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on November 25, 2016
Naked Statistics is very well done. This book gives you an entry look into the world of statistics. If you have ever been curious about how statistics work, and never took a class, this book would be good for you. Charles Wheelan talks about what statistics does and what it looks at, but doesn’t get in to how it works. He really simplifies the topic to make it easy for anyone to understand.
The book is written from a perspective that the audience hates statistics and has never wanted to look into it at all. Wheelan does a great job in addressing that, and he tries to make the process less painful. His examples are off the wall and make reading the book entertaining.
This book doesn’t really teach you statistics, but tries to peak your curiosity, so you do continue on your learning journey. He doesn’t go into all of the pesky details of why the math works, but he does have appendixes and sources of where he gathers all of his sources for each section of statistics he goes over.
I really liked how Wheelan explained how different groups can mess with data depending on how it is interpreted or how people can skew the methodology to produce certain results. He has a great explanation of how people lie with statistics or distort confidence in results.
The book is written from a perspective that the audience hates statistics and has never wanted to look into it at all. Wheelan does a great job in addressing that, and he tries to make the process less painful. His examples are off the wall and make reading the book entertaining.
This book doesn’t really teach you statistics, but tries to peak your curiosity, so you do continue on your learning journey. He doesn’t go into all of the pesky details of why the math works, but he does have appendixes and sources of where he gathers all of his sources for each section of statistics he goes over.
I really liked how Wheelan explained how different groups can mess with data depending on how it is interpreted or how people can skew the methodology to produce certain results. He has a great explanation of how people lie with statistics or distort confidence in results.
on March 20, 2017
This is a very readable and entertaining statistics book. Yes really, it is fun. I took a statistics class in graduate school, where I learned all the formulas and calculations. Honestly, I learned more from this book because it tells you when and how to apply your new knowledge. It's funny, and is filled with practical examples. I'm still not totally convinced about his Let's Make a Deal statistics though. LOL You don't have to know any math to read this book. This author leads the calculations to computer programs. I wish my grad school professor had done the same.
on May 30, 2017
Maybe I know too much about stats to appreciate this book. I have a graduate degree and have taken at least 5 stats courses. I thought the book might be interesting for a heady casual read.
There were occationally interesting examples, but the organization seemed very strange. I hated how he kept mentioning things he was going to talk about in a later chapter. Litterally every chapter has hints to later material that is out of place either ahead or behind.
I think it would have been better if it were made of many short chapters instead of fewer longer chapters. The chapters seemed drawn out, a mix of poorly related topics, and preventable redundancies.
It is easy to read. It is not complicated material. It just isn't very good.
There were occationally interesting examples, but the organization seemed very strange. I hated how he kept mentioning things he was going to talk about in a later chapter. Litterally every chapter has hints to later material that is out of place either ahead or behind.
I think it would have been better if it were made of many short chapters instead of fewer longer chapters. The chapters seemed drawn out, a mix of poorly related topics, and preventable redundancies.
It is easy to read. It is not complicated material. It just isn't very good.
on May 29, 2017
This book not only gives great insight into the realm of statistics, but delivers it in a fashion that is very easy to read. Wheelan explains the basics concepts in statistics, from probability to regression, with such simplicity. Though I personally already had a large amount of knowledge in the field of statistics prior to reading this book, i found myself being able to understand the basics with Wheelans examples far more easier than being previously taught these came concepts in the classroom. While a book on statistics may seem daunting and quite boring, Wheelan does a fantastic job of keeping the reader engaged with humor and real life examples of how statistics applies to the world we live in today. Whether you are reading this to grab a basic foundation of statistics or are brushing up on the concepts, this book is a must read!
on June 15, 2016
I read this book for a research methods class and I honestly couldn't have asked for a better explanation of statistics. The author, Charles Wheelan, explains in the introduction that he struggled with learning statistics and other economic-related subjects because he couldn't see how it applied to the real world so he fills the book with examples that we can actually relate to in our everyday lives. For example, one of the chapter subtitles is "How does Netflix know what movies I like?" I'm pretty sure every Netflix subscriber has wondered that at least once while browsing through their recommendations. In addition, Wheeler is actually an amusing writer and I found myself chuckling more than once while reading this.
I was very surprised to have found the book as interesting as I did. Math was probably my least favorite subject in school and, in general, I find the entire subject a bit boring. However, this book really made me interested in how statistics play a role in our everyday lives. I highly recommend it to absolutely everyone. You don't need to be taking a class or work with statistics to find this book interesting.
I was very surprised to have found the book as interesting as I did. Math was probably my least favorite subject in school and, in general, I find the entire subject a bit boring. However, this book really made me interested in how statistics play a role in our everyday lives. I highly recommend it to absolutely everyone. You don't need to be taking a class or work with statistics to find this book interesting.
VINE VOICEon March 22, 2014
In my role as a Six Sigma trainer, I spend a lot of time teaching people about statistics, and I'm always looking for more approachable ways to describe the methods and techniques we're talking about. Dr. Wheelan does a spectacular job of providing real world, fact based (well, mostly - lots of buses being nabbed in this volume), examples to explain how statistics work. I can't recommend it enough for the layman interested in the concept or especially the student needing to learn about the tools.
I'll be providing his book to all my students from now on - there's so much useful information, and he explains the concepts of normality, the central limit theorem, regression, and hypothesis testing in a way that anyone should be able to understand after one read through.
My only minor quibble is the reliance on U.S. based examples - lots of talk of football and such here. That's remarkably minor and only stands out as I have students from around the world who may be slightly confused until I can explain what a linebacker is.
I recommend this book in the highest and will certainly keep a copy for my children to read as they get a bit older.
I'll be providing his book to all my students from now on - there's so much useful information, and he explains the concepts of normality, the central limit theorem, regression, and hypothesis testing in a way that anyone should be able to understand after one read through.
My only minor quibble is the reliance on U.S. based examples - lots of talk of football and such here. That's remarkably minor and only stands out as I have students from around the world who may be slightly confused until I can explain what a linebacker is.
I recommend this book in the highest and will certainly keep a copy for my children to read as they get a bit older.
on July 27, 2016
I am teaching a stat course later on this year. I bought this book - after reviewing it in the advertisement - as a "non-technical" approach to the subject and have been very pleased. The author puts some humor in the presentation, and make connections using some elementary math to present an interesting book to read that puts a "face" on the subject. Several reviews have not been kind to the author's presentation, but it really works for me. I haven't finished it yet (I am reading it slow and reflecting0 but I am enjoying his presentation. He doesn't stress you out with "academic prose" but rather gives you something you (I) am familiar with and brings a smile (I can feel the smile). When I finish the book, I will give a more complete review, but I can tell you now that if the text continues enlightening me as it has, I will probably consider purchasing his text on "naked economics"!
on March 2, 2017
If you want a book that mixes math and humor, this is perfect. It draws on real-world examples and analogies to demonstrate pretty complex subjects and to make them very easy to understand. I had to get this as a textbook for a graduate statistics course, and I could actually see myself reading this for leisure because it's pretty entertaining as well. Great read, definitely recommend for anyone struggling to understand statistics
on June 2, 2016
I have been reading this book and I like it so far, but there are 2 things that bothers me a lot:
1) A lot of sport metaphors which is fine in general, but the problem is they are based on american football and baseball terms. That is absolutely OK for a reader born in USA, but let me say that a lot of people across the ocean do not know much about it! I am sure that there are more broadly respected sports, i.e. soccer. Just a little bit more of case about international readers...
2) When it comes down to inference, I found that the following statement in chapter 9:
====
You may recall from the last chapter that we can create a standard error for each of our samples: S/sqrt(N) where S is the standard deviation of the sample and N is the number of observations.
====
is very confusing because chapter 8 says:
====
If you’ve followed the logic this far, then the formula for the standard error follows naturally:
SE = S/sqrt(N) where S is the standard deviation of the population from which the sample is drawn, and N is the size of the sample.
====
How did we replace the standard deviation of the *population* with the standard deviation of the *sample* so easily? I didn't not find any explanation of that..I guess that it's because the sample's standard deviation is "similar" to the population it was drawn from, but does is it enough to change the formula so drastically?
1) A lot of sport metaphors which is fine in general, but the problem is they are based on american football and baseball terms. That is absolutely OK for a reader born in USA, but let me say that a lot of people across the ocean do not know much about it! I am sure that there are more broadly respected sports, i.e. soccer. Just a little bit more of case about international readers...
2) When it comes down to inference, I found that the following statement in chapter 9:
====
You may recall from the last chapter that we can create a standard error for each of our samples: S/sqrt(N) where S is the standard deviation of the sample and N is the number of observations.
====
is very confusing because chapter 8 says:
====
If you’ve followed the logic this far, then the formula for the standard error follows naturally:
SE = S/sqrt(N) where S is the standard deviation of the population from which the sample is drawn, and N is the size of the sample.
====
How did we replace the standard deviation of the *population* with the standard deviation of the *sample* so easily? I didn't not find any explanation of that..I guess that it's because the sample's standard deviation is "similar" to the population it was drawn from, but does is it enough to change the formula so drastically?
