Good looking guys earn more than you

I shamelessly stole most of this post from Overcoming Bias. Lots and lots of research shows that attractive people get better salaries, better jobs, get elected more, get more lenient sentences in court, etc. Even you have this bias, although you think you are very fair and take all decisions based purely on merit. On to the research:

Research has shown that we automatically assign to good-looking individuals such favorable traits as talent, kindness, honesty, and intelligence (for a review of this evidence, see Eagly, Ashmore, Makhijani, & Longo, 1991). Furthermore, we make these judgments without being aware that physical attractiveness plays a role in the process. Some consequences of this unconscious assumption that “good-looking equals good” scare me. For example, a study of the 1974 Canadian federal elections found that attractive candidates received more than two and a half times as many votes as unattractive candidates (Efran & Patterson, 1976). Despite such evidence of favoritism toward handsome politicians, follow-up research demonstrated that voters did not realize their bias. In fact, 73 percent of Canadian voters surveyed denied in the strongest possible terms that their votes had been influenced by physical appearance; only 14 percent even allowed for the possibility of such influence (Efran & Patterson, 1976). Voters can deny the impact of attractiveness on electability all they want, but evidence has continued to confirm its troubling presence (Budesheim & DePaola, 1994).

A similar effect has been found in hiring situations. In one study, good grooming of applicants in a simulated employment interview accounted for more favorable hiring decisions than did job qualifications – this, even though the interviewers claimed that appearance played a small role in their choices (Mack & Rainey, 1990). The advantage given to attractive workers extends past hiring day to payday. Economists examining U.S. and Canadian samples have found that attractive individuals get paid an average of 12-14 percent more than their unattractive coworkers (Hammermesh & Biddle, 1994).

Equally unsettling research indicates that our judicial process is similarly susceptible to the influences of body dimensions and bone structure. It now appears that good-looking people are likely to receive highly favorable treatment in the legal system (see Castellow, Wuensch, & Moore, 1991; and Downs & Lyons, 1990, for reviews). For example, in a Pennsylvania study (Stewart, 1980), researchers rated the physical attractiveness of 74 separate male defendants at the start of their criminal trials. When, much later, the researchers checked court records for the results of these cases, they found that the handsome men had received significantly lighter sentences. In fact, attractive defendants were twice as likely to avoid jail as unattractive defendants. In another study – this one on the damages awarded in a staged negligence trial – a defendant who was better looking than his victim was assessed an average amount of $5,623; but when the victim was the more attractive of the two, the average compensation was $10,051. What’s more, both male and female jurors exhibited the attractiveness-based favoritism (Kulka & Kessler, 1978).

Other experiments have demonstrated that attractive people are more likely to obtain help when in need (Benson, Karabenic, & Lerner, 1976) and are more persuasive in changing the opinions of an audience (Chaiken, 1979)…

See full article. Includes a formal list of references in case you don’t believe me.

Get a degree via mobile phone

Now a university in Japan is offering courses over cell phones:

The lectures are shown as a streaming video on the handset, with text and images appearing on the screen. The professor’s voice can be heard in the background. In a demonstration Wednesday, an image on the pyramids popped up on the screen and changed to a text image as a voice played from the handset speakers. Ancient Egyptians would be mystified and willing to trade any pyramid for such wondrous technology.

See full article.

You don’t understand numbers

You are terrible with numbers, unless there is a very good reason why you are different from the subjects of the psychological experiments described below. See this post at the always interesting Overcoming Bias blog:

Then how about this? Yamagishi (1997) showed that subjects judged a disease as more dangerous when it was described as killing 1,286 people out of every 10,000, versus a disease that was 24.14% likely to be fatal. Apparently the mental image of a thousand dead bodies is much more alarming, compared to a single person who’s more likely to survive than not.

But wait, it gets worse.

Suppose an airport must decide whether to spend money to purchase some new equipment, while critics argue that the money should be spent on other aspects of airport safety. Slovic et. al. (2002) presented two groups of subjects with the arguments for and against purchasing the equipment, with a response scale ranging from 0 (would not support at all) to 20 (very strong support). One group saw the measure described as saving 150 lives. The other group saw the measure described as saving 98% of 150 lives. The hypothesis motivating the experiment was that saving 150 lives sounds vaguely good – is that a lot? a little? – while saving 98% of something is clearly very good because 98% is so close to the upper bound of the percentage scale. Lo and behold, saving 150 lives had mean support of 10.4, while saving 98% of 150 lives had mean support of 13.6.

Or consider the report of Denes-Raj and Epstein (1994): Subjects offered an opportunity to win $1 each time they randomly drew a red jelly bean from a bowl, often preferred to draw from a bowl with more red beans and a smaller proportion of red beans. E.g., 7 in 100 was preferred to 1 in 10.

According to Denes-Raj and Epstein, these subjects reported afterward that even though they knew the probabilities were against them, they felt they had a better chance when there were more red beans. This may sound crazy to you, oh Statistically Sophisticated Reader, but if you think more carefully you’ll realize that it makes perfect sense. A 7% probability versus 10% probability may be bad news, but it’s more than made up for by the increased number of red beans. It’s a worse probability, yes, but you’re still more likely to win, you see. You should meditate upon this thought until you attain enlightenment as to how the rest of the planet thinks about probability.

See full article for more examples and references.

In a follow-up article he has another great example. When subjects were asked to choose between a 7/36 chance of winning $9 or a 100% chance of winning $2, only 33% chose to go for the $9. That seems reasonable. But when (a different set of) subjects were asked to choose between these two choices:

Choice 1: 7/36 chance of winning $9 or a 29/36 chance of losing 5¢
Choice 2: 100% chance of winning $2

Strangely, 60.8% of the subjects chose choice 1! Note that this is strictly worse than the corresponding choice in the previous experiment. Apparently,

After all, $9 isn’t a very attractive amount of money, but $9/5¢ is an amazingly attractive win/loss ratio.

You can make a gamble more attractive by adding a strict loss to it! Isn’t psychology fun?

Again the full article contains even more goodies.