Sharpshooter fallacy:

Definition Example
When a precise target is chosen only after a vague prediction or speculation is made. Last year, the governor promised to stimulate the economy during his term, and you will note that this year there has been an increase of 2,000 jobs in the service industry.
The governor in the example may be ignoring other less-favorable data to paint a picture of success. This fallacy is similar to cherry-picking. It is subjectively and arbitrarily (though perhaps subconsciously) selecting data that will bolster your position while ignoring data inconsistent with your position. For this reason, scientists attempt to reduce subjectivity by starting with a hypothesis, then attempt to falsify that hypothesis by every imaginable means. This increases the objectivity basic to scientific success and respectability.

Case Study One

Consider someone who claims he can accurately and consistently predict the outcome of coin flips. After 5 flips he has only guessed 2 flips correctly (40%), and wants to continue the experiment. Finally after 20 flips, he has guessed 13 correctly, and wants to stop, making his accuracy appear to be 65%. However, because he was able to choose when to quit, the results are subjectively biased, and do not meet the standards of experimentation set by science.

Case Study Two

Cherry picking data on global warming has been one recent example of this fallacy. “If you look at the data and sort of cherry-pick a micro-trend within a bigger trend, that technique is particularly suspect,” says John Grego, a professor of statistics at the University of South Carolina.

Keep in mind that a fallacious argument does not entail an erroneous position.

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