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micro micro
wrote...
Posts: 170
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9 years ago
Hi Guys, I've got a test which I'd like to run but not sure which type is adequate. I have a set of curved graphs which I'd like to check for overlap i.e. autocorrelation between such curves. I've tried using the residual values with the Durbin-Watson but not sure if this is the right test since I got a great significant value which I believe is too good for the data.
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wrote...
Educator
9 years ago
What's the relationship between your independent and dependant variables (linear, exponential, etc.)?

If you're going to do the Durbin-Watson, follow this:
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micro Author
wrote...
9 years ago
Independent. I'm plotting light intensity vs. distance and the light intensity is arbitrary i.e. not of interest in fact I can standardize and change the Y axis into a binary (0 and 1) so I get peak or no peak on the Y-axis with a change in distance.
wrote...
Educator
9 years ago
That would be cool, never seen that done before (binary style). I've never compared graphs by superimposing them on one another, so I can't give you any valuable pointers. What I usually do is look for trends, find their line/curve of best fit and use that for comparison sake.
wrote...
Valued Member
9 years ago Edited: 9 years ago, ortho2122
I probably don't understand the experiment completely. Light intensity is related to the inverse square of distance from the source. What exactly are your response and input variables?


Assuming that the Durbin-Watson finding is real, then I'd be looking for an explanation of why the residuals are so strongly correlated. If the correlation is spurious, I'd still want to be able to explain why it isn't real.
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