Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

# Naked Statistics: Stripping the Dread from the Data

Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

Compare

4out of 5Robert Muller–I couldn't get through this book, mainly because I know too much about statistics and I know too much about the specific examples he gives to illustrate his points. Unfortunately, while at times Wheelan does convey the underlying concepts of probability and statistics in a way that would help you understand them at a basic level, he does so in what I would regard as a patronizingly oversimplified way. If you compare this book to Nate Silver's book on prediction or, indeed, to the book he says mo I couldn't get through this book, mainly because I know too much about statistics and I know too much about the specific examples he gives to illustrate his points. Unfortunately, while at times Wheelan does convey the underlying concepts of probability and statistics in a way that would help you understand them at a basic level, he does so in what I would regard as a patronizingly oversimplified way. If you compare this book to Nate Silver's book on prediction or, indeed, to the book he says motivated him (How to Lie with Statistics), this book simply doesn't deliver the goods. It clothes the concepts of statistics in yet another layer of misunderstanding and half truth. If, for example, he had spent a chapter on "unemployment" and really showed how, as a descriptive statistic, the number is meaningless for all kinds of measurement and theoretical reasons, I would have been impressed. Instead, he used it as an example of a good statistic. If he had cited Savage's "The Flaw of Averages" while making points about averages, dispersion, and distributions (the wrong points, I might add), I would have been impressed. If he had at least *mentioned* Bayes Rule and Bayesian statistics, I would have been impressed. I wasn't impressed.

4out of 5☘Misericordia☘ ~ The Serendipity Aegis ~ ⚡ϟ⚡ϟ⚡⛈ ✺❂❤❣–Cool and easy. Even though I would have liked more advanced stuff made easy and cheesy.

4out of 5DonkeyPopsicle–There are many popular science books that try to teach basic statistical concepts, but more often than not they fall into the awful popular science trope of narrative over concepts that Malcolm Gladwell introduced into science writing and then Jonah Lehrer perfected into an awful, horrible art. Take Nate Silver's lauded book 'The Signal and the Noise'. Each chapter is about some specific area of prediction, and along the way some statistical concepts are introduced but rarely elaborated [I will There are many popular science books that try to teach basic statistical concepts, but more often than not they fall into the awful popular science trope of narrative over concepts that Malcolm Gladwell introduced into science writing and then Jonah Lehrer perfected into an awful, horrible art. Take Nate Silver's lauded book 'The Signal and the Noise'. Each chapter is about some specific area of prediction, and along the way some statistical concepts are introduced but rarely elaborated [I will note that Nate Silver only rarely mentions what the expert had for lunch during their interview, unlike much worse science books that presume we are interested in the culinary habits of scientists]. In that book, Silver also tries to make a case for Bayesian statistics over traditional statistics, but because the explanation of the concepts is not very rigorous, we don't get so much an argument as an opinion. Charles Wheelan's book is a fantastic antidote to modern popular science writing and conceptual hand-waving. In a nutshell, the book is a stats 101 course without the math. Unlike, say, popular physics books where understanding can only be vaguely metaphorical at best without knowing quite a bit of advanced mathematics (giving the illusion of knowledge; yes, you've read "The Elegant Universe", but sorry, you still know bupkis about string theory), statistical concepts can be explained and even employed in a critical fashion without much math at all. Knowing that variation is much more informative than simply the mean doesn't require that you know calculus. Likewise for understanding simple experimental design (and most experimental designs are simple: state a null, apply Student's t-test, and you've got 70% of published scientific papers). Of course, saying that something can be explained without math is not the same as actually doing it proficiently, but Wheelan has excelled here. The examples are all intuitive, and the writing is clear and easy. Perhaps more importantly, Wheelan spends an entire chapter on the Central Limit Theorem halfway through the book, and then uses that to explain statistical inference, sampling, and regression. Giving the Central Limit Theorem such pride of place is appropriate but is often neglected in basic statistics textbooks (not to mention popular statistics books). The book is not flawless, but the quibbles are minor. First, Wheelan has a silly sense of humor that intrudes into the book too often (culminating in several pointless footnotes that only serve to extend jokes). Second, although there are a few mathematical appendices for various chapters, they are generally far too short and actually need more math than they have. As it is, they are likely to confuse more than help. In general, Wheelan's book is a must read for anyone that hasn't taken a basic stats course (so every journalist ever) or can't remember much from when they did take it.

5out of 5Herve–I have already talked about statistics here, and not in good terms. It was mostly related to Nicholas Nassim Taleb`s works, The Black Swan and Antifragile. But this does not mean statistics are bad. They may just be dangerous when used stupidly. It is what Charles Wheelan explains among other things in Naked Statistics. Naked Statistics belongs to the group of Popular Science. Americans often have a talent to explain science for a general audience. Wheelan has it too. So if you do not know about I have already talked about statistics here, and not in good terms. It was mostly related to Nicholas Nassim Taleb`s works, The Black Swan and Antifragile. But this does not mean statistics are bad. They may just be dangerous when used stupidly. It is what Charles Wheelan explains among other things in Naked Statistics. Naked Statistics belongs to the group of Popular Science. Americans often have a talent to explain science for a general audience. Wheelan has it too. So if you do not know about or hate the concepts of mean/average, standard deviation, probability, regression analysis, and even central limit theorem, you may change your mind after reading his book. Also you will be explained the Monty Hall problem or equivalent Three Prisoners problem or why it is sometimes better (even if counterintuitive) to change your mind. Finally Wheelan illustrates why statistics are useless and even dangerous when the data used are badly built or irrelevant (even if the mathematical tools are correctly used!). Just one example in scientific research (which is another topic of concern to me) "This phenomenon can plague even legitimate research. The accepted convention is to reject a hypothesis when we observe something that would happen by chance only 1 in 20 times or less if the hypothesis were true. Of course, if we conduct 20 studies, or if we include 20 junk variables in a single regression equation, then on average, we will get 1 bogus statistically significant finding. The New York Times magazine captured this tension wonderfully in a quotation from Richard Peto, a medical statistician and epidemiologist: "Epidemiology is so beautiful and provides such an important perspective on human life and death, but an incredible amount of rubbish is published". Even the results of clinical trials, which are usually randomized experiments and therefore the gold standard of medical research, should be viewed with some skepticism. In 2011, the Wall Street Journal ran a front-page story on what it described as one of the "dirty little secrets" of medical research: "Most results, including those that appear in top-flight peer-reviewed journals, can't be reproduced. [...] If researchers and medical journals pay attention to positive findings and ignore negative findings, then they may well publish the one study that finds a drug effective and ignore the nineteen in which it has no effect. [...] On top of that, researchers may have some conscious or unconscious bias, either because of a strongly held prior belief or because a positive finding would be better for their career. (No one ever gets rich or famous by proving what doesn't cure cancer. [...] Dr. Ionnadis [a Greek doctor and epidemiologist] estimates that roughly half of the scientific papers published will eventually turn out to be wrong." [Pages 222-223]

5out of 5Dan Lutts–Excellent book for the layperson that gives you a solid grasp of statistics as well as how statistics can be used and abused. As Wheelan says in the book: Statistics don't lie, but the data behind them can because they can be faulty, misleading, or downright false. Reading the book helps you become more critical so you won't naively believe a person or organization's argument when they cite statistics to support their case or when you read about scientific breakthroughs in the newspaper or other Excellent book for the layperson that gives you a solid grasp of statistics as well as how statistics can be used and abused. As Wheelan says in the book: Statistics don't lie, but the data behind them can because they can be faulty, misleading, or downright false. Reading the book helps you become more critical so you won't naively believe a person or organization's argument when they cite statistics to support their case or when you read about scientific breakthroughs in the newspaper or other claims based on statistics. Here's one interesting thing Wheelan says: about half the articles in medical journals are eventually pulled because their statistics are wrong.

5out of 5Wen–A solid five-star. If only I had had Charles Wheelan as my college statistics professor! :) The synopsis on Goodreads was a good review,so I'll save some ink here. These were all basic statistic concepts, from probability to regression. While breaking down the basic concepts, Wheelan sought to caltivate intuition around them. And he did a fantastic job. Better yet, he made me chuckle all the time with those funny, sometimes provocative real-life examples. Some of the examples, like the route cause A solid five-star. If only I had had Charles Wheelan as my college statistics professor! :) The synopsis on Goodreads was a good review,so I'll save some ink here. These were all basic statistic concepts, from probability to regression. While breaking down the basic concepts, Wheelan sought to caltivate intuition around them. And he did a fantastic job. Better yet, he made me chuckle all the time with those funny, sometimes provocative real-life examples. Some of the examples, like the route cause of the 2008 financial crisis and the Monty Hall problem, have been widely telegraphed; I’d assume Wheelan’s explanations will make them easier to sink in. I took statistics classes during two phases of my education, but am currently using little of it at work. Given big data is on the rise, and large free data sets are becoming more obtainable, I’m toying the idea of taking data crunching as a pastime. To challenge myself, I opted for the audiobook and played it at double speed. Not until double-digit chapters when I had to pause and rewind, because keeping four-digit numbers in my head became impossible on the noisy subway. That said, Wheelan did not lose a beat, or his cool, in breaking down more difficult hypothesis testing and multivariate regression for a lay person. I applaud making audiobook available for math-related subjects; it would benefit visually impaired students who might otherwise find math’s too daunting. On that note, Jonathan Davis did a wonderful job with his smooth narration and sense of humor pretty much syncs with the author.

5out of 5Petre–Good intro book for aspiring to be statistician. Simple explanation for very complicated concepts.

5out of 5Jenne–This is not the most exciting book ever, but it's way more exciting than you would think for a book about statistics. More importantly, people: YOU NEED TO KNOW THIS STUFF. This is how you separate the lies from the damn lies from the nonsense that TV news shows spew at you. I don't care if you read THIS one, but please just fucking read a book about statistics. THANK you.

4out of 5Caitlin–Being a mathematics and statistics teacher, of course I am inclined to enjoy a statistics book. There were times I found myself a bit bored because I was being explained basic statistical concepts of which I already possess a wider understanding. This book is an excellent recommendation to students just starting statistics as it gives practical and engaging examples of statistics and easy to follow. For those who already have a broad understanding of statistical topics as well as commonly used e Being a mathematics and statistics teacher, of course I am inclined to enjoy a statistics book. There were times I found myself a bit bored because I was being explained basic statistical concepts of which I already possess a wider understanding. This book is an excellent recommendation to students just starting statistics as it gives practical and engaging examples of statistics and easy to follow. For those who already have a broad understanding of statistical topics as well as commonly used examples of probability, this book can be repetitive and frustrating. It also bothered me that at more than one time throughout the book Wheelan assumes that the reader does not wish to know more about these topics and so he has processed information so we don't have to. These are more of the things I would have liked to know more about but then perhaps I should have been reading a different book if that was what I was desiring. Overall, a well written book about probability and statistics. Useful to anyone who is just starting a journey in statistics as it breaks down various statistical concepts that can be confusing to a beginner.

4out of 5Dale–Very engaging. There are 3 categories of readers who would enjoy or benefit from this book: 1. People who are generally curious about things and want to know why someone might say that statistics is becoming 'sexy'. 2. People who are just starting a statistics 101 class, or are about to, and would like some motivation. 3. People who know a fair bit about statistics but who would like a little perspective and history. Wheelan, as advertised, is an entertaining writer who sort of draws you in with litt Very engaging. There are 3 categories of readers who would enjoy or benefit from this book: 1. People who are generally curious about things and want to know why someone might say that statistics is becoming 'sexy'. 2. People who are just starting a statistics 101 class, or are about to, and would like some motivation. 3. People who know a fair bit about statistics but who would like a little perspective and history. Wheelan, as advertised, is an entertaining writer who sort of draws you in with little stories of statistical mysteries, mistakes, and deceptions. It's a fairly easy read, and you won't know much statistics by the end of the book, but I think you'll understand why it's an important field.

4out of 5Patrik–How good is this book? After reading "Naked Statistics" I wanted to teach an introductory statistics course! I could see myself engaging the students with really cool stories, confuse them with fun probability examples, only to wittily explain it clearly a minute later. I would pursue the connection between probability and inference and they would all clearly understand hypothesis testing. I would give great tales of statistics being misused and the students and I would chuckle together over how How good is this book? After reading "Naked Statistics" I wanted to teach an introductory statistics course! I could see myself engaging the students with really cool stories, confuse them with fun probability examples, only to wittily explain it clearly a minute later. I would pursue the connection between probability and inference and they would all clearly understand hypothesis testing. I would give great tales of statistics being misused and the students and I would chuckle together over how famous researchers made mistakes. Then we would promise to never make such silly mistakes ourselves. I would never show the students "Naked Statistics," always pretending that I came up with the examples by myself... The students would love me. The administration would love me. I would receive awards, promotions, and (finally) significant pay raises. That is how good this book is. Too bad I don't teach statistics...

4out of 5Elizabeth Theiss–An amusing, clear, and even fun introduction to basic statistics and probability, this gem explains foundational concepts and provides compelling examples to illuminate them. It covers correlation, normal distributions, the central limit theorem, significance, standard error, multiple regression, and so on in a way that math-phobes can likely handle without panic attacks. I wish I had read this before taking grad stats. The truth is that students of statistics today can use Excel, SPSS, Stata an An amusing, clear, and even fun introduction to basic statistics and probability, this gem explains foundational concepts and provides compelling examples to illuminate them. It covers correlation, normal distributions, the central limit theorem, significance, standard error, multiple regression, and so on in a way that math-phobes can likely handle without panic attacks. I wish I had read this before taking grad stats. The truth is that students of statistics today can use Excel, SPSS, Stata and similar programs to calculate statistics. So the focus has changed from working formulas to gaining a deep understanding of the assumptions, meaning, and limitations of statistics. Wheelan's excellent book provides the background for this understanding in a readily comprehensible way.

4out of 5Sarah–I was too frustrated with the author's tone to finish. He introduces the book by explaining why he doesn't like calculus. He recalls "schooling" his high school calculus teacher when his class was given the wrong version of the AP Calculus exam. The story felt unfitting and painted the author as a punk, and the tone continues. To paraphrase an example of accuracy vs. precision, "'Go through two lights, take a left at the second light and I'm the tthird house on the right' is accurate, 'I live 4. I was too frustrated with the author's tone to finish. He introduces the book by explaining why he doesn't like calculus. He recalls "schooling" his high school calculus teacher when his class was given the wrong version of the AP Calculus exam. The story felt unfitting and painted the author as a punk, and the tone continues. To paraphrase an example of accuracy vs. precision, "'Go through two lights, take a left at the second light and I'm the tthird house on the right' is accurate, 'I live 4.23 miles SW' is precise, and 'I live a really f---ing long way' is neither." Why the last example? I put this book down, disappointed.

4out of 5Amy–Statistics 101 with cheesy jokes.

5out of 5Jacob–Another good Wheelan, similar to Naked Economics: Undressing the Dismal Science. There are a few topics that overlap a bit, but the author does a good job of keeping them separate. This has much of the personal anecdotes / history that make the topic more interesting, and the author includes more silly scenarios in this one which keep you engaged, such as the continually missing & crashing buses of marathon runners and sausage festival attendees. Unfortunately, the third quarter of the book gets Another good Wheelan, similar to Naked Economics: Undressing the Dismal Science. There are a few topics that overlap a bit, but the author does a good job of keeping them separate. This has much of the personal anecdotes / history that make the topic more interesting, and the author includes more silly scenarios in this one which keep you engaged, such as the continually missing & crashing buses of marathon runners and sausage festival attendees. Unfortunately, the third quarter of the book gets a bit dry and stultifying when the author discusses Inference, Polling, and Regression Analysis, but the last quarter redeems itself with discussions of regression analysis mistakes and how statistics is being used to address social problems. Those discussions are once again engaging and meaningful, and include issues such as the increase in autism rate, how to tell good teachers from bad and change teacher's pay to reward the good ones, and how to reduce global poverty (this is one of the slightly overlapping bits with Naked Economics). I also found the numerous discussions of how statistical inference can go wrong to be extremely helpful -- like any tool, you have to know what it's good for and when. Wheelan brings up that even in peer-reviewed medical journals, many if not most of the findings can't be repeated. There's also mention of a paper that finds about half the peer-reviewed papers (remember, these are supposed to be the vetted ones) are wrong, with the irony noted that if the author's right, then he's just as likely to be wrong.

4out of 5Morgan Blackledge–I read this as a supplemental text for a statistics course. Its pretty good in terms of providing fun examples of statistics constructs, written in an accessible, punchy, relatable voice. I think I was a little underwhelmed because other authors have written really well on the same subject e.g. The Signal And The Noise by Nate Sliver, The Black Swan (or really anything) by Nassim Nicholas Taleb and the Drunkard's Walk by Leonard Mlodinow. I LOVED all of those books, and they are extremely tough a I read this as a supplemental text for a statistics course. Its pretty good in terms of providing fun examples of statistics constructs, written in an accessible, punchy, relatable voice. I think I was a little underwhelmed because other authors have written really well on the same subject e.g. The Signal And The Noise by Nate Sliver, The Black Swan (or really anything) by Nassim Nicholas Taleb and the Drunkard's Walk by Leonard Mlodinow. I LOVED all of those books, and they are extremely tough acts to follow. I can recommend Naked Statistics, but I urge the would-be reader to consider picking up the other books mentioned as well. You’re not going to know statistics after you read these texts. That takes a different kind of systematic study and practice. But you will be able to relate to statistics better, and you just might become enchanted by the worldview statistics engenders. Three of these 😐😐😐

5out of 5Eny Rebel–This was one of the best and simplest books about statistics I've ever read. I'm not a math major person, not a statistician and honestly I am not very interested in deep theoretical knowledge about statistics. This book helped me to understand the statistics in easy and simple way from a business viewpoint. I rarely got bored reading it, which is hard to say for most books of statistics and economics. Because the book entertained me , enlightened me and used practical, meaningful, real life exa This was one of the best and simplest books about statistics I've ever read. I'm not a math major person, not a statistician and honestly I am not very interested in deep theoretical knowledge about statistics. This book helped me to understand the statistics in easy and simple way from a business viewpoint. I rarely got bored reading it, which is hard to say for most books of statistics and economics. Because the book entertained me , enlightened me and used practical, meaningful, real life examples in each chapter

5out of 5Ned–This book is a great primer for those who are not familiar with basic statistical concepts (in fact, I encourage you to read it as statistics can be highly manipulative). If you have completed at least one university-level statistics course or the equivalent then you can safely pass on this book (most advanced topics: OLS regression and t-statistics).

5out of 5Dmytro–This book attempts to provide an introduction to the field of statistics in plain language in the form of stories. I found that the method they took was too long winded. It would have been better to just explain the core mathematical concepts.

5out of 5Michael Lynch–Laughter is rarely associated with Statistics in my experience, but I laughed all the way through this book. Math-y people will love it, and math-challenged people will discover that stats can be fun. WHO KNEW? Statistics made an indelible impression on my life. More twenty years ago, I was enrolled in a graduate program in logistics management, knee deep in a graduate level stats class. I turned the full glare of my undergraduate education in English literature on the problem, t Laughter is rarely associated with Statistics in my experience, but I laughed all the way through this book. Math-y people will love it, and math-challenged people will discover that stats can be fun. WHO KNEW? Statistics made an indelible impression on my life. More twenty years ago, I was enrolled in a graduate program in logistics management, knee deep in a graduate level stats class. I turned the full glare of my undergraduate education in English literature on the problem, to no avail. I struggled. I studied. I prayed...and that is probably what got me through the course. At the end of the semester, having passed the course against what I believed to be statistically impossible odds, I changed schools and changed majors and never looked back....statistics made me a historian. Wheelan has made a dense, mundane, somewhat incomprehensible subject not only accessible, but enjoyable. He explains things in layman's terms with humor and creative examples, and makes the reader say, "Oh! I get it now!" The casual reader or non specialist may glance at the title and be vaguely interested. The word "naked" comes first, offering the promise of something naughty, perhaps even salacious. As the casual reader glances around to see who is watching before he picks it up to flip through the pictures, he catches that second word, "statistics," a cold bucket of water on most any libido (economists and statisticians will find the illustrations titillating). The important part, however, is the subtitle: He really does strip the dread from the data, and replaces that dread with understanding. Though math-y people will enjoy it, this book is especially for the casual reader: the one who took a casual approach to math in school, yet could find no causal relationship to his poor grades. How good is the book? I offer the following data points: 1) I read portions of every chapter to my wife, the math teacher, and have promised to let her read it next. 2) I have ordered another copy for my daughter, who majored in math and is now an engineer. 3) I've ordered two more of his similar works, Naked Economics and Naked Money. 4) I've begun thinking about how I can strengthen my own historical research and analysis with appropriate statistics. Any book that can make me say I enjoy statistics is a very good book indeed!

4out of 5Coan–Naked Statistics by Charles Wheelan Numbers are sexy. There’s no denying it. People like numbers and measuring things. They like seeing the ranking of their favourite sports stars, hearing what the latest political polls are saying or just knowing what CPI is doing. But for all this, many people might not know how these numbers such as ranks, sampling means, indexes etc, are actually derived and how they can be best used or questioned. If you’re interested in this topic (and there is a good chanc Naked Statistics by Charles Wheelan Numbers are sexy. There’s no denying it. People like numbers and measuring things. They like seeing the ranking of their favourite sports stars, hearing what the latest political polls are saying or just knowing what CPI is doing. But for all this, many people might not know how these numbers such as ranks, sampling means, indexes etc, are actually derived and how they can be best used or questioned. If you’re interested in this topic (and there is a good chance you are if you’re reading a review about a book on statistics), then let me explain why this book may or may not be for you. Naked Statistics aims to explain 1st semester University quantitative analysis material in a fun way. Hold up, get back here. It’s not as hard as it sounds and is aided tremendously by the author only getting very mildly technical when really needed. In fact, they add appendices for some of the jargon heavy parts which you can then ignore or read at your leisure. Covering things such as the basics of correlation, averages and standard deviation (items you might recall from high school) to the early stages of multi-variate, regression analysis; this book does a good job of explaining what these are and how they work. Some formulas are available in the notes but really the book aims to raise the reader’s awareness rather than be an instructional text on how to undertake the math. Being, essentially, a plain English mathematics book, the author walks that fine line of mainstream ease of understanding, numbers and imparting good insights that can get you thinking. I think it helps that the author isn’t actually a statistician which has allowed them to avoid some pitfalls I’ve seen in other books which are more jargon heavy and academic in prose. Ultimately your mileage will vary based on your background knowledge. I read the book as a bit of a refresh on some points but a lot of the examples (Netflix correlation algorithms, program evaluation in schools, big data mining etc) weren’t new to me. However if you don’t study/work in this field, I think it is an eminently fine choice to broaden your horizons. It may also help raise your awareness of poor statistics and how they can be misused. Before you ask, yes there are jokes in the book. But no, there aren’t any statistics puns. Some geekery ensues around the author’s obvious love for statistics -but that’s not a bad thing 😊 4/5 stars.

4out of 5Elizabeth Davis–Actually a pretty good book for building your conceptual understanding of statistics. Starts almost frustratingly simple, but eventually explores interesting and foundational concepts like the central limit theorem and multiple regression analysis. Charles Wheelan is a pretty good writer and the book reads well with lots of entertaining digressions. And a lot of the studies explored in the book were interesting, and allowed for compelling real-world examples of the book’s concepts. But some exam Actually a pretty good book for building your conceptual understanding of statistics. Starts almost frustratingly simple, but eventually explores interesting and foundational concepts like the central limit theorem and multiple regression analysis. Charles Wheelan is a pretty good writer and the book reads well with lots of entertaining digressions. And a lot of the studies explored in the book were interesting, and allowed for compelling real-world examples of the book’s concepts. But some examples tended towards problematic: such as a study that explains away the statistical significance of discrimination in the gender pay gap and other studies that validate increased policing and juvenile incarceration. These societal issues are very complex, are still being researched, and understandably cannot be fully deconstructed in a book whose main purpose is to simplify major statistics concepts. In my opinion, a lot of nuance is required to engage on topics like this, and citing them in a popular book without that nuance was an interesting pedagogical decision that I don’t really agree with. Nevertheless, it’s a decent book to start with if you want to dive deeper into statistics in the future, or you’re just curious enough to build up your higher level understanding. If you have a stats background, though, I doubt this book would be too helpful, unless you’d like to become a stats teacher or TA.

4out of 5Sandesh Rawat–Exactly what I expected this book to be -- a compelling read on Statistics and its practical usage. The language is easy to read and examples given are super witty and relatable. For instance, I could totally relate the test vs control methodology that I'd used for one of my clients and few things that should have been more careful about. Charles shares all complex/technical stuff in Appendix at the end of respective chapters (so it's up to you if you want to get into the dirty stuff). The book i Exactly what I expected this book to be -- a compelling read on Statistics and its practical usage. The language is easy to read and examples given are super witty and relatable. For instance, I could totally relate the test vs control methodology that I'd used for one of my clients and few things that should have been more careful about. Charles shares all complex/technical stuff in Appendix at the end of respective chapters (so it's up to you if you want to get into the dirty stuff). The book is filled with real-life examples. I'd say anyone - no matter what their profession is - will take something away from the book. For example, I'm not buying a lottery ticket, ever! or I'm not purchasing an extended warranty for my $99 printer. Charles definitely gives the reader a new lens to look at things. Post reading this, you’ll think twice before believing the outcomes of polls/surveys or sensational headlines such as “wearing blue socks improves your GMAT score”(lol). I could somewhat link the narrative of this book with another book called Narrative and Numbers by Aswath Damodaran. Bottom-line of both of these books is: don't take statistics/numbers at their face value, use your judgement - because numbers by themselves can't! I'd definitely love to read Charles’ other 2 books - Naked Economics and Naked Money.

4out of 5Taufan Satrio–This should've been a supplementary reading material during my college years. It altered my sentiment towards Statistics and Probability to the point where curiosity and intuition can take its place and do their job. Its concise writing and examples will help you dissect unfathomable formulas, find their core concept, and make you smile while you're at it

5out of 5Thao Nguyen–This might be a good book for a normal non-statistical person with intuitive explanation of several basic concepts: descriptive statistics, correlation and such. Too bad, I work with statistics so the choice of examples seems redundant for me from time to time, some are even obscure and confused. Especially for those who are not familiar with American things (voting, baseball, etc), this book may seem to be a very tedious reading. Overall, a fair good read, at least you can get some intuition on This might be a good book for a normal non-statistical person with intuitive explanation of several basic concepts: descriptive statistics, correlation and such. Too bad, I work with statistics so the choice of examples seems redundant for me from time to time, some are even obscure and confused. Especially for those who are not familiar with American things (voting, baseball, etc), this book may seem to be a very tedious reading. Overall, a fair good read, at least you can get some intuition on stats.

4out of 5Aju–Mandatory reading for those just getting into statistics and those already familiar with it. Totally focusing on the "why" with interesting examples and gotchas. Ensures you will ask the right questions in most practical applications of statistics. I'll be re-reading this one every once in a way.

4out of 5Katie–Useful review of statistics with easy to understand examples

5out of 5Nana–Instead of focusing on the theory and the mathematics behind each equation, the author explains the intuitive ideas and gives practical examples which help me comprehend statistics much easier.

4out of 5Phong Vu–Fun introductory book for statistics, which addresses several key concepts and usages of the subject. It doesn't dive deep into boring formulas, just introduces the intuitions and reasons why they matter.

5out of 5Mommalibrarian–This books shows no calculations and a very small number of formulas. "The point of statistics is not to do myriad rigorous mathematical calculations; the point is to gain insight into meaningful social phenomena. Statistical inference is really just the marriage of two concepts that we've already discussed: data and probability (with a little help from the central limit theorem)." Given this emphasis I think almost anyone, with no background in statistics, could get a good feel for the meaning This books shows no calculations and a very small number of formulas. "The point of statistics is not to do myriad rigorous mathematical calculations; the point is to gain insight into meaningful social phenomena. Statistical inference is really just the marriage of two concepts that we've already discussed: data and probability (with a little help from the central limit theorem)." Given this emphasis I think almost anyone, with no background in statistics, could get a good feel for the meaning of the terms and the relationship of the pieces used to form the calculations. The following was written with mathematical symbols in the text. "SE = s divided by the square root of n, where s is the standard deviation of the population from which the sample is drawn, and n is the size of the sample. Keep your head about you! Don't let the appearance of letters mess up the basic intuition. A large sample drawn from a highly dispersed population is also likely to be highly dispersed; a large sample from a population clustered tightly around the mean is also likely to be clustered tightly around the mean....This is why the standard deviation (s) is in the numerator" The examples are lively. There are footnotes pointing out when extra mathematics would be applied in a real situation and slightly more in-depth discussions but still no calculations in separate end of each chapter appendices. He calls the detail of most of the mathematics frosting on the cake and maintains they are not necessary to understand the basic relationship expressed in the equations. I had one course in statistics from the psychology department (not the math department) during college and did not feel I learned anything new from this book. I was hoping for more about lying with statistics. Evaluating statistics was touched on - I guess I just wanted more.