Lies, Damned Lies, and Statistics/Quotes

""Aw, people can come up with statistics to prove anything, Kent. 'Forfty' percent of all people know that.""

- Homer Simpson, The Simpsons - "Homer the Vigilante"

""The death of one man is a tragedy, the death of a million is a statistic.""

- Not Joseph Stalin

""Ever since the formation of the Justice League, half of all marriages have ended in divorce! And the other half in DEATH!!""

- Glorious Godfrey lookalike, Justice League

"75% percent of people will believe anything that has a statistic in it."

"Nothing is so fallacious as facts, except figures."

- George Canning

"Because this is a meteorological fact I can prove with graphs and lying. It snows EVERY CHRISTMAS DAY. Oh, shut up, what do you know??"

- Steven Moffat on the rules of Christmas Movies, Radio Times issue 18-31 December 2010

"Consider the following as a rule. Whenever you have nonlinearity, the average doesn’t matter anymore. Hence:  The more nonlinearity in the response, the less informational the average. For instance, your benefit from drinking water would be linear if ten glasses of water were ten times as good as one single glass. If that is not the case, then necessarily the average water consumption matters less than something else that we will call “unevenness”, or volatility, or inequality in consumption. Say your average daily consumption needs to be one liter a day and I gave you ten liters one day and none for the remaining nine days, for an average of one liter a day. Odds are you won’t survive. You want your quantity of water to be as evenly distributed as possible. Within the day, you do not need to consume the same amount water every minute, but at the scale of the day, you want maximal evenness. [...]From an informational standpoint, someone who tells you “We will supply you with 0ne liter of water liter day on average” is not conveying much information at all; there needs to be a second dimension, the variations around such an average."

- Nassim Nicholas Taleb, Where You Cannot Generalize from Knowledge of Parts