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Statistics: For this data I will be using Spearman's Rank Coefficient of correlation. This type of data stat shows the relationship between the independent and dependant variables. Number Value (x) (Metres) Rank (Rx) Value (y) Rank(Ry) D = Rx-Ry D2 1 0.00 1 10.3 7 -6 36 2 1.25 2 0.67 2 0 0 3 2.50 3 0.33 1 2 4 4 3.75 4 2.00 3 1 1 5 5.00 5 2.07 4 1 1 6 6.25 6 9.33 5 1 1 7 7.50 7 21.3 9 -2 4 8 8.75 8 22.7 10 -2 4 9 10.0 9 18.7 8 1 1 10 11.25 10 9.7 6 4 16 _-_-_-_-_-_-_-_-_-_- _-_-_-_-_-_-_-_-_-_- _-_-_-_-_-_-_-_-_-_- _-_-_-_-_-_-_-_-_-_- Total 0 68 Once you have these you can work out Spearman's coefficient of correlation using this formula: Rs = 1- [6?D2/n3-n] 1- [408/990] 1- 0.412: = 0.588 (3 DP/SF) Null Hypothesis: There is not a significant relationship between the distance from the path and the abundance of creeping moss. Alternative Hypothesis: There is a significant relationship between the distance from the path and the abundance of creeping moss. This calculation will show me if I have a positive correlation and will also guide me as to accept or reject my hypothesis. Using the table of critical values at 95% confidence level, this means that I am 95% confident that my results are not due to chance. The critical value is 0.679 because it has 10 pairs of variables. Since the Spearman's...

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