## Q: Preference choice data analysis

### Q: Preference choice data analysis

I'm trying to figure out how to analyze/the best way to analyze data from
the following type of question:

Which of the following 2 superheroes do you like better:  superman or
batman?

__ superman
__ batman
__ like both the same

My data looks something like this:

3 / 25% superman
4 / 33% batman
5 / 42% like both the same

The hypothesis I'd like to test is:

H0:  Both superman and batman are liked equally.

If reject H0:  Batman is liked more than superman.

My suspicion is that given n=12, I cannot reject H0.

What test/statistic do I need to test this hypothesis?

Tony

### Q: Preference choice data analysis

Quote:> I'm trying to figure out how to analyze/the best way to analyze data from
> the following type of question:

> Which of the following 2 superheroes do you like better:  superman or
> batman?

> __ superman
> __ batman
> __ like both the same

> My data looks something like this:

> 3 / 25% superman
> 4 / 33% batman
> 5 / 42% like both the same

> The hypothesis I'd like to test is:

> H0:  Both superman and batman are liked equally.

> If reject H0:  Batman is liked more than superman.

> My suspicion is that given n=12, I cannot reject H0.

Definitely,  n=12   hardly offers any test.

For n=120,  you might  do a  "test for proportions."
That might be a t-test  using the 4 separate numbers.
The 'tied'  sentiments do not contribute to the difference,
but they *do*  help make it logical to consider the proportions
as being (to some extent)  independent -- instead of being
100%  minus < the other>.

Actually, using the 2 numbers, the logical test would
be the comparison that the split was 50%  so it might
be done as a binomial test:  Is the parameter  0.50?

After all is said, n=12  is too small
for any test be show a difference,
unless there was a clear preponderance.
And then you  would probably have to be

--

http://www.pitt.edu/~wpilib/index.html
"Taxes are the price we pay for civilization."  Justice Holmes.

Hi,
I am in search of an expert for table analysis based on PROC FREQ,
especially for higher order tables. While writing a tabular overview about
tests for table analysis (just one page, you'll love it), I noticed a
somewhat confusing presentation Chapt. 4 (2 x r, s x 2 tables) in Stokes et
al., my favourite source. I contacted the authors, however SAS Institute
forwarded that it may take a few weeks for her to respond. Well, I cannot
wait that long, so I would like to get in touch with a table analysis expert
to make sure that this overview is free of flaws, and if interested, to
confirm or (better) to reject my considerations. Anybody interested in table
analysis?
Annette