Hi Javed,
Easy.
A<-c(2000,2100,2300,2400,6900,7000,7040,7050,7060)
median(A)
[1] 6900
B<-c(3300,3350,3400,3450,3500,7000,7100,7200,7300)
median(B)
[1] 3500
wilcox.test(A,B,paired=FALSE)
Wilcoxon rank sum test with continuity correction
data: A and B
W = 26.5, p-value = 0.233
alternative
Any reasonable test of whether two samples differ should be scale and
location invariant. E.g., if you measure temperature it should not matter
if you units are degrees Fahrenheit or micro-Kelvins. Thus saying the
medians are 3500 and 6200 is equivalent to saying they are 100.035 and
100.062: it
> This is my function:
>
> wilcox.test(A,B, data = data, paired = FALSE)
>
> It gives me high p value, though the median of A column is 6900 and B
> column is 3500.
>
> Why it gives p value high if there is a difference in the median?
Perhaps becuase a) because you are testing the wrong data
We've had this conversation.
A) This is off-topic for R-Help. Your question is about the statistical test,
not about the R coding.
B) A difference in sample statistics, whether or not it "looks" large, is not
sufficient for statistical significance.
On 3/19/19, 12:48 PM, "R-help on behalf of
Hi
This is my function:
wilcox.test(A,B, data = data, paired = FALSE)
It gives me high p value, though the median of A column is 6900 and B
column is 3500.
Why it gives p value high if there is a difference in the median?
Regards
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