To whom it may help:
My research is on cellular/molecular responses after hormones farmacological administration and I'm not quite sure how to perform statistical analysis.
I have 15 test groups plus my control group (DMEM) and I did my experiments two different times (2 occasions) in triplicate looking for cell proliferation.
As you know, with three replicates, if I try to analyze my data in each occasion, I wont have enough samples to do normality tests. That situation forced me to do Kruskal-Wallis Non-parametric Test. However, the results are far away from what we can really see on data images and graphically.
I tried to analyze each occasion using parametric statistical analysis ANOVA one-way and It was a catastrophe. Some results of the first occasion doesn't match with the second one.
Well, as I compare my results based on fold-change, I also tried to gather both results of different occasions. Now, since I'm using 6 different replicates per group, in this way It's possible to perform normality test - I did use Komogorv-Smirnov Normality Test and after that I did ANOVA one-way and compared all groups with Tukey post-test. Results now were way better. Nevertheless, I would like to know if this is the best way to analyze my data. Also, is there any advice on how should I analyze my data?
Best regards !
My research is on cellular/molecular responses after hormones farmacological administration and I'm not quite sure how to perform statistical analysis.
I have 15 test groups plus my control group (DMEM) and I did my experiments two different times (2 occasions) in triplicate looking for cell proliferation.
As you know, with three replicates, if I try to analyze my data in each occasion, I wont have enough samples to do normality tests. That situation forced me to do Kruskal-Wallis Non-parametric Test. However, the results are far away from what we can really see on data images and graphically.
I tried to analyze each occasion using parametric statistical analysis ANOVA one-way and It was a catastrophe. Some results of the first occasion doesn't match with the second one.
Well, as I compare my results based on fold-change, I also tried to gather both results of different occasions. Now, since I'm using 6 different replicates per group, in this way It's possible to perform normality test - I did use Komogorv-Smirnov Normality Test and after that I did ANOVA one-way and compared all groups with Tukey post-test. Results now were way better. Nevertheless, I would like to know if this is the best way to analyze my data. Also, is there any advice on how should I analyze my data?
Best regards !