SPSS - what test to run with MANY different variables

[klykk]

Hello, I need help deciding what statistical test to run (and advice on how to run properly) for many different variables. In this case the researcher wants to know how demographics influence test scores, there are 6 independent variables (age, gender, years in workforce, etc.) all nominal. Then there are 7 different dependent variables, which are competencies scored on a scale. What test should I run to see if the demographics are affecting the competency scores? Right now I am considering running each independently vs. a multivariate regression analysis. Any advice on how to run & get accurate results would be much appreciated.

Thanks!

[Karabiner]

there are 6 independent variables (age, gender, years in workforce, etc.) all nominal.

Age or years in workforce are not nominal (categorical) variables,
at least they are ordinal.

Then there are 7 different dependent variables, which are competencies scored on a scale.

How are they scaled? Ordinal? Interval?

What test should I run to see if the demographics are affecting the competency scores? Right now I am considering running each independently vs. a multivariate regression analysis.

It depends on your research question. By the way, did you mean
multiple regression (several predictors in one analysis)?

Kind regards

K.

[klykk]

Thanks for getting back to me.

In this case age, years in workforce, etc. (all of the independent variables) were coded for different categories, ex. 1 is coded for ages 20-25. This is why I am using them as nominal.

The dependent variables are scored on an interval scale. They are the scores of various competencies and behaviors.

The question is: are there any significant differences in competencies and behaviors of managers based on age, gender, education, years in workforce, years in industry, years in current position?

Any advice you can give me would be much appreciated. Because there are so many factors in play I got stuck on what approach to take. (Yes I meant multiple regression)!

Thanks so much!!

[Karabiner]

In this case age, years in workforce, etc. (all of the independent variables) were coded for different categories, ex. 1 is coded for ages 20-25. This is why I am using them as nominal.

It is an interval scaled variable. How you will use it depends
on the very analyses you want to perform.

The question is: are there any significant differences in competencies and behaviors of managers based on age, gender, education, years in workforce, years in industry, years in current position?

So you want to perform Spearman-correlations (between competencies or behaviours
and ordinal scaled characteristics like age or education), Mann-Whitney U-tests or t-tests (comparison of competencies or behaviours between 2 groups, e.g. between
males and females), oneway analyses of variance or Kruskal-Wallis H-tests (comparison of competencies or behaviours between more than 2 groups).

Kind regards

K.

[klykk]

Thank you that was very helpful. I've started with the t-test for gender and oneway analysis or variance for the other variables. Thanks again!!