Skip to content
Related Articles

Related Articles

Wilcoxon Signed Rank Test
  • Last Updated : 26 Nov, 2020

Prerequisites: Parametric and Non-Parametric Methods 
                        Hypothesis Testing 

Wilcoxon signed-rank test, also known as Wilcoxon matched pair test is a non-parametric hypothesis test that compares the median of two paired groups and tells if they are identically distributed or not. 

We can use this when:

Differences between the pairs of data are non-normally distributed.
Independent pairs of data are identical. (or matched) Eg. (Math, English: Both subjects) ; (June, July: Both months) 
 

Steps involved:



Step 1 - Determine the null (h0) and alternate (ha) hypothesis. 
Step 2 - Find the difference (D) between the two columns. [D = B-A]
Step 3 - Find absolute difference (Abs-D). [Abs-D = |D|]
Step 4 - Assign ranks to Abs-D from lowest (1) to highest (n).

Assigning Ranks: 

If any two or more Abs-D values are same, then assign them consecutive ranks, then find the average of the ranks for each set of duplicate value. Consider the following scenario:

Abs-D445
Rank12345678
Modified Ranks123.53.56667
Case I - For Abs-D = 3 
       -> Assign them consecutive possible ranks. (3,4)
       -> Find average of 3,4 => (3+4)/2 = 3.5
       -> Assign the rank = 3.5 to both the 3's present in the table.             
Case II - For Abs-D = 4
        -> Assign them consecutive possible ranks. (5,6,7)
        -> Find average of 5,6,7 => (5+6+7)/3 = 6
        -> Assign the rank = 6 to all the 4's present in the table.
Step 5 - Find the sum of the ranks assigned to positve (T+) and negative (T-) Abs-D values. 
Step 6 - Find the Wilcoxon Rank. (Wcalc = minimum(T+,T-))  
Step 7 - Use the value of n and α and find Wtable in two-tailed section of 
      'Critical values of wilcoxon signed rank test'. 
     (take α = 0.05, if not given)
Step 8 - Interpretation of result.

NOTE : We use two-tailed test when we are dealing with two hypothesis. (null and alternate) 

Interpretation of result

When Wcalc < Wtable :
    -> Reject H0 (null hypothesis) 
     -> The two groups are not identically distributed.

When Wcalc > Wtable :
    -> Accept H0 (null hypothesis)
     -> The two groups are identically distributed.

Example Problem (Step by Step):

Consider the following example. The smog concentration data of 13 states of India were measured. Perform the Wilcoxon signed rank test and determine if there’s a significant difference in the concentrations recorded in May to that in December. [take α = 0.05]

States

Smog concentration 
in May
(A)



Smog concentration 
in December
(B)

Difference
[D]
(B-A)

(Step-2)

Absolute 
Difference
[Abs-D]

(Step-3)

Rank

 

(Step-4)

Delhi

13.3

11.1

-2.2

2.2

5

Mumbai

10.0

16.2

6.2

6.2

9

Chennai

16.5

15.3

-1.2

1.2

3

Kerala 

7.9

19.9

12.0

12.0

11

Karnataka

9.5

10.5

1.0

1.0

2

Tamil Nadu

8.3

15.5

7.2

7.2

10

Orissa

12.6

12.7

0.1

0.1

1

UP

8.9

14.2

5.3

5.3

7

MP

13.6

15.6

2.0

2.0

4

Rajasthan 

8.1

20.4

12.3

12.3

12

Gujarat

18.3

12.7

-5.6

5.6

8

West Bengal

8.1

11.2

3.1

3.1

6

Jammu 

13.4

36.8

23.4

23.4

13

n = 13
α = 0.05

Step 1 - h0 : Cmay = Cdecember (no change in the smog concentration)
     h1 : Cmay ≠ Cdecember (smog concentration changed)
Step 2,3,4 - Refer the table given above.
Step 5 - T+ marked as [ ] in table.  
     T- marked as [ ] in table.
∑T+ = 75
∑T- = 16
Step 6 - Wcalc = minimum(75,16) 
           = 16
Step 7 - Using n = 13 and α = 0.05 in table (click here)
     Wtable = 17
Step 8 - Wcalc < Wtable :
      Rejecting H0. 
     i.e smog concentration have changed from before.

Conclusion: 

Wilcoxon signed-rank test is a very common test in the fields of pharmaceuticals, especially amongst drug researchers, to find out the dominant symptoms of various drugs on humans. Being a non-parametric test, it works as an alternative to T-test which is parametric in nature. For any doubt/query, comment below.  

machine-learning

My Personal Notes arrow_drop_up
Recommended Articles
Page :