# What are the first steps to find the right model for non-normal data?

I a total of 8 Independent Variables (4 continuous - Scales outcomes - and 4 categorical - Demographic and other personality questions) and 2 Dependent Variables (1 continuous and 1 count). The DVs involve data from an Iterated Prisoners' Dilemma - 1)participants mean consumption per game (continuous variable) and 2) the number of cooperations participants played during each game (count variable).

I have tested the DVs for Poisson distributions, but none of them is. Residuals of the continuous variables are not normally distributed.

My main aim is to analyse the main effect of the IVs on the 2 DVs. I am also interested in testing the possible interactions between two of the IVs and their subsequent effects on the outcome variables. What is the best statistical model to use considering that all the variables are not normally distributed? Or at least, what are the first steps I should take knowing that the data is not normally distributed?

I have been looking into Generalized linear models, but how can I run any model if I don't know the exact distribution of my data? Should I try to normalize my data?

Count DV:

Continuous DV: Thank you

• It would be great if you could expand on the problem. What are your DVs and IVs? Can you provide scatter plots so that others can see how the DVs are related to IVs? – jcken Jun 12 '20 at 10:57
• @jcken thanks for the answer, I edited the question by adding more details regarding the experiment. I'm not sure what are the scatterplots you are interested in but I added a couple of Histograms to show the distribution of the DVs. – John Walk Jun 12 '20 at 11:13
• The responses (you say DVs) don't have to follow reference distributions closely for associated models to be useful. Thus I would certainly start with a Poisson model for # of cooperations and possibly start with a gamma model and/or a logarithmic link for mean consumption. A shared flavour for both example responses is that values can't be negative and that mean responses given predictors will be positive. Such features lend themselves to generalized linear models. – Nick Cox Jun 12 '20 at 11:19
• @JohnWalk scatter plots show the relation between the IV and DV; if you want to model this relationship it would be useful to understand what it looks like! E.g. it could show an approximately linear or polynomial relationship between IV and DV – jcken Jun 12 '20 at 11:36