Which Statistical test should I use?
Hi guys, having a real issue picking the right stats test and would be grateful of another set of eyes.
I set up a survey so participants (all from the same origin, so within groups) had to assign values of numerical preference to various web visitor interactions, lets say:
Reading the content
Sharing the website with others (via Facebook, Twitter, etc)
Commenting on the content
Reading further related content on the website
Buying Products
Contacting the webmaster (for a quote or service)
Clicking Adverts
They had to assign a value between 0 and 100 to each of the above statements, while the total sum of all of these statements must also add up to 100.
My hypothesis (h1) is that there will be a significant difference between each of the listed 7 items in terms of score, but I don’t know which way (two-tailed)
Which is the correct test for this enviroment?
Thanks
The null hypothesis is that the expected value for each interaction is equal to one another, so that the expected count for each is 100 / 7 = 14.2857143.
The alternative hypothesis is that they are not equal to one another.
A chi-square test for goodness-of-fit is appropriate for this scenario, where chi square = the summation of (observed count – expected count)^2 / expected count for all web interactions. Chi-square tests are always one-sided tests, however.
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