laptak2003/AmazonDataScience huggingface dataset:
I'm getting my feet wet with Python and Python for Data Analysis. This is a great book for beginners to advance users who want to explore and learn Data analysis using Python. In addition to using Python for other purposes.
Good, relevant, practical content.Bad book quality. Pages started coming loose after a few days. I was expecting better for a $60 book that is supposed to be used as reference (as opposed to a cheap paperback novel you only read once).
So far, this book has been an inspiring reading. It contains a huge number of data cleansing, transformation, analysis & etc. code snippets. The code is very clean and - for the most part - self-explaining (at least,  for a seasoned software developer). The book step by step displays the motivations behind the design and functionality of center-piece Python modules - and you would not expect anything less from the original designer of Pandas. I feel this wonderful book being a natural extension of ageless Practical CS classics by Niklaus Wirth, Kernighan-Ritchie, and B. Stroustrup for Data Science Age.
I needed a jump start on python use in data processing for a new job I was starting. I come from the Java world, so major transition. This got me up to speed and I hit the ground running.
Iâ€™ve read this probably 3 times start to finish and I refer to it whenever I get stuck coding something.This book gives you the foundation for almost anything youâ€™d do in Python. Most of your time is spent cleaning data, thatâ€™s what pandas was built for. I recommend this to any beginner.Some reviewers mention it isnâ€™t well written...itâ€™s a book on code, how exciting were you hoping it to be?
Great book, though a bit dry and slow. My only complaint is that I would have preferred more examples, but I don't think that was the aim of this book, and I think it accomplished it's goal of being a good general resource for people beginning their career/learning with Python and data manipulation. Not comprehensive by any means, but thorough enough for any beginner/intermediate python programmer.
Really good read for striving Python developers and data scientists. Wes McKinney, being the original creator of Pandas, surely has a lot of knowledge to share. I have several Python related books, and this is the one I go back to most often.
It covers the basic syntax quite well.  After reading this book, I could look at code on the web, understand it and modify it for my own use.
I have read most of the book. Some topics are not well explained. Overall I am happy with this book.
Book covers IPython, NumPy, and Pandas; and includes very helpful appendices. Buy it!
Iâ€™m relatively new to python and data analysis tools like Pandas. Started a month ago and this book makes several things clear â€” wish I had had it a few weeks ago.Weâ€™ll written and generally doesnâ€™t get into minutiae. Very useful.
My kindle oasis keeps crashing on the same section.had to skip that chapter . great book for learning pandas, would deserve 4 stars if not for the crashes
Nvidia compatible GPU Python for data analysis explanation in examples. Overall is broadly discusses of Data analysis.
Great book for someone familiar with other programming language and getting into Python.  I was able to rewrite a program I had done in R using info from this book.
This is the book you want.  This is every bit as detailed as I hoped it would be with a great introduction, great examples, and great coverage of fundamental, basic, and advanced functionality.  If you want to dive deeper into Pandas and data analysis, this is for you.
A very general guide to start data analysis using Python.
I ordered this book and pages 81 through 104 were missing. Check your copies when you receive them..
Excellent.  Organization perfect.  I could dive in precisely where the diving needed to be done.  I got exactly the backstory on these technologies, very efficiently.
Wish I would've bought this before trying to learn this myself. It would've saved me a lot of time.
It's been 2 months that I bought this book. I like the way author - Wes McKinney (developer of pandas) has written the book and given its perspective. This book is a great start for using python as a programming language for data analysis.
Excellent book, helps to understand better the logic of Pandas.
As advertised - great for data analysis
The material covererage is pretty good, but the book itself is more of a summarized reference to technologies rather than something focused on solving real problems.
Great read from one of the original developers of pandas.
Pandas explained very well by its original developer
Pandas is an amazing software. I bought this book to support Wes. Thank you for Pandas!
Such a good refresh. If you work with data, this belongs on your bookshelf.
Reads like a manual. Difficult to learn unless youâ€™re looking for something specific.
My introduction to Python was primarily through this book. I keep coming back to it for a quick reference. I'm not seasoned Python pro, but I would recommend this to anyone.
Kindle format it's ok.  Don't have any issue so far.
Mc Kinney books are the best
This book was required by my data visualization class. I wasn't able to find a cheap used version of this book so I ended up reading the temporary PDF my school had at the library. Let's just say this... This book is SO good and SO useful, that I ended up shelling out money to buy it AFTER I've read the book already and AFTER the class was over. I think it's just such a handy guide for anyone to have. I'm sick of crappy presentations overloaded with meaningless data that don't convey any useful information. If you are too, I highly recommend this book.
Lots of great information about Data Science for Beginners, If you want to know more about becoming. I very suggest that you try this Data Analysis, Machine Learning. for Beginners. I found that this book is well written and easy to understand.
Read the sample.  Buy something elsd.
I found this a difficult read with poor grammar and horrendous readability along with blatant errors which are going to confuse to anyone new. For example the text says "In Python there are four numerical values supported:" and then lists  Int  Float and ComplexI don't know about you but I see three numerical *types* there, not four.I *believe* the author is trying to say there are four numerical *types* as there are clearly many more than four numerical *values*, e.g: 0, 1, 2, 3.2, 4.75 ... There are 5 numerical values right there. Python only supports four? And if the author meant numerical types, he only listed three. As far as I understand reality three != four. I encountered either readabilty factual errors on nearly every page if not in every paragraph.As far as readability, take the following quote discussing the naming of variables in chapter 3: "However, the technique of naming variables remains illegible as different programmers decide on how they are going to create their kind of names." Can any of you make sense of that? In some ways it reads like something that was translated from a different language into English without any translation or editorial review. No competent editor would let something like that go to press, and this was just one of the many such issues in the first three chapters.
Excellent book for data science introduction, it was a good recap for me on most of the models used in machine learning.
Excellent book, well written and great examples given to help you understand the applications of each method. Would recommend to anyone with an interest in data science and machine learning.
It is a superb scholarly voyage through data science. A segment calculation of security and profound quality GDPR and inclination spread. By and large, a great general job. From this book you can get numerous things about information science. Amateurs additionally can take numerous aides from this book. This book likewise helps the peruser with Python learning. An exceptionally supportive book for software engineers.
This book is definitely for beginners as the concepts are step-by-step using examples, exercises and mini-projects. However, the author does well-explaining thoughts, and it is very in-depth. If you are looking for a career in data science and something intermediate to advanced to enhance your deep learning and data science aptitude, this is an excellent book to go with.
I'm delighted with this book. It includes a convenient approach to Data Science for Beginners topic. Not only details about all algorithms but also discusses various critical steps in preparing the data sets for deep learning work, evaluating the models using Tensor Flow and Keras. Can't wait to attempt the Hands-on project at the end of the book.
Recently bought this book. But found many figures in the book are just blank. Will try to see if Amazon can send me a new copy
The author, Wes McKinney, succinctly sets forth the contents and goals of his book: "This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. My goal is to offer a guide to the parts of the Python programming language and its data-oriented library ecosystem and tools that will equip you to become an effective data analyst. While 'data analysis' is in the title of the book, the focus is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis." It is a massive revision of the 1st Edition â€“ practically a rewrite. The emphasis is on Python 3.6, rather than 2.7 in the earlier edition.s The book presumes operating knowledge of Python and some of its libraries. The author describes his effort as â€œan introductory text in working with [primarily structured] data in Pythonâ€. That is, data that could be expressed in a spreadsheet (though the authorâ€™s description is substantially broader than my summary). The treatment is detailed, but well-written and well-illustrated. The level of detail can be fairly described as staggering. While the book does not promise to teach you data analysis itself â€“ which is an almost limitless subject â€“ but rather about the tools with which you can analyze data. Sample datasets are available for download to perform the exercises. If youâ€™re new to data analysis, I would suggest at least skimming the entire book to get an overview of what the libraries can do and then honing in on specific libraries. Overall, I think this is the go-to resource for learning how to use Pythonâ€™s data wrangling libraries in conjunction with Python.Jerry
Paperback version tends to fall apart, making challenging to use the book.
I found this book to be a good introduction to data analysis using Python. I do not think it is a useful introduction to data analysis in general as programming is just one aspect of data analysis.This book will fade quickly as it refers to the current state of development of PANDAS, and other tools in Python.I was introduced to data analysis through R. And I have programmed in Python. I learned about both from MOOCs.At my current skill level, I can develop fairly complex models in R using about 20-30 lines of code. I would struggle to do the same in Python even with the help of this book. The Python data analysis software does not appear to be as developed and integrated as the R tools.
I don't think I'd use this as an introduction to the Python programming language.  For that, personally, I had gotten this book:Â Python Crash Course: A Hands-On, Project-Based Introduction to Programming.  This doesn't mean that others couldn't use this book for such purposes, just that personally I think the Python Crash Course book was better for introductory purposes.Once you get past the introductory point and you need to get into data analysis, this book is just what the doctor ordered, or at least it offers plenty of useful information and insight into tools that you would use for your own data analysis.I'm lucky enough to be working with the second edition of this book which means that the author has taken the opportunity to update this book in multiple places compared to the original edition.  This gives us all the benefit of the lessons learned and feedback that had been provided to the author and also allows us all to get insight on the latest libraries and tools that were known and available when this book was updated.
The writing seems to indicate readers should already be familiar with some variant of C or other coding language. In any case, the book is not well written for novices in technology. I'm putting two stars here because everything written is accurate and worth knowing, but the material is not well introduced or coherently presented, which leads to confusion and exasperation. On top of that, there is almost no explanation for why the information is relevant or interesting, leaving the reader to figure it out (this book should have mini-examples at the end of every chapters). The information is there, but there is definitely a better book out there for learning data analysis with Python.
I love the book it is very comprehensive.  I actually like the simple examples with random numbers as it makes it easy to replicate the mechanics of the examples quickly and easily.Unfortunately I purchased this for my new Kindle Paperwhite and it could cause my Kindle to completely lock up.  I initially thought it was the Kindle itself so after three tries working through this issue with Amazon support and replacing the Kindle, Amazon determined it is a problem with this eBook which they refunded.  This was very disappointing as accumulated notes and highlights on the Kindle.
This is a nice introduction to the Data Science modules in Python. It's quite thin so it's not a Python tutorial and you are expected to have some familiarity with programming. I found the book well written and easy to follow. Much of the books source code is available online, so you won't have to spend too much time typing out programs. Inevitably the material is a little out of date, bu I found the book well organized and easy to follow.
Python for Data Analysis is a comprehensive and well organized book.  But as with many O'Reilly publications, there is an underlying assumption of knowledge about programming concepts.As an introduction to a new language for someone who has programming experience with other languages, and is familiar with data analysis in general - I would recommend this book enthusiastically. It can be used as a sequential guide to learning Python or as reference material. It uses easy to understand, with concise examples to demonstrate every topic discussed.For a person who wants to learn Python as their first programming experience, this is not the book for you. Python is often described as the easiest first language to learn and that may be true. But in this book, concepts such as data types, and packages, and vocabulary such as 'interpreted languages' are assumed to be common knowledge.
I bought this book for understanding the term 'Data Science' and its concept. This book provides a perfect and complete understanding of the topic. Must read for someone who is going into the field of Data Science or for someone who wants to explore the area and know what it consists. Best overview of the topic that I have read.
The book is about Data Analysis.Reading this book you will get knowledge about various aspects involved in data mining and how to exactly set up the appropriate environment for your machine learning .I have also learned Utilization and Procedure of Data Science.The book is so informative and helpful.Highly recommend.
Programming in Python is definitely not childâ€™s play, but reading this book with instill you with enough skill to write advanced data science programs. It covers the basic principles of the modules, libraries, and toolkits necessary for data science and shows you how to master and use them to their maximum capacity.
The book is about Data Analysis.Reading this book you will get information about different angles engaged with information mining and how to precisely set up the proper condition for your AI .I have additionally learned Utilizations and Procedure of Data Science.The book is so instructive and helpful.Highly prescribe.
Excessively straightforward anyway it gives us an incredible comprehension. This book makes me significantly make a couple of data examinations successfully.I enjoyed this book. It is a quick read and gives a good understanding of the importance of the need for a data science approach to your business.
This book is really well written and worth reading it. The content is explained good and with a flow. This book is for any one who wants general understanding of the data science and it's related fields. If you are new in this field this book will be a good read for deciding your career.
A part of critical instruction of Step by Step Your Information Science. This is often a extraordinary book for learning Data Science for Apprentices. It is undoubtedly an awfully enlightening book. it was exceptionally supportive but truly critical. best book i perused so distant.
An inspiring quick read to help break free of the tyranny of Excel's default chart styles. The book is packed with practical advice aimed at making your charts and accompanying stories more visually pleasing and impactful.
This is a good book to understand the map of data science before jumping into the field and learn. For me it gives a map where to go and what skills are required to learn, It's a must read for anyone intereste
The mathematical foundations are very well tackled and the code is well commented and explained. It will be much better if the codes were written in Python but most of them can be easily implemented in Python.
I would prescribe this to anybody. Each individual on earth should understand this! In the wake of perusing this Data Science book I am really encountering! This book has helped me incredibly.
A fantastic book for Layman in Data Science. if you are starting in the industry like me, take this book now. The best book on Data Science and coding I have yet seen at this price... Thanks
This book is for any one who wants general understanding of the data science and it's related fields. If you are new in this field this book will be a good read for deciding your career.
Their noteworthy scientific and specialized ability. It is an awesome presentation that is extremely wealthy in instinct and overly commonsense. This book contains something shrouded mystery equations that are enlightening for learning python learning. Truly, it fates to occur and we need to plan to acknowledge it.
This book is excellently written. Following this I learned a lot about this topic. I recommend this book. Thanks author for writing a good book.
Grateful to come across this book for several reasons. 1) My path to better data visuals was to save PowerPoint decks from other internal teams who had great design and message communication, I didnâ€™t understand what those good design elements were until this book came along.
This book helps. It worth the price. If you have some basic Data Science for Beginners knowledge and are seeking how to implement RNN and CNN under different real-life conditions, this book is precisely the one you want and don't hesitate to buy it.
This book is exceptionally enlightening and accommodating. All the tips of this book are extremely educational. I am particularly glad to have this book. I might want to express appreciation to the writer of this book. He worked superbly. Suggested!
The book is about Data Analysis.Reading this book you will get data about various points connected with data mining and how to unequivocally set up the best possible condition for your AI .I have also learned Utilizations and Procedure of Data Science.The book is so enlightening and helpful.Highly recommend.
The book is rich with screenshots and step-by-step explanations on how to apply data analysis techniques. Overall this is an excellent guide. This is an essential guide for everyone. I'm going to best rating this good content book. Thankful!
A lot of important instruction of Step by Step Your Data Science. This is a great book for learning Data Science for Beginners. It is indeed a very informative book. it was very helpful but really important. best book i read so far.
The content is explained good and with a flow. This book is for any one who wants general understanding of the data science and it's related fields. If you are new in this field this book will be a good read for deciding your career.
it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results.
I found this highly valuable because you are able to actually work on real data sets. This is also a quick way to learn industry recognized tools and mathematical concepts that are actually being used by data scientist.
Brilliant book for a flat out learner who needs to comprehend the terms and get acquainted with the subject. Would prescribe to all beginner .
the writer has made an amazing try to give an explanation for complex theories in a simplified manner through giving examples applications.
This is a tremendous resource for anyone looking for a refresher or a basic introduction to machine learning.
This book contains something shrouded mystery equations that are enlightening for learning python learning.
Great book, highly recommend. This is a great book. Itâ€™s been extremely helpful and informative.
I found out much new information about Data. I will recommend it with pleasure.
Very good book and nice intrroduction to data science concepts. Recommended
Very good book and nice introduction to data science concepts. Recommended
I liked how it gave a good overall view in what data science involves.
This book is phenomenal. it's an ideal blend of elevated level clarification and specialized subtleties.
This is an excellent book for anyone interested in data science
Great and interesting book with useful informations.
It was exceptionally simple to peruse and comprehend. I welcome the data about the substance. Much appreciated, writer for this incredible book. I energetically suggested this book.
I get numerous accommodating data from this book of Data Science. So I think this book best for Beginners individuals. So it ideal book for Beginners.
amazing book
This book gave a mind-boggling review to me as I headed into a Data Science work following a long time of working as a Software Engineer. I didn't require an overview of the certified math behind each model sort, so it was impeccable finding a book that would assist me with remembering the procedures and use cases without requiring a few pages of assessing the verifiable underpinnings. This book is a stunning introduction for data science for embellishment on how one would consider data. This book gave a diagram of the fundamental considerations and thoughts regarding data science. This book is practical and strong. Overall this is an excellent guide. This is an essential guide for everyone. I'm going to best rating this good content book. Thankful!
This book is awesome to read and I think this book is the best book of this topic, and I really appreciate this book.This book gave me a lot of information. The book is very organized. I am very much pleased to read this book.The start of the book was wonderful. The book is simple and easy to read and understand.I really liked this book.I would highly be recommended to read this book, for everyone.
Great introduction for beginners. The author did a good job in using layman terms to explain how each algorithm works and provide the audience a general understanding of the big picture
The chapters are neatly organized, so you can go back and find content easily. I love this book and want to recommend to anyone.
I was interested to know about python programming and I bought this book from amazon kindle store. After reading this book I learned many kinds of data science programming and python programming too. Thanks to the author.
This Book was full of informative information. It was very easy to read and understand.I appreciate the information about the content.Thanks author for this great book.I highly recommended this book.
This book is so informative. Has clear knowledge about data science. All of easy to understand. Really this book is so helpful. I would highly recommended to all for this book.
Data science for Beginners book is very helpful book for learn python. youâ€™ll discover everything you need to know to get started. Don't miss to read.
There is a lot of information in a very nice guide book that has helped my personal life a lot. Thank you for a great article.
This book contains much helpful things about Data Science. I will recommend it.
This book gave an amazing assessment to me as I headed into a Data Science business following a long time of working as a Software Engineer. I didn't require an examination of the veritable math behind each model sort, so it was impeccable finding a book that would assist me with reviewing the strategies and use cases without requiring two or three pages of assessing the accurate underpinnings. I didn't require a review of the declared math behind each model sort, so it was impeccable finding a book that would help me with checking on the structures and use cases without requiring a couple of pages of surveying the certified underpinnings.
This book is great. youâ€™re a complete beginner or a programmer looking to improve his skillset, Data Science for Beginners is your all-in-one solution to mastering the world of Python and Data Science. Highly recommended this book.
This book gave a diagram of the fundamental considerations and thoughts regarding data science. This book is practical and strong.
Great book for beginners. This book has been super helpful for me. I read the whole book and itâ€™s really amazing.
The ebook offered here is painful to read, it does not work well on the amazon app, and you cannot download the book to read within another application.  It constantly flips pages while you are trying to read and a lot of the functionality that makes books easier to read on the amazon app does not work for this book.  Also, Alexa cannot read this book.
Very poor quality, I bought pearson hoping to find Something better. But the papel quality is terrible.
Exactly what I asked for!
Great Amazon rental service but required book was aweful. Lots of YouTube to really learn the materials .
This book really needed an editor. I am only 18 pages in but I have come across four acronyms  that were never spelled out so the reader is left trying to discern what the acronym stands for. Like PM on pg 5, DSS on pg 13, ESs on page 13. If you are new to the topic itâ€™s annoying and just plain lazy to not use proper writing etiquette. One of the first sentences you read in the preface list companies redundantly. I have to read this for a class and Iâ€™m not excited about reading such a poorly written text.
Ordered as part of my Business Analytics course in my Masters. This book is detailed and gives real life examples from a managerial perspective. Helped me understand Project Management concepts better and was really helpful in getting good scores.Pros: Detailed, informative.Cons: ExpensiveThis book is really good if you are looking to understand Business Analytics from Managerial perspective
I love this book because it has all major concepts which are explained very clearly from basics. I can recommend this book for the people who are looking to start their career in Business Intelligence field. The book is printed very good and i didn't get bored or stressed when studying this book.
Great book but dont buy/rent for kindle if you dont have a kindle. Not compatible with mac kindle, waste of money!
Fast shipping great product!
Great price for college book!
Great source for my courses.
As advertised and fast delivery
Great book bought it for class and now realize it is better to purchase school book on ebook instead of hard copy.
I received this as gift to help me with a Stat class I was taking.  It does well explaining basic statistical concepts in plain English with a startling lack of numbers in the examples.  Where a traditional textbook fails in explaining it's material and it's relevance, this book excels.  I had hoped it would reconcile my difficulties understanding regressional analysis but that did not come to fruition.  The author has some humor that he applies sparingly and is welcomed and the examples make the knowledge gained seem relevant.  That aside, don't expect to  learn statistics by reading this alone.  There is little re-read value to it as it presents itself in a storytelling manner which you wouldn't need to hear again.  Do not let that dissuade your purchase as this does what most educational texts fails to do,  which is mak  you care about the subject and see its prevalence in society.
I'm tardy on submitting a review on this as I read it awhile ago.I purchased this book as a step on my journey to build up certain skill sets and knowledge in a field that I wish to break into and combine with my current expertise.  This book was a great read on statistics.  In my opinion, the author did a fantastic job explaining concepts and how the associated formulas worked in a slightly technical way, but mostly leading into explanations in layman' terms.  In particular, the examples he used to further explain the material really brought everything together and made it easy to understand and retain.  They weren't just the typical generic and sterile situational type of examples, rather something that the vast majority of readers can relate to or, at least, visualize more simply.  Something that was more interesting to get the reader vested in the material.Thanks to the author for taking the time to write this.  I have your other books on my reading list now.
I found naked statistics to be a very interesting read and while I did learn a lot, I didnâ€™t get the formulas to address the specific applications I was seeking. I would like a simple table of formulas and their applicable uses that I could program into a spreadsheet to play around with. The stories, while educational and relevant, were also distracting to my purpose in reading the book in the first place. I would, however, highly recommend this book for students and people with less life and business experience than a 76 year old.
The description "easy read" should not go with a book that explains statistics. Unbelievably, this book does that. I have read books and taken graduate level courses in an effort to learn statistics to transition from medical care to medical research. Although this book would be far from replacing those, it has taken much of the pain and obtuse explanations away and supplanted them with easy to understand lingo and real world application.  I understand concepts much better after reading this book.  Heck, I may try and learn economics by reading the same authors book on that subject ( which I have no clue about one, but will soon!)
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!
This book attempted to explain statistics in an approachable way. However, there were so many trivial examples he never actually taught you any statistics. Also, his examples were biased towards a particular perspective which were very distracting.
Goes on a lot of pointless opinionated asides. Too many words, not enough numbers. It's not really about statistics. Spends a lot of time talking about polling. 2016 was the death of polling.
This book is very well written and ties in the main concepts of statistical analysis in ways that keep the reader engaged and interested. It isn't a simple regurgitation of facts and statistics, but instead takes a humorous approach at showing the reader how he/she already uses statistics in many aspects of life and outlines why it can be so useful to have a solid knowledge in this subject area. Charles Wheelan does a great job presenting a topic that is typically somewhat dry and difficult in a way that will generate frequent laughs followed by moments of realization as the principles outlined become suddenly clear.
Disclosure: I'm a social science researcher and statistician. Back in the day, I thought it would be fun to use Huff's 1954 "How to lie with statistics" in an intro stat course. Then now departed good friend Gerald Bracey wrote "Reading educational research: How to avoid getting statistically snookered," and that became the new standard for my wish to use a book in an intro social science/educational research course. Now along comes Wheelan's book. It is in my opinion at the very least a great alternative to Bracey's book, and if I were teaching an intro statistics (as opposed to introductory research methods) course - including to undergraduates but these days likely for grad students too - I'd use Wheelan as one of the texts.We (meaning college professors) typically do a great job of scaring the daylights out of students about the really very logical statistical concepts. What we need to do is to a great job of helping people get past the fear so they can use the tools in every day life -- and keep from getting snookered. Now there's a way for everyone to get past the fear: get Wheelan's book.
This wouldâ€™ve been great if it didnâ€™t, as my professor pointed out, constantly make weird and insulting body weight references. He talks a lot about fat people. Iâ€™m a petite young woman as is my professor which Iâ€™m specifying because it was still immediately off putting to people of lower weights. So many other ways to make your point dude. Lots of other metaphors. Or if youâ€™re going to poke fun at fat people...be funny. Not a dick.
I bought this book because I love working database, Excel and numbers. It was really hard for me to get 100 pages in. I gave up after that. Like stats textbook only with slightly more interesting models.
Although this book is a nod to How to lie with statistics, if I were to compare it, this book is very similar in approach to NDT's Astrophysics for people in a hurry.Charles Wheelan uses easy to relate topics to demonstrate how statistics are used to break down the information, validate results, and draw conclusions. All the while stressing how statistics can be misleading and downright dangerous if used incorrectly.He did the best he could without being overly technical but the regression chapter suffered a bit due to oversimplification. I still found it extremely worthwhile.
I'm currently taking Masters Level econometrics classes.  While I've been memorizing the formulas and how tos, I struggled putting the pieces together on the what the story was telling until I read this book.  (I think if you show up to a masters level class, they assume you already know the basics!)This book filled in a lot of the blanks for me.  My undergrad was in Accounting (decades ago!) and I'm not sure how, but I hopped through college avoiding statistics so there were some gaps that needed to be filled.  I LOVED the approach of the book and highly recommend it to anyone starting out in statistics to provide a great lay of the land.  I'm passing it on to my 18 yo who wants to go into stats in college.  It's a great framework.
I got naked statistics because I was curious why it was one of the top rated books for stats. The ideas and theories were described in a very simplistic way to understand. However, the book provides very basic and generic explanations. If you got this book to learn how to conduct stats or evaluate data - it won't help. There is very little information with regards to the techniques of data evaluation or it gives the excuse of "this information can be found in a more advance books".Overall the book is good for people who look for just skim knowledge in statistics, but I wouldn't recommend it if you want to use it to pass your stat class.
Charles Wheelan really addresses a disparity every student of math has faced at one time or another, and that is "why in the world do I need to know this?" This question has gone though every bored child's mind while Mrs.xxxxx goes on and on about derivatives, and factorials and parabolas, never putting into context the value or application of the subject matter in the real world, luckily for us we have Mr. Wheelan to fill in those gaps for us. In this day and age statistics are a continually more important facet of life whether in be in the financial markets, or even Netflix recommendations, the human race has become the ultimate data pool for intelligent people to solve radical problems, and what the author does in this book is provide the context of how stats can expand our prospective.
Wheelan attempts to make statistics understandable and relevant to the average person who can't be bothered with statistics or math in general. He provides examples of how each concept in statistics are used in various aspects of our daily lives from casino probabilities to how the data gathered can be misused or misinterpreted to present a claim to the uninformed. There are some dry humor throughout the book when chapters are seemingly boring that make it seem like reading a textbook. There are also statistical terminologies and concepts that may be difficult to understand and I believe this is why the book is a supplementary material for some statistics classes. The book is good in helping understand general statistics and why it is used in particular areas where the data is needed.
I teach (and do) statistics for a living and this just became one of my favorite statistics books.  Instead of being a technically rigorous math book, this is some of the best technical writing I have ever read.  All of the core topics covered in introductory statistics texts are presented here.  In the usual stat text concepts are explained with formulas and then examples are given.  This book takes the opposite tack. Every topic is beautifully framed with entertaining or laugh out loud examples and the few formulas are relegated to an occasional appendix.  The examples are so well chosen that the humor does not feel forced or contrived.  Rather they just make it easier to stick with the book.  At times the author is a bit long winded (especially if you are used to terse scientific writing) but overall the pace is good.The reader of this will walk away knowing the "why" of statistics and will likely be tempted to learn the "how" using more technical books.
I had to read this book for my degree, and though it was an easy read overall,there was one thing I very much disliked about it.The author spoke about autism a lot, and as an autistic person, that obviously piqued my interest, but the way they spoke about it was wrong.They claimed that scientists don't know what causes autism (even though most autistic people and scientists agree that it's all genetics), they claimed that children who are autistic have larger brains than "normal" children (which is wrong in so many ways), they claimed that there's a "rising autism rate" (which isn't true, because more people are being diagnosed because now psychologists and doctors know what to look for in diagnosis someone), and that there's an "autism epidemic".That makes me sick.Autistic people have existed since the beginning of humanity.Autistic people were thrown in mental hospitals and hidden from the world for years because people didn't know how to treat them.There is no "autism epidemic". There is just a rise in more people being diagnosed because we know now what it means to be autistic.It's people like this author who make our lives more difficult to live.It's people like this author who perpetuate stereotypes that there's something wrong with us and that we need to be cured, even though there is no cure for something in our genetics.So thank you for that.
I heard about Naked Statistics, from Charles Wheelan, a few months ago. It was mentioned on a LinkedIn group as an excellent book. So I urged to bought itâ€¦and I wasnâ€™t disappointed. Naked Statistics is a journey in the world of statistics applied to everyday challenges.The book is very readable and is often funny. Wheelan introduces some concepts through a new TV show: CSI Regression Analysis. Each statistical concept is presented through several examples. Topics covered range from descriptive statistics to correlation/causation and false positive vs. false negative, among others. The Monty Hall problem is also very well explained.The book goes on with more advanced topics such as randomized experiments. The author explains several challenges related to such methods and how to surpass them. Wheelan also discusses hypothesis tests and issues related to confidence level and p-value. The book is an homage to How to Lie with Statistics and it is complementary to it. Naked Statistics is a delicious surprise that will delight anybody interested in statistics and analytics.
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 have taken enough courses in statistics to understnad and apply the math. However, like many, I studied with the goal of passing exams. Many of the exercises done in class or as assignments were interesting enough ( measuring effects of drug-trials, applying the binomial method in different situations, analysing if a factory part should be rejected, etc. ) but this book offers a far wider and more conceptually-appealing number of real-life examples to allow the reader better grasp the meaning and application of statistics in different situations. I particulary enjoyed his emphasis on the importance of randomness in statistical studies, and his description of the application of the NY Times/CBS poll for gauging voter preferences. He also explains well how researchers have to take great care in ensuring they apply statistical tools correctly so as to avoid mistaken conclusions.
I was familiar with the concepts in the book but I read it as a refresher course. I found it easy to follow and written in an interesting style. The book maintained my interest because the author sprinkles it with the techniques and results from real studies that are interesting in their own right.  Almost anyone will be able to understand the explanations because of the thought experiments and some made up stories that illustrate the concepts.  I highly recommend it for both the statistics and the interesting and important study results that it contains.
I just finished reading Naked Statistics by Charles Wheelan.  This book met all my expectations.  It provides an excellent description of the field of statistics.  Although statistics is just a little over 100 years old, it has obviously become the way that we describe the world and at least an intuitive understanding of these concepts is important.  I would strongly recommend this group for two groups of people.  The first group would be people like myself who are interested in the general understanding of statistics and have no desire whatsoever to do any of the manipulations that are necessary if you want to be a real statistician.Mr. Wheelan did an excellent job in describing a number of things that are of great interest to me as a physician.  Those include his excellent discussion of type 1 and type 2 errors, the miracle of regression analysis and how powerful this can be, particularly in medical studies.  Another area is that he described the counter intuitive situation with Monty Hall on Let's Make a Deal about as well as anyone has.  So many times when I read about this, I understand it for an hour or so, but then my old way of thinking seems to slip back in.  When that happens, I am going to go back and review his chapter.The second group of people that I would recommend this for are young people that are starting out in a career in medicine or any other area and especially those that are taking their first statistics class. I think a great problem with education, especially in medical school and postgraduate medical school training, is that the students jump into the middle of statistics without understanding their purpose or their basic concepts and rarely come away with anything more than a mechanical understanding of the subject.I can highly recommend this book for any of the two groups that I have just mentioned.  I would give it a 5-star rating.  Because of this experience, I have just started to read Professor Wheelan's previous book, Naked Economics.
This book was recommended to me by my MBA professor, and while the book was easy at the beginning, it turned very complicated since it used sports that I donâ€™t understand at all to explain statistics concepts. The book used baseball and American football, which I do not know or understand since I am from South American, not from the US, and those sports are not part of the culture where I came from. I think the book could be better if they use examples that can be applied around the world, not only to the United States.
clear explanations, full of examples and funny besides. This is not about the math but about using statistics, understanding how articles interpret information and statistical analyses.  I needed to buy a copy after borrowing the book from the library because I wanted to be able to refresh my memory, really cement some of these ideas into my head so that I can use the information over and over.  Yes, I have taken an undergraduate and two graduate courses in statistics but remember very little.  This book is so useful because we are assaulted daily with "results" from studies and we need a common sense but knowledge=-based appraoch to evaluate the significance of those studies and their results.  Dr. Wheelan:  you get an A!
I have been struggling to get through math-ier statistics books ... they put me to sleep. This was such a pleasant surprise, giving me insights into all those equations I had ground through elsewhere. I blew through the book without a yawn.