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collected, a phenomenon sometimes known as base rate neglect. If we see more broken-down Fords than Jaguars, we tend to assume that Fords are less reliable, ignoring the fact that there are many times more Fords driving round than Jaguars. Exercise 2.5 Neglecting base rates Try for yourself this real-life problem, which was given to health professionals, whose day-to-day job involves just this kind of decision, and pregnant women, who might be faced with it too (from Bramwell, West & Salmon, 2006). The serum test screens pregnant women for babies with Down’s syndrome. The test is a very good one, but not perfect. Roughly 1% of babies have Down’s syndrome. If the baby has Down’s syndrome, there is a 90% chance that the result of the serum test will be positive. If the baby is unaffected, there is still a 1% chance that the result will be positive. A pregnant woman has been tested and the result is positive. What is the chance that her baby actually has Down’s syndrome? ORGANIZING INPUTS 45 Now turn to Appendix 2 to find out what the right answer is and how to calculate it. The answers of the health professionals are also there. If you got the answer wrong, you will see that you are in good company. Experimental design and statistics are about taking valid decisions about what is true and false, particularly when the evidence is numerical. For example, one of Kahneman’s targets from his early days in the Israeli army was the interview. All the evidence suggests that interviews are, for most purposes, a hopeless way of selecting students, which is why most psychology departments gave up using them many years ago. However, even if we know this, we still feel confident in our judgements when we do interview people. We are also particularly bad at intuitive decisions based on numbers and we are, more generally, bad at evaluating decisions when we have made them. So if we are trying to decide whether one psychotherapy is better than another, whether a particular drug affects a particular kind of behaviour, or whether houses with burglar alarms are more or less likely to be burgled, we need careful design and statistics to help us find the truth.
46 STUDY SKILLS FOR PSYCHOLOGY STUDENTS This skill is essential in psychology, but of course, decisions like this pervade our everyday life as well. We are regularly taking decisions about what phone or car to buy, or what to do to keep healthy and slim. So learning how evidence should be collected (the design bit) and evaluated (this is where we may need statistics) to get at the truth and judge whether the advice you are being given is valid or not will be an important skill for you to carry with you for the rest of your life. Despite their obvious importance most of us approach experimental design and statistics with considerable apprehension. Coming to terms with design, which is about avoiding your data being influenced by factors that you are not interested in or that prevent you measuring what you want to measure, is the easier bit. It involves random assignment to groups, counterbalancing testing order to avoid practice effects, and so forth. Identifying confounding variables like these is largely just intelligent common sense. Avoiding them is a bit more difficult, but there are well-developed procedures that you will be introduced to in your methods classes and in any methods textbook. Statistics are intellectually more challenging. You should not be too worried, though. Andy Field, the author of our favourite, and much praised, statistics textbook writes, “I have a sticky history with maths because I used to be terrible at it. At 13, I was almost bottom of my class, yet 12 years later I’d written a statistics textbook” (Field, 2005, p. xxi). A second reason why you should not be too worried is that this is another area where base rate neglect rears its ugly head. We fail to take the base rate into account adequately when comparing our own abilities with those of others. In a review of the literature, Dunning, Heath, and Suls (2004, p. 69) conclude that “on average, people say that they are ‘above average’ in skill (a conclusion that defies statistical probability)”. Over-rating one’s driving ability is a particularly strong example of this tendency (see, for example, Horswill, Waylen & Tofield (2004). However, and this is the bit that is relevant to coping with statistics, recent work (Moore, 2007) suggests that this illusory self-aggrandisement is limited to common behaviours and abilities. For rarer and less common skills, the tendency is to underestimate our abilities. Statistics falls into this category, explaining why people often lack confidence in approaching the subject. Like cooking, experimental design and statistics can be tackled at two levels. You can do things from first principles, getting to grips with the underlying logic and maths, or in the case of cooking, the properties of different ingredients or flavours. Or you can buy a cookbook and follow the recipe. Think of Andy Field, or whoever wrote your recommended textbook, as the Jamie Oliver of statistics. They are good cooks and you trust their advice enough just to follow the recipe without worrying too much about why you soak some dried pulses before cooking and cook others before soaking them. You just do it and it works. Of course, it is more fun if you understand the underlying principles, and it enables
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164 SUCCESSFUL STUDYING Assessing t
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Appendix 3 Acronyms and abbreviatio
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References Aserinsky, E., & Kleitma
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218 INDEX Blindsight, 189 Body mass
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222 INDEX Phenomenology, 196 Piaget
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224 INDEX t-test, 209 Turnitin, 84-
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