Spearman's Rank Correlation Coefficient
Why do I need to do this test?
You need to perform this test if you are looking for a relationship between two pieces of data. A change in one of the variables will lead to a change in the other. In mathsspeak this means you have a dependent and an independent variable  one controls the other.
What do I do first?
Draw a scatter graph with a trend line to identify whether there is a relationship between your two peices of data. If it appears that there is no relationship, then there is no need to perform a Spearman's Rank test. You can read about how to do a Spearman's Rank test in Waugh (3rd ed.) pages 635637.
How do I perform the test?
You can do the test by hand using the instructions in Waugh, or the class handout, or you can cheat a little and use an online Spearman's Rank calculator.
What does the result mean?
Spearman's Rank will be a value between 1 and +1.
A positive correlation is denoted by a value between 0 and +1
A negative correlation is nenoted by a value between 0 and 1
The closer your value is to 1 or +1 the greater the strength of the relationship between your two variables.
A value closer to 0 means that the correlation between your 2 pieces of data is weak and that there are other factors that also play a part in the variation of your data.
How do I use this result in the exam?
You can use your result in a question concerning analysis, conclusions or evaluation.
You may need to say why you did the test, what the outcome was (your Spearman's Rank number), and what this tells you about the data.
The result of your test might support your hypothesis, or it might not  you need to say this.
You need to suggest the other factors that might have influenced the variations in your data, and you need to understand why  to do this you need a good grasp of the underpinning theory.
Sample Paragraph for Conclusions.
The study aimed to investigate the relationship between light intensity and percentage ground cover in a deciduous woodland in the Wyre Forest, near Kidderminster. Using a scatter graph, a positive correlation was identified which agreed with the hypothesis that percentage ground cover would be higher in areas of higher light intesnsity. Following this, a Spearman's Rank value of 0.785 was obtained. This supports the hypothesis and makes the overall conclusion to this aim more reliable since this result is statistically significant at the 95% level. However, since the Spearman's Rank value is less than one, there must still be other factors that influence the variation in percentage ground cover. Slope aspect plays a part, whereby southfacing slopes in the northern hemisphere recieve greater insolation than northfacing ones. Since the data was collected across a valley, this factor may have accounted for lower percentage cover results collected from the northfacing slope. The tree species in the vicinity of the data may also have had an impact on the percentage ground cover because the size and shape of the tree and it's leaves will alter the amount of precipitation that reaches the woodland floor. A tree such as Horse Chestnut with a dense canopy and broad leaves may reduce the throughfall of precipitation significantly by interception. This will reduce the percentage of ground cover since water availability is a limiting factor to plant growth.
