# Null hypothesis with multiple equally important hypothesis

I am working on an assignment for a course in statistics, and a part of the assignment is to give the null hypothesis of an experiment. The experiment is as followed (short summary):

A company is testing 3 interfaces for a website. They test the interfaces with 15 students, 5 for each interface, and all 5 have a different computer knowledge level. They are all given the same task and the time it takes for each of them to complete the task is the data we're using.

I know need to find the null hypothesis of interest. As far as I understand null hypothesis and the alternative hypothesis should be 2 competing propositions. However, as far as I can tell I have 3 proposition: interface 1 is better, interface 2 is better and interface 3 is better.

What null hypothesis should I have here and why?

• Even before getting into the issue of hypothesis testing, how do the skill levels of the $5$ students using Interface $1$ differ from the skill levels of the $5$ students using Interface $2$ and from the skill levels of the $5$ students using Interface $3$? The data gathered might not be very useful in arriving at any defensible conclusions about which Interface is "better" if Interface $3$ required the least time but was also assigned to students who happened to be more skilled than those who used the other Interfaces. Jan 12, 2012 at 14:09
This information should be in your textbook and/or course notes. There are more than 1 testing procedure that creates a single overall hypothesis to test (then you can use follow-up or post hoc procedures to look at additional comparisons of interest). Two commonly used (and taught in early stats classes) methods are Analysis of Variance (ANOVA or AOV) and $\chi^2$ tests on two-way tables (sometimes called contingency tables). One of those may be what the question is expecting you to use, look the details up in your textbook (or wikipedia, or some other source) and see what hypotheses are used in the examples.