Lesson Two: How Charts can be Manipulated.Lesson One: The way we gather information for Stats is inherently wrong.Darrell Huff: How to Lie with Statistics.If I haven’t taken notes like this for a book, it probably means I didn’t enjoy it that much or don’t think that its lessons will stand the test of time. All I can say is that me taking notes on a book like this is the greatest endorsement that I can give to a book. If you’ve enjoyed this book summary, order the book online! It’s a short, easy read.įinally, for those wondering why I do book summaries like this, I am not really sure why. Never take a statistic at face value – everyone has a bias, so go to the source material.Ĭhapter 10: How to Talk Back to a Statistic The author of a chart is probably misleading you with the axis.Ībsolute changes are somewhat meaningless without ascertaining what is the percentage increase or decrease.Īlways question if one result is being used to infer something else that doesn’t necessarily follow. Remember the importance of standard error and always keep the ‘plus-or-minus’ in mind… They tell you incredibly useful things about the underlying data that will help inform your own conclusions about a study.Ĭhapter 4: Much Ado about Practically Nothing If these figures aren’t provided in an article (they probably won’t be), then go to the source material and look for them there. Is the ‘average’ the mean, median, or the mode?Ĭhapter 3: The Little Figures That Are Not There.
Those that present conclusions of studies will likely not be forthcoming regarding those biases since they want to push their own agenda: Always go to the source material!Īlmost every sample has a bias that you need to be aware of in order to draw accurate conclusions. As such, while this summary will hopefully whet your appetite, there is no substitute for the real thing. The most important lesson to take away from the book is to always go to the source material when you’re presented with facts & opinions.
This book is great for anyone that wants a refresher on the most common statistical shenanigans that are all around us. How to Lie with Statistics was written in 1954 but is even more relevant today than it was at the time of writing.
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