Download Mobi The Data Detective: Ten Easy Rules to Make Sense of Statistics By Tim Harford
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Ebook About From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter. As “perhaps the best popular economics writer in the world” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.Book The Data Detective: Ten Easy Rules to Make Sense of Statistics Review :
Darrell Huff's classic book, How to Lie with Statistics, warns us not to get misled by statistics. In this book, Tim Harford tells us how to see the Truth with statistics. He gives us ten rules of thumb for thinking about reported numbers. But the real reason for reading the book is for all of the stories Harford tells to illustrate each rule. It's like the greatest hits from the BBC radio show he has hosted for years.Here is a simple summary of the ten rules:1. When considering new information, pay attention to how it makes you feel. Your emotions can influence you to dismiss accurate statistics that you do not like and to embrace false statistics that you do like2. Sometimes your personal experience (a worm's eye view) conflicts with a bird's-eye view statistic. For example, the subway may be only half full on average during the day but packed every time you ride it (during rush hour). Both perspectives help you understand the truth.3. Make sure you understand what is being counted. When counting beans, the definition of a bean matters.4. Look for information that can put a statistic into context, like the trend, the scale, or how it compares to other situations.5. Try to learn where the statistics came from (the backstory) – and what other data might have vanished into obscurity.6. Ask who is missing from the data, and would our conclusions differ if they were included.7. Ask tough questions about algorithms and the big datasets that drive them, recognizing that without intelligent openness they cannot be trusted.8. Pay more attention to the bedrock of official statistics – and the sometimes heroic statisticians who protect it.9. Look under the surface of any beautiful graph or chart. Don't let the beauty mislead you.10. Keep an open mind, asking how we might be mistaken and whether the facts have changed.Those ten tips sound boring, but Harford's stories are not. Most of them show the power of useful statistics. As Harford says: "Good statistics are not smoke and mirrors; in fact, they help us see more clearly. Good statistics are like a telescope for an astronomer, a microscope for a bacteriologist, or an X-ray for a radiologist." You are going to say I am being overly critical in my rating and review, and that I am biased myself. To his credit, Harford admits that he has friends on the left and leaves out his friends on the right. How am I supposed to interpret this in the context of his analysis of the climate change debate? Yet in a book about responsible use of statistics, how is the interpretation of data not supposed to be objective if one wants to gain maximum credibility?Harford appears to do with "climate change" what most other "data detectives" do - leaving out the elephant in the room. Somehow, the author seems to want the reader to believe that his thoughtful, unbiased perspective on climate change data is correct and therefore the rest of the book too on all the other topics.Harford thoughtfully addresses the issue of bias and how there is a certain type of bias that is extremely hard to overcome. Unfortunately, it seems he falls prey to it himself. What is this elephant that I am referring to? Population size. As scientists appear to have concluded beyond a reasonable doubt, climate change today is dwarfed by climate change events in the past even when there wasn't a single human being on the planet. The only difference with today is that "climate change" appears to jeopardize the comfortable way of life of the "rich" few, and the living space of the "poor," mostlyby virtue of rising sea water levels. As humans we are now around to notice and get upset about it. Yet somehow, climate change activists want everyone to believe that between the ~1.5 billion of 1940 and ~7.5 billion today, the additional pollution, consumption and other habits of those extra 6 billion people should be discounted as trivial. Somehow, we are all supposed to believe that because we as humans are around to observe, measure, and interpret (biased or not) changes in the planet's climate, it is therefore only we who cause it and everybody who says it is not (only) us is obviously wrong.How am I supposed to not read the rest of the book with a huge grain of salt Mr. Harford? Why not suggest that population size could have an impact? Why not suggest that institutionalized narcissism/psychopathy is the root cause of our denial? Not the denial about climate change. I am talking about denial that we already have the solution. How many more credible alternatives to fossil fuel use do we have to invent for somebody with influence to take a pick and tell us all this is it? I am not talking about Elon Musk either with this flagrant display of a 100 year old technology that he didn't build and that causes so many negative side effects, presumably easily exported to less affected countries.Harford continues along the same line of a thin argument by addressing the anti-vaxx movement in what seems to be a one sentence denial of their motive. One study, Harford claims, put to rest the argument that vaccination would be the cause of autism. Never mind that there are many different kinds of autism, that autism exists on a scale (spectrum disorder, remember that distinction Mr. Harford?) and that apparently other studies show how in certain communities much higher rates of autism were found that could not be explained as a result of the natural process that Harford prefers to favor.The stories Harford otherwise shares to validate his opinions appear certainly entertaining. Perhaps no human is capable of writing a book about statistics completely free of bias. In this case, it seems I was unfortunately duped into believing "Data Detective" came close to accomplishing that goal.By the way, Mr. Harford, Amsterdam did not suffer starvation during WWII. That was only in the winter of '44-'45, the socalled "Hunger Winter." There appears to have actually been an economic boom in the Netherlands during the first years of the war. Perhaps it was because the Dutch simply wanted to survive after their government and the royal family left the country for greener pastures, or because the Dutch had a hunch that the Nazi regime would eventually bite the dust and more sensible Germans would gain the upper hand again, people with whom they had always had good trading relations.Having said that, it may be that Data Detective would have had much more of an impact for me if Harford had considered one aspect of statistics that seems often overlooked: context. While it may be relatively easy to extract data from a population, it may be less easy to interpret that data in the psychological and emotional context from which the data springs forth. If narcissism is as widespread and engrained as it appears to be, it would explain why society's problems have such a hard time being properly understood and solved.When one has as much data to process as Harford apparently went through to write a book, and finish it in a reasonable amount of time, it is understandable that not every topic gets the treatment it would seem to deserve in the eyes of some - well, me in this instance. 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