Parametric or non-parametric test ?

Dear the members of group.
I have 2 questions regarding my research which has 8 variables in which 6 of them are normally distributed and the rest are not normally distributed.
1. Do I need to use parametric test for those 6 variables and non parametric test for the rest of two variables to obtain the similar study objective ?
2. The 8th variable has several data which are grouped into two subgroups in which the first subgroup is normally distributed but the other subgroup is not . If I would like to compare mean difference between those groups, which test is more suitable, either the parametric or non parametric test ?
I seek your response. Thanks in advance


No cake for spunky
It depends on what you want to do. It is not normally whether a variable is normal or not that matters, but whether the error term is. Individual variables can be non-normal and the error term not be affected. Also most methods are robust to the normality assumption so it has to be signficant to matter. Commonly, as with regression, non-normality does not influence the parameter or SE calculations, but the confidence intervals and statistical tests.

Whether you have to use a non-parametric test depends on what you are doing, if you can transform the data etc. We need more details before answering your question.