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I am trying to see if there is a statistical significant difference between the amount of bycatch in 5 different types of gear used by fishermen. For each gear I have varying number of replicates as there are higher number of fishermen using certains types of gears compared to others. I have converted my raw data into 'percentage of time occurred' in order to compare them. What stats test should i use? I have access to minitab, but I am a novice with it.

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If you have at least 6 fishermen using each type of gear, you could begin with ANOVA. Since you're working with percentage data (which violates the assumptions of ANOVA), you'll want to logit- or arcsine-transform the data first.

If the ANOVA turns up significant results, you'll want to run a post-hoc test.

This is important: in the ANOVA, you'll want the identity of the individual fisherman to be a random factor.

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unfortunately, for 2 types of gear I only have 4 fishermen in each, I thought I would just mention that after the results of the analysis. If the data wasn't in percentages but rather expressed as 0.03 (instead of 3%), would i still have to logit? ( ia am a complete novice as you can see!). I don't think my data is normally distributed either, does this affect what stats test I use?? – Guy Apr 8 '12 at 7:47
If the data isn't normally distributed you, could try a non-parametric test, like Kruskal-Wallis. If you went non-parametric with it, you wouldn't need to perform any data transformation on the percentages. – Julie Apr 8 '12 at 18:01
Done Kruskal-Wallis, and it seems to have worked. Hopefully that'll be ok! Thanks a lot! – Guy Apr 9 '12 at 20:47

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