I'm doing a research and I have some concerns, and I'd appreciate your kind assistance on them.

Basically, I'm designing an instrument to measure something (a single dependent variable), and I'm going to conduct many statistical analyses, such as multiple regression, factor analysis, etc. As part of such analyses, I'll also be looking at basic statistics, such as correlations and statistical significance.

The problem is that all my independent variables are categorical, mostly ordinal (5-points likert scale), with some nominal variables, too. My concern is that I've been asked to strictly make use of parametric tests on my data, although they are clearly non-parametric. For example, testing for statistical significance by applying t-test on a question with 5-likert scale responses, which I personally think does not make any sense.

Furthermore, I tried to look for alternative non-parametric tests, but they can be very challenging, let alone their interpretations (especially to someone who is only uses SPSS). Given these circumstances: If I must use parametric tests to analyze non-parametric data, any tips on the possibility of maybe reducing the

*unreliability*of results? (perhaps increasing likert scale points from 5 to 7, for example?)

Thank you very much,

Tx