I'm thinking that yes, if you insist on using 'error' as a nominal, or categorical, measurement, then it will be very hard to analytically draw much conclusion with it.

I'd suggest you look more closely at what 'error' means here. Could it be number of mistakes (in typing?), or some ranking of degree of seriousness of them? Perhaps a ranking of the ease of making a specific mistake could give you some kind of rating value for them. (keeping in mind that seriousness of an error does not = ease of making it - those are two different measurements.) Once you have an ordinal scale, and work a little to make it mostly linear, or an interval scale, then you can take off.

Jay

DG wrote:

Hi

For my thesis I am planning a 3X3X3 within subjects experiment. The
experimental task requires subjects to count the number of times a
particular alphabet appears on the monitor and enter it using a keyboard
(depending on the number of times the alphabet appears). I have two
dependent variables - error in response and number of subtasks completed
(ranging from 1 to 5) in a time limit of 15 seconds.  My research hypothesis
is that performance (speed and accuracy) will be better when the monitor is
at a certain distance (0.7m) as compared to when it is at another distance
(2.5 m).

For the error in response dependent variable will it be nominal data? If it
is nominal data then how can I verify the hypothesis. What test would I use?

Thanks
DG



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