with these type of problems start to hesistate and think to much but this example helped i just have to read it over again and practice to get it.