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Spearman's Rank Correlation is a technique used to test the direction and strength of the relationship between two variables. In other words, its a device to show whether any one set of numbers has an effect on another set of numbers.
It uses the statistic
which falls between -1 and +1.
Procedure for using Spearman's Rank Correlation
- State the null hypothesis i.e. "There is no relationship between the two sets of data."
- Rank both sets of data from the highest to the lowest. Make sure to check for tied ranks.
- Subtract the two sets of ranks to get the difference
.
- Square the values of
.
- Add the squared values of
to get
- Use the formula
where
is the number of ranks you have.
- If the
value...
- ... is -1, there is a perfect negative correlation.
- ...falls between -1 and -0.5, there is a strong negative correlation.
- ...falls between -0.5 and 0, there is a weak negative correlation.
- ... is 0, there is no correlation
- ...falls between 0 and 0.5, there is a weak positive correlation.
- ...falls between 0.5 and 1, there is a strong positive correlation
- ...is 1, there is a perfect positive correlation
- between the 2 sets of data.
- If the
value is 0, state that null hypothesis is accepted. Otherwise, say it is rejected.
Practical Example of Spearman's Rank Correlation
Question: Use the Spearman's Rank Correlation to establish whether there is any relationship between the distance away from school students live and the IB Geography grades they attain.
- Red type indicates what you have been given. Black type indicates the working done.
- Null Hypothesis: There is no relationship between the two sets of data.
-
| Distance From School (in miles)
|
| IB Geography Grades Attained
|
|
|
|
| 3
| 2
| 4
| 4
| 2
| 4
|
| 7
| 1
| 4
| 4
| 3
| 9
|
| 2
| 3
| 7
| 1
| 2
| 4
|
| 2
| 3
| 6
| 2
| 1
| 1
|
| 1
| 5
| 5
| 3
| 2
| 4
|
|

therefore
therefore



- There is a weak positive correlation between the two sets of data. The null hypothesis is rejected.
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