Notes Essay

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Quantitative Methods Lecture Notes Levin et al. Chapters 1, 3, 6, 7, 8, 9, and 11 Chapter 1 – Introduction Let’s start with a cautionary tale Consider the following: A study of the incidence of kidney cancer in the 3,141 counties of the United States reveals a remarkable pattern. The counties in which the incidence of kidney cancer is lowest are mostly rural, sparsely populated, and located in traditionally Republican states in the Midwest, the South, and the West. What do you make of this? Gates Foundation made substantial investment in small schools based on a study that showed that the most successful schools, on average, are small. It turns out we are not very good statisticians. We like stories, but not really the source of the story. This causes us to make mistakes in evaluating the randomness of truly random events. For example take the sex of 6 babies born in sequence in a hospital. Consider three possibilities: BBBGGG GGGGGG BGBBGB Are the sequences equally likely? There is a widespread misunderstanding of randomness. Streaks in sports * We pay more attention to the content of messages than to information about their reliability, and as a result end up with a view of the world around us that is simpler and more coherent than the data justify * Many facts of the world are due to chance. Causal explanations of chance events are inevitably wrong. * Even faced with data to the contrary, we tend to stick to our stories We see this illusion of understanding used in a lot of business books. “Let’s look at what previously successful people did and copy them”. Stories of success and failure consistently exaggerate the impact of leadership style and management practices on firm outcomes. A study of Fortune’s “Most Admired Companies” finds that over at twenty-year period, the firms with the worst ratings went on to

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