Counts data re-distribution.
I ran ANOVA however, the numbers don't make sense. My experiment was based on treating plant tissue culture explants with NaDCC and PPM. After a 30-day period, I had to count the number of aseptic and contaminated tubes from a batch of 10. So if 5 tubes were contaminated it means 50% were aseptic. On the other batches, I had O%-contaminated tubes and 100% clean tubes. Therefore, there's a huge variation between the numbers resulting in my data having a non-normal distribution or skewed distribution. For me to use ANOVA I assume my data must be normally distributed. The tubes were counted and values were converted to percentages. But when plotting graphs in Excel +/-SD extended passed zero to the negative quadrant. I am not familiar with statistics or ways to code, I am completely clueless on how to resolve this issue.
Dear, If your data is not normal or, even there is no evidence of equidispersion, then you need non-parametric methods: Mann-Whitney or kruskal wallis approach.
You can transform it using natural log, or 1/sqrt if it is not negative, ah yes you can also use kruskall-wallis, welch correction annova, and also non parametric analysis
Alamir Louro Thank you, I have familiarized myself with Kruskal Wallis on SPSS when analyzing the data I am supposed to compare sites and determine if there are significant differences in responses to different treatments. A mini sample is attached to provide my data layout with variables. What would be a suitable non-parametric method to handle this pairwise comparison type in SPSS?
yes for non normal data we use non parametric statistics, alternative to ANOVA is Kruskal Wallis, equally performance as ANOVA
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