Question

I am trying to find an appropriate statistical test to run for a research study using someone else's gathered data (so that no IRB process is needed). In their data they present:

Likelihood of Falling Asleep:

Never 17

Seldom 22

Moderate 15

High 12

Use of napping during duty:

Never 27

Rarely 19

Sometimes 16

Often 4

To simplify I think that it would probably be beneficial to group these as:

Likelihood of Falling Asleep

Never: 17

Yes: 49

Use of Napping During Duty:

Never: 27

Yes: 39

So variables are:

Likelihood of Falling Asleep

Use of Naps on Duty

Hypothesis:

Null hypothesis: Likelihood of Falling Asleep and variable Use of napping during duty are independent of each other.

Alternative hypothesis: Likelihood of Falling Asleep and variable Use of napping during duty are not independent.

Both of these seem to be independent variables, but is there a way to show a relationship (or lack thereof) without a dependent variable. In this case the dependent variable could be "pilot" of which 66 were surveyed for the study that I am taking the data from. Trying accurately to show whether or not the likelihood of falling asleep in the cockpit is related to whether or not the pilot naps on duty outside of the cockpit.

I think a Chi Square would be a way to attempt to show whether or not a relationship exists, however I get stuck when I input data into stat crunch as a chi square compares the actual data to what we expect should happen (in this case 33/33). Is there a good way to test the two against each other or to show possible relationships?

Thanks!

Answer 1