Multiple comparisons of economic game data

Any help would be greatly appreciated!

I am analyzing some data to which I think I need to make some kind of multiple comparisons correction. The data comes from an economic game (Dictator game) and is the form of donations made by subjects ranging from $ 0.00 to $ 0.50 (can be any $ 0.01 denomination). Subjects were primed with an experimental image or an control image I am primarily interested in the effect of which image they were shown on their donation.

I did the following tests all on the same donation data;
1) I used a Mann-Whitney U test to test if there was a difference in the amount donated for each image shown, control or experimental prime (Main hypotheseis).
2)I tested If there was a difference in the amount donated by each gender (Mann-Whitney U test)
3)I tested the relationship between age of dictator and donation using Spearmans Rank
4) Income and Education were categorical, eg. one level of Education would be "Some High School" and one level of Income would be "$0-$15 000" for each there was 6 levels. I tested donation against the different levels of Income (Kruscall-Wallis) and did the same for Education (Kruscall-Wallis).
5)Although dictators could choose any value to donate they all choose one of 11 amounts. For each of these amounts I tested if they were over represented by dictators who saw one image compared to the other. For each amount I encoded the data as 1 if they donated this amount and 0 for any other amount and ran a fishers exact test for each amount (11 tests in total). The only one that was significant was $0.50, those that saw one image gave $0.50 significantly more often than those that saw the other.

I realize I have gone overboard with tests. I am not too sure too which I should apply an adjustment. ie. If I Bonferroni adjust for the kruscall-wallis test do I just divide alpha by 6 as this is how many levels in income and Education or do I need to take into account the Mann-Whitney tests and Spearmans rank. Also, for the Fishers exact tests the data is encoded differently for each test. Therefore do I need to make a correction or not? What sort of correction should I make?

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TS Contributor
Hi JonoBone,

I see no problems until number 5. If I read well, you didn't do too many tests in the first four steps so I wouldn't worry too much about correction. Yet the 11 tests in the fifth step seems different. I would only use the bonferroni correction in those eleven tests, where you compared with each of the available answers. Still, if you are too worried about it, you could some modeling to test most of the hypothesis in steps 1 to 4, but as I told you, I don't think it is necessary.