Example:
1. Do you think that this anxiety is a result of lack of experience in public speaking?
- yes
- no
Since it is nominal data, and more importantly categorical data, you should use chi square test using the SPSS tool.
Scoring a Yes/No survey is the easy part. You simply need to tally the Yes and No responses for each question for all the participants and divide it by the total number of participants to get the percentages of Yes and No for each question. Of course, if it is a mixed-methods study, you will have to score (evaluate) more qualitatively.
Regards,
Aira -
First, you might consider how this relates to sample size. Penn State has a lot of good online resources freely available. Here are a couple:
https://online.stat.psu.edu/stat415/lesson/6/6.2
https://online.stat.psu.edu/stat415/lesson/6/6.3
Note that simple random sampling is assumed here.
Another very good, classic resource would be W.G. Cochran, Sampling Techniques, 3rd ed, 1977, Wiley. I have a 1st edition, and that's good too.
Best wishes - Jim
PS - You should concentrate on a confidence interval. See
https://online.stat.psu.edu/stat415/lesson/5/5.1
A standard error, like a p-value, changes with sample size, but unlike a p-value, a standard error and confidence intervals are practical and interpretable. A lone p-value is virtually meaningless.
Total percentage of what?
I don't know what your research questions are, but it is likely that googling IRT will help.
IRT Daniel? Would that be item response theory from psychometrics? I'm not familiar. Perhaps an online reference would help.
Yes James R Knaub . Item response theory. A good intro is https://www.amazon.com/Response-Theory-Psychologists-Multivariate-Applications/dp/0805828192/ref=sr_1_3. It is also called latent trait modeling, more in UK (so I latent trait modelling). Part of the general linear latent variable model, used when the observed variables are binary and latent variables are metric. A good reference is https://www.amazon.com/Latent-Variable-Models-Factor-Analysis-ebook/dp/B005C65XUE/ref=sr_1_2, though this is more mathematical than the above reference.
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