Why I am getting Same p-value, h and stats while using Wilcoxon Rank test for 7 different data set?

I am trying to find the significant realtion between the az_solar and Mean_Surface_REF of seven different bands using Wilcoxon rank test. But I am geeting same p-value and statistics for every bands. However, each band contains different value.

Would some one please help me regrading these issue?

%% This is the code i am using

[p1,h1,stats1] = ranksum(az_solar,Mean_Surface_REF(:,1));

[p2,h2,stats2] = ranksum(az_solar,Mean_Surface_REF(:,2));

[p3,h3,stats3] = ranksum(az_solar,Mean_Surface_REF(:,3));

[p4,h4,stats4] = ranksum(az_solar,Mean_Surface_REF(:,4));

[p5,h5,stats5] = ranksum(az_solar,Mean_Surface_REF(:,5));

[p6,h6,stats6] = ranksum(az_solar,Mean_Surface_REF(:,5));

[p7,h7,stats7] = ranksum(az_solar,Mean_Surface_REF(:,7));

Results:

8.1275311e-44

8.1275311e-44

8.1275311e-44

8.1275311e-44

8.1275311e-44

8.1275311e-44

8.1275311e-44

Also, I have attached my dataset.

Answer 1

[dpb]

taz=readmatrix('az_solar.xlsx').';
>> [mean(taz) std(taz)]
ans =
  138.9109     16.7621
>>
>> mnref=readmatrix('Mean_Surface_REF.xlsx');
>> [mean(mnref); std(mnref)]
ans =
    0.0030    0.0065    0.0166    0.0093    0.0013    0.0045    0.0049
    0.0034    0.0023    0.0043    0.0034    0.0039    0.0053    0.0052
>> 

pretty-much explains it -- the means are some 4-5 orders of magnitude between the one vector and any of the vectors in the array. You've just totally saturated the value of the test statistic to the point the p-value returned is essentially zero.

You'd have been able to determine this yourself if you had simply looked at your data before blindly throwing it at some test statistic.

>> [p,h,stats]=ranksum(taz,mnref(:,1))
p =
   8.0633e-44
h =
  logical
   1
stats = 
  struct with fields:

       zval: 13.8827
    ranksum: 25026
>> format long, format compact
>> 1-normcdf(stats.zval)
ans =
     0
>> normcdf(stats.zval)
ans =
     1
>> normcdf(stats.zval)
ans =
     1
>> 

Answer 2

[the cyclist]

That test statistic only depends on the count and relative ordering of the respective set elements. In your case, it looks like the counts are always the same, and (as @dpb points out), your 7 cases are always completely offset from the comparator set.

Here is a small example showing the same thing:

x = 1:5;

y1 = 101:105; % 5 elements, fully offset from x
y2 = 1001:1005; % Also 5 elements, fully offset from x [same result]
y3 = 101:103; % 3 elements, still fully offset [different result due to different count]

ranksum(x,y1)

ans = 0.0079

ranksum(x,y2)

ans = 0.0079

ranksum(x,y3)

ans = 0.0357