I have a research project and I am really confused on what I should do with the data.

I asked people to complete a survey. The survey had 10 qualities that people look for in their partners. I asked every person to rank the 10 qualities from 1-10, with 1 the most important and 10 the least important. My sample size is 149.

I now have an Excel spreadsheet of this information. I have 149 rows and 10 columns. Each column is one of the qualities and I have just gone across and entered in what how each person ranked each quality, from 1 to 10.

e.g. A1=2, B1=5, C1=10, D1=6, E1=7, F1=1, G1=3, H1=9, I1=4, J1=8 (which is the data from one person's response to the survey)

What I want to test is how statistically significant each quality is in determining what people think is important in their partners.

To do that, I need to determine what my explanatory and dependent variables are. I seem to have 10 explanatory variables (the qualities) but I have no idea what to do about the dependent variable.

I eventually have to import all this data into Eviews and I know how to use Eviews, I just have no idea how I should set the data up. One of my issues is that the numbers I have put into Excel aren't really numbers, they're rankings... and I don't know what to do.

Am I thinking about this in the entirely wrong way? I have no idea what I'm doing.

Also, am I correct in thinking that this would be a Poisson regression model? I don't really know what to do because my variables are qualitative not quantitative... the numbers aren't numbers, they are ranks.

What I want to test is how statistically significant each quality is in determining what people think is important in their partners.
As far as I can see the only thing you can do is to determine a rank order of the variables (qualities).
Regarding statistiscal tests, Friedman for a global test and/or Wilcoxon signed rank test for pairwise
comparisons of qualities might apply.

regards

K.

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