In Weed Science field experiment, we normally go for statistical transformation of data to bring it near to normal distribution.Most of the time, we go for Square root transformation [ sqrt(x+0.5)]. My question is:
whether the choice of transformation remain same for all set of weed data i.e. sqrt (x+0.5)
If not, under situation we are using the different statistical transformation.
Is it possible we can use different statistical transformations at different stage of observation.
If you go through the weed science paper most of the time they use square root transformation, rather than log transformation. Can you please explain the nature of data collected.
There will be higher treatment variance, block variance as well as replication variance as we are dealing with 2 control treatments (weedy check and Weed free) plus other treatments...
Weedy check treatments always corresponds to higher value of Weed data(weed dry matter and Weed density) while zero value with weed free treatment...if we analyze treatment difference , we will get higher variance..there is assumption of analysis of variance (ANOVA) to have equal variance( others are independence with normality)..square root transformation is used to transform the data resulting in approximately equal variance with variable critical difference..and I think at all the stages if crop growth, one should used same transformation..log transformation is also employed in Weed researches...
As for analysis in ANOVA is concerned, we expect variation between the treatment, whether it is weed-free or weed check or any other treatment. The very purpose of the transformation is to reduce the within treatment variation, rather between the treatment.