Texas sharpshooter fallacy
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The Texas sharpshooter fallacy is using the same data to both construct and test a hypothesis. Its name comes from a parable where a Texan fires his gun at the side of a barn, then paints a target around the bullet holes and claims to be a sharpshooter. A hypothesis must be constructed before data is collected based on that hypothesis. If one data set is used to construct a hypothesis, then a new data set must be generated (ideally, in a different way, based on predictions made by the hypothesis) to test it.
Much of young earth creationism relies on this form of post hoc reasoning. This is most clearly demonstrated in fundamentalist Christians' discussions of how the flood created geologic structures. Their ideas rely on finding data and constructing a hypothesis around that data, with no further testing of these ideas after this construction. This is a clear example of this particular fallacy.
Creationist and intelligent design arguments claim that the chances of a protein molecule forming "randomly", or a cell forming "randomly" via abiogenesis, or the universe forming "randomly" into what we see today are incredibly low, and thus it must have been designed. This argument is extremely faulty in that it doesn't acknowledge that physical processes are not random, but are guided by the laws of physics, chemistry, and eventually, biology: evolution via variation and natural selection.
In late 2010, "Feeling the Future: Experimental Evidence for Anomalous Retroactive Influences on Cognition and Affect", a psychology paper by Daryl Bem, ostensibly provided evidence of precognition. In Bem's experiments, a small but statistically significant number of test subjects' responses appeared to be influenced by conditions which appeared later in the tests. However, Bem has acknowledged forming some of his conclusions after the tests, rather than testing fixed hypotheses as any rigorous application of the scientific method should. He has also stated that, before concluding and publishing his research, "I purposely waited until I thought there was a critical mass that wasn't a statistical fluke". While this may seem logical at first glance, deliberately waiting for such a "critical mass" actually means stopping research at a point when the results appear favourable to the hypotheses rather than continuing through a pre-set number of experiments before checking for overall findings.
The crazification factor is often an example in popular usage: you will find endless examples of people online go ad hominem when 20-30% of people do something the speaker doesn't like, or are even polled as holding an opinion they don't like.