The biological data is listed as following:
V1 V2 V3 V4 V5 V6
0.064 0.014 0.016 0.012 0.013 0.023
0.056 0.000 0.000 0.008 0.010 0.000
0.042 0.014 0.024 0.008 0.017 0.023
0.031 0.014 0.016 0.008 0.013 0.023
0.068 0.000 0.008 0.004 0.020 0.000
0.081 0.000 0.000 0.004 0.010 0.000
0.060 0.014 0.016 0.006 0.010 0.023
or you can download it from http://www.mediafire.com/?6yp9l9m47jv433a.
A<- dat[,1]
B<- dat[,2:6]
I want to compare the difference between the first column to other columns of the data.Because only dat[,2] and dat[,6] not subject to normal distribute,I used wilcox.test instead of t.test function to caculate in R. But the warning messages rised up,such as "In wilcox.test.default(A, B[, 1]) : cannot compute exact p-value with ties". Could you give me some suggestions? Thank you.
> wilcox.test(A,B[,1])
Wilcoxon rank sum test with continuity correction
data: A and B[, 1]
W = 49, p-value = 0.00184
alternative hypothesis: true location shift is not equal to 0
Warning message:
In wilcox.test.default(A, B[, 1]) : cannot compute exact p-value with ties
•
written
by
Chuangye •
It's a warning message, nothing more. You have two identical values in your data, these are the ties. Now the ranks are not unique and exact p-values cannot be calculated. You might want to look at at statistics text, there is some discussion here on dealing with ties.
This could be very easily gleaned from a quick perusal of Google and would have been better off asked on http://stats.stackexchange.com/
Thank you! And do you think it is right to use wilcox.test fucntion to sovle the problem? And I will aslo turn to help on http://stats.stackexchange.com/.
You appear to have some excellent answers here:
http://stats.stackexchange.com/questions/2852/how-to-analyze-these-data
So I will leave it to the experts :)
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Just wanted to comment as I saw this coming up again thanks to Lars' efforts. It's generally a bad idea to ask a question this way, as the question cannot be answered without knowing how the data was obtained, what are the hypothesis of the experiment. It's sort of turning upside down the scientific process, you should make a hypothesis before the experiment, and have a clue about possible analysis or test. So sorry to your experiment was flawed from the start, because you tried to find a method that gave you the results you wanted.
And btw, saying "...this biological data..." is like asking the chef of your favorite French restaurant: "and how do you cook food?"