iPad Notebook export for A Field Guide to Lies: Critical Thinking in the Information Age

August 27, 2017

Some quick quotes from
Citation (MLA): Levitin, Daniel J.. A Field Guide to Lies: Critical Thinking in the Information Age. Penguin Publishing Group, 2016. Kindle file.
that I really liked

Each short quote is preceded by the words “Highlight” & indication of the location in the book.

PART ONE | EVALUATING NUMBERS

Highlight(pink) – FUN WITH AVERAGES > Page 18 · Location 278 But be careful drawing conclusions about individuals and groups based on averages. The pitfalls here are so common that they have names: the ecological fallacy and the exception fallacy. The ecological fallacy occurs when we make inferences about an individual based on aggregate data (such as a group mean), and the exception fallacy occurs when we make inferences about a group based on knowledge of a few exceptional individuals. For example, imagine two small towns, each with only one hundred people. Town A has ninety-nine people earning $ 80,000 a year, and one super-wealthy person who struck oil on her property, earning $ 5,000,000 a year. Town B has fifty people earning $ 100,000 a year and fifty people earning $ 140,000. The mean income of Town A is $ 129,200 and the mean income of Town B is $ 120,000. Although Town A has a higher mean income, in ninety-nine
Highlight(pink) – FUN WITH AVERAGES > Page 21 · Location 309 Here is a brain-twister: The average child usually doesn’t come from the average family. Why? Because of shifting baselines. (I’m Highlight(pink) – PROBABILITIES > Page 117 · Location 1399
The consequences of such confusion are hardly just theoretical: Many court cases have hinged on a misapplication of conditional
probabilities, confusing the direction of what is known. A forensics expert may compute, correctly, that the probability of the blood found at the crime scene matching the defendant’s blood type by chance is only 1 percent. This is not at all the same as saying that there is only a 1 percent chance the defendant is innocent. What? Intuition tricks us again. The forensics expert is telling us the probability of a blood match given that the defendant is innocent: P( blood match | innocence)

PART TWO | EVALUATING WORDS
Highlight(pink) – OVERLOOKED, UNDERVALUED ALTERNATIVE EXPLANATIONS > Page 161 · Location 1947
A companion to the cherry-picking bias is selective windowing. This occurs when the information you

PART THREE | EVALUATING THE WORLD
Highlight(pink) – BAYESIAN THINKING IN SCIENCE AND IN COURT > Page 221 · Location 2679
The problem of mistakenly thinking that P( Guilty | Evidence) = P( Evidence | Guilt) is so widespread it has been dubbed the prosecutor’s fallacy.

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