I attribute the kinks to inconsistencies in the data collection. I have other data that is being collected that is much better controlled as far as the collection. This was the first year and we were working out the kinks.
However, that said the r-squared for each line using this data was all over O. 95 so I'm still pretty confident.
What I am trying "prove" is to create a pretty solid argument that using this approach is more robust and useful than using transformed data and a linear model based ANOVA. This would add a level of confidence in the differences we see on the graph. There will be concrete differences between the lines.
TBH My advisor is a pretty heavy advocate of the ANOVA method because it is what he was taught. I feel this is a better description of the data. I don't know what it means in nature when the stats are transformed using arcsine. The actual emergence on day 4 is the arcsine of what I counted?
However, that said the r-squared for each line using this data was all over O. 95 so I'm still pretty confident.
What I am trying "prove" is to create a pretty solid argument that using this approach is more robust and useful than using transformed data and a linear model based ANOVA. This would add a level of confidence in the differences we see on the graph. There will be concrete differences between the lines.
TBH My advisor is a pretty heavy advocate of the ANOVA method because it is what he was taught. I feel this is a better description of the data. I don't know what it means in nature when the stats are transformed using arcsine. The actual emergence on day 4 is the arcsine of what I counted?