Playing With Statistics. . .

. . .can result in any outcome a person/statistician/ideologue desires:

The problem is doubly difficult when dealing with statistical data.

Most non-specialists assume you just plug a set of numbers into a computer and get a nice graph. But real statistical data is “dirty” and needs to be cleaned or “conditioned” in order to analyze it. Outlying data, measurement errors, and equipment failures, all have to be dealt with.

The problem is that this process of conditioning can have the effect of throwing away any data that doesn’t fit the original hypothesis.

Why is this important? In the ongoing debate over global warming's anthropogenic causality, statistics such as temperature increases, intensity of hurricanes, and precipitation amounts, etc. etc. can be misunderstood, misused, or completely cooked in order to achieve a desired outcome.

There are "lies, damn lies, and statistics", according to Mark Twain. Then there is global warming science. Be skeptical.

(via Wizbang)