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Feb 5, 2013 at 22:31 history edited user88 CC BY-SA 3.0
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Feb 4, 2013 at 17:15 history edited user1243255 CC BY-SA 3.0
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Feb 4, 2013 at 16:36 history edited user1243255 CC BY-SA 3.0
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Feb 4, 2013 at 14:35 vote accept user1243255
Feb 4, 2013 at 13:41 vote accept user1243255
Feb 4, 2013 at 13:49
Feb 4, 2013 at 7:13 answer added Corvus timeline score: 2
Feb 3, 2013 at 23:22 history edited user1243255 CC BY-SA 3.0
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Feb 3, 2013 at 23:08 comment added Corvus Be careful what you do with the results then. For example, if it were the case that after B became 1, it hung around at 1 for 30 seconds, then the probability you get from a naive method will very biased if interpreted as the "probability that any randomly chosen location with A=1 is currently in B=1 at any given time". However, if your intention is only to apply this result to exactly the same data collection algorithm in the future, then it should be OK.
Feb 3, 2013 at 22:53 comment added user1243255 We do not know/care cause our signal gatherer just hits those locations every 10 seconds and sees whether location is alive or not and moves on but we do know that B is caused by A just by design of logic.
Feb 3, 2013 at 22:51 comment added Corvus So neither A nor B "stick" and hang around for a while? Your example shows a sequential string of A's - just coincidence?
Feb 3, 2013 at 22:48 answer added Arthur Small timeline score: 1
Feb 3, 2013 at 22:30 comment added user1243255 Each visit is independent but B depends on A due to way logic is built.
Feb 3, 2013 at 22:26 comment added Corvus What is wrong with simpky counting up the occurrences in a frequency table? Are your data independent samples? Do you have any reason to fear selection biases? Is each visit independent or is there strong autocorrelation here?
Feb 3, 2013 at 22:16 history asked user1243255 CC BY-SA 3.0