I have a database containing records of several parameters: one is a quantitative parameter $D$ (e.g. average fuel consumption), others are qualtitative parameters $X_1, ..., X_n$ (e.g. make, color, engine type, ...) and quantitative parameters $Y_1, ... Y_m$ (e.g. average speed, driver's age, ...).
I am trying to assess whether there is any statistical relationship between $D$ and the other parameters $X_i, Y_j$. The ultimate goal would be to identify which of the $X_i, Y_j$ are relevant to "predict" $D$, and which are the ones that should be dismissed (because they are actually unrelated to $D$).
Please note that at this stage, I am just trying to identify what are the relevant parameters. The question of determining a quantitative relationship between $D$ and those parameters would come after this analysis.
I was thinking about performing chi-squared tests of independance between $D$ and the various $Y_j$, but I am rather confused about what to do with the qualtitative $X_i$. My questions are therefore:
- What tests/analysis can be used for the qualtitative parameters $X_i$ ?
- Is there any additional analysis that could be performed on top of the chi-squared tests for the $Y_i$?