Nonparametric tests to support parametric tests

[Joseph]

hi people,
i am new here so excuse my 'innocence' in statistics.
I was wondering if someone could tell me if i am on the right track.
In my doctoral thesis I have an experimental group of 15 children with learning difficulties and a control group of another 15 children, matched at random. I am going to administer a programme to the experimental group.
Before the programme I administered 3 tasks to the experimental group and control group and I repeated the tasks after the programme.
I am using two way ANOVA to see if there were main effects of group, main effects of time and interaction effect. If i find an interaction effect I would administer a t-test.

Since I am not convinced that I should use parametric tests I also decided to further data analysis by using nonparametric tests (Wilcoxen and Mann-Whitney) to compare these results with those of the parametric tests. These would confirm and support my parametric results.

Is this acceptable? would it look stupid in a thesis if I do something like that? cause actually I would like to include the ANOVA but I want to play safe cause I do not want examiners to note that the assumptions for using parametric tests have been violated. So I tried to be safe and cautious.
THanks for any advice and help.

[elnaz]

Hello
i tell you about process of analysis data briefly:
1 ) you should test normality.
2 ) if data were normal then you should use parametric test.
3 ) if data were not normal then you should use nonparametric test.
if your data were normal but you used nonparametric for them is not false but your accuracy is less than results of parametric test in this case.
i think you can use many test on your data for example between experimental group data in after and before program, you can use tests for compare mean of data , and so on.
i hope you will be succeed

[Joseph]

thank you very much elnaz. You have been very helpful.

[elnaz]

you are welcome