Setting an experiment with ordered categories as predictors

I am trying to apply a multi-factorial regression analyses on a model with 4 different predictors each of which can have four different weights as levels: 0.1, 0.2, 0.3, 0.4. I run 24 different samples applying permutations of these levels for the four predictors.
predictor 1 : four levels(0.1,0.2,0.3,0.4)
predictor 2 : four levels(0.1,0.2,0.3,0.4)
predictor 3 : four levels(0.1,0.2,0.3,0.4)
predictor 4 : four levels(0.1,0.2,0.3,0.4)
So, I get this model:
Y = B + B1Predictor1 +B2Predictor2+...
However, my response variable is not normally distributed, it looks more as a factor variable showing only three different results across the 24 samples. Based on this, I am not sure, whether I am using the right model for my study.

Can anyone help?
Thank you!


TS Contributor
It is not necessary for either the predictors or the response variables to be normally distributed. What is important is for the residuals to be normally distributed.