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Irrationality 14,15: Mistaking the Cause, Misinterpreting the Evidence

01/22/2013

Chapter 14: Mistaking the Cause

Kindle Notes:

The more dramatic the outcome of an event, the more likely we are to attribute the cause to the agent. In one study, one group of subjects were told that a man parked his car on a hill. After he had got out, the car rolled down the hill and hit a fire hydrant. Another group were given the same story except that they were told the car hit and injured a pedestrian. The second group – those told that the driver’s action had serious consequences – held him more responsible than those told that the car simply hit a fire hydrant. This cannot be rational: the driver’s actions were the same in both cases (2694).

it has been shown that we are more likely to believe that someone is responsible for an action that injures ourselves than one that injures a friend and we are more likely to blame someone for injuring a friend than for injuring someone we don’t know (2701).

Many other experiments suggest that we are poor judges of the causes of our emotions. Male subjects were required to ride a stationary exercise bicycle for several minutes and were then shown pictures of female nudes. They rated them as more sexually stimulating than did subjects who had not been physiologically aroused by a spell on the bicycle (2789).

These phenomena are related to our ability to find a plausible story to explain anything that people, including ourselves, do or feel. We are driven to explain to ourselves the causes of our own moods and emotions and in so doing we often go badly wrong (2791)

One of the most convincing demonstrations of people’s inability to determine the causes of their failings comes from a study of real life undertaken at Harvard University. Women were asked to keep a diary in which they were to record for two months how far they had been in a good or bad mood on each day. In addition they had to make a note of a number of preset items that might influence their moods, such as amount of sleep the previous night, the weather, their state of health, their sexual activity and the stage of the menstrual cycle. When the diaries were handed in, the investigators subjected them to a mathematical analysis that teased out how far each of these factors was in fact associated with different moods (2797).

After their record-keeping was over, the women were asked to rate how far they thought each of the possible preset factors actually had determined their moods. Surprisingly, their ratings on these factors bore little or no relationship to those uncovered by the objective mathematical analysis (2805).

moral
1. Suspect any explanation of an event in which the cause and the effect are similar to one another, even when it is made on the highest authority.
2. Suspect all epidemiological findings unless they are supported by more reliable evidence.
3. Consider whether an event could have causes other than the one you first think of.
4. In allocating cause and effect, consider the possibility that they may work in the opposite direction to that for which you first plump.
5. Be sceptical of any causal relationship unless there is an underlying theory that explains it.
6. Remember that in most circumstances it is as reasonable to reason from effect to cause as from cause to effect.
7. In apportioning responsibility for an action, do not be influenced by the magnitude of its effect.
8. Don’t hold someone responsible for an action without first considering what others would have done in the same circumstances.
9. Don’t assume that others are like yourself (2812).

Chapter 15: Misinterpreting the Evidence

moral 1.
Do not judge solely by appearances. If something looks more like an X than a Y, it may nevertheless be more likely to be a Y if there are many more Ys than Xs.
2.   Remember that a statement containing two or more pieces of information is always less likely to be true than one containing only one of the pieces.
3.   Guard against believing a statement is true because you know that part of it is true.
4.   Remember that if you learn the probability of X given Y (for example, the probability that a cab is green if a witness claims it is), to arrive at the true probability of X you must take into account the base rate (the frequency of green cabs).
5.   Remember that the frequency with which a given attribute or event is observed is likely to deviate more from its frequency in the population as a whole in small samples than in large ones. Don’t trust small samples.
6.   Beware of biased samples.

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