Reply to Re: Temporal Nullification, Niiiice :P *beep* *beep*
If you don't have an account, just leave the password field blank.
Only one explanation? The basic idea that a specific observation can have only a single explanation is flawed. For example when I use DNA profiling to investigate a murder and I find a match there are multiple explanations for this match:
- The man with the matching DNA is the murderer.
- The man's identical twin is the murderer.
- Someone with the same set of genetic mutations is the murderer. (Very unlikely, but not impossible)
- The DNA that was found is not from the murderer.
And very often we have much less detailed observations to work with and we can come up with a large variety of explanations. Perhaps a single observation has only a single cause, but that doesn't mean we can always deduct that from our observations.
I agree on your point that it is not needed to actually see something to have proof, in fact our eyes can be very deceiving. But you'll need to remember what assumptions you're making and that your observations and reasoning, no matter how detailed or thorough, can be flawed in some way. Certainty can not be found in science, only a high probability.
- The man with the matching DNA is the murderer.
- The man's identical twin is the murderer.
- Someone with the same set of genetic mutations is the murderer. (Very unlikely, but not impossible)
- The DNA that was found is not from the murderer.
And very often we have much less detailed observations to work with and we can come up with a large variety of explanations. Perhaps a single observation has only a single cause, but that doesn't mean we can always deduct that from our observations.
I agree on your point that it is not needed to actually see something to have proof, in fact our eyes can be very deceiving. But you'll need to remember what assumptions you're making and that your observations and reasoning, no matter how detailed or thorough, can be flawed in some way. Certainty can not be found in science, only a high probability.
