I have two datasets, and I wish to determine the statistical difference between two groups. I am comparing a visual plant injury scoring system to a remotely-sensed scale, and the coefficient of variation (CV) is usually used for this purpose (it goes on the assumption that the lower the CV of the dataset, the "better" the scale). It's important to note that the data has been normalized between 0 and 1, to make for a more accurate comparison.
How can I test for differences in the two CVs? Given there are just two datasets, it would be easy to do a t-test if comparing means. However, I'm not needing to compare the means. Can this be done in R?
Here is the data, in case reference is needed:
dataset <- data.frame(visual = c(152,
150,
275,
407,
364,
105,
415,
221,
374,
408,
265,
290,
186,
130,
263,
113,
290,
157,
348,
384,
369,
175,
421,
183,
214,
146,
333,
374,
201,
262,
364,
343,
395,
332,
290,
294),
remotesense = c(104,
132,
148,
370,
257,
373,
409,
320,
350,
178,
236,
100,
219,
403,
107,
345,
102,
307,
292,
258,
271,
220,
165,
211,
204,
420,
339,
380,
227,
390,
354,
153,
423,
103,
342,
116))