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Head First Series
Head First Statistics: A Brain-Friendly Guide
Wouldn't it be great if there were a statistics book that made histograms, probability distributions, and chi square analysis more enjoyable than going to the dentist? Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples.
Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics so you can understand key points and actually use them. Learn to present data visually with charts and plots; discover the difference between taking the average with mean, median, and mode, and why it's important; learn how to calculate probability and expectation; and much more.
Head First Statistics is ideal for high school and college students taking statistics and satisfies the requirements for passing the College Board's Advanced Placement (AP) Statistics Exam. With this book, you'
Before you know it, you'll not only have mastered statistics, you'll also see how they work in the real world. Head First Statistics will help you pass your statistics course, and give you a firm understanding of the subject so you can apply the knowledge throughout your life.
Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics so you can understand key points and actually use them. Learn to present data visually with charts and plots; discover the difference between taking the average with mean, median, and mode, and why it's important; learn how to calculate probability and expectation; and much more.
Head First Statistics is ideal for high school and college students taking statistics and satisfies the requirements for passing the College Board's Advanced Placement (AP) Statistics Exam. With this book, you'
Before you know it, you'll not only have mastered statistics, you'll also see how they work in the real world. Head First Statistics will help you pass your statistics course, and give you a firm understanding of the subject so you can apply the knowledge throughout your life.
716 pages, Paperback
First published January 1, 2008
145 people are currently reading
530 people want to read
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Displaying 1 - 30 of 31 reviews
November 17, 2020
I'm not sure how to recommend this book to people. If you're taking a statistics class, it is not detailed enough to be useful. If you're looking to improve your statistical knowledge in applied settings (i.e. ML, Data Analysis, & general scientific reasoning) it ends up being too focused on exams and classroom settings. My best recommendation is to skim through it and note the important topics, but don't spend too much time working through the problems by hand. They simply take up too much time and aren't entirely helpful for your understanding of statistics. That being said, if you just want a simple review of basic statistics and want something slightly more rigorous than the popular stats books that have emerged in the past few years, then give this a whirl.
October 30, 2018
This is book takes you for an enjoyable ride to explore statistics. I have never enjoyed reading a scientific books like this. It's not boring at all and concepts are well-explained. I really wanna thank the author for making scientific topics like statistics more enjoyable. after reading this, I am curious to read the rest of the Head First series.
June 10, 2010
This was horrible. All the useful stuff could've been fit on no more than 50 pages, with far better explanations. The method they use for presentation is able to drive mad almost everyone who's not mentally retarded or 3 years old.
Also, this book explains stuff which is so elementary it drives you crazy. Why do they need 2-3 pages to tell me how to calculate the borders when you split an array in equally sized parts, how hard is is b[x:]=(len/num)*x... (x-th border for len-sized array split in num chunks).
Pure waste of paper.
Also, this book explains stuff which is so elementary it drives you crazy. Why do they need 2-3 pages to tell me how to calculate the borders when you split an array in equally sized parts, how hard is is b[x:]=(len/num)*x... (x-th border for len-sized array split in num chunks).
Pure waste of paper.
November 28, 2015
This book is for people who begins to learn stat. It explains fundamental concepts like standard deviation, variance or even Bayes's theorem in an intuitive to understand and remember. Especially I really favor the Q&A section at the end of each part where the book will go into explaining relative questions regarding to the discussed topics. This Q&A is well-demonstrated in form of an interview. Sometimes I just went straight to the Q&A and Notes at the end instead of reading the whole section. It could save readers a bunch of time.
January 18, 2016
If you think statistics is hard , or you have hard time with statistics this book is the key to solve you problem fro basic statistics.
October 28, 2023
Book of the Day – Head First Statistics
Today’s Book of the Day is HEAD FIRST STATISTICS, written by Dawn Griffiths in 2008 and published by O’Reilly Media.
Dawn Griffiths is a prolific scientific author, trainer, software developer and the co-founder of HereScreen Ltd. She also created the video course The Agile Sketchpad with her husband, David.
I have chosen this book as, using statistics almost every day in my job – I even used it to develop the bias-recognizing algorithm in my thesis, I find it an extremely well-designed book on the subject.
Like all the other books of the Head First Series, this one also provides a unique, engaging, captivating, and even fun point of view on statistics, a subject many consider hard to understand.
One of the things that will immediately strike the reader’s eyes is its immersive and visually stimulating format. The design of the book employs a full array of colourful and easy-to-understand graphics, illustrations, and diagrams to explain statistical concepts, from the easiest to the most complex ones. This approach obviously sets this apart from typical academic statistics textbooks, making it more appealing to those who might otherwise be taken away from the subject.
The writing style of the author is brilliantly kept informal and conversational, which helps to demystify the formulae, jargon, and concepts of the subject. Griffiths uses a good dose of humour and real-world examples to make abstract statistical ideas more relatable and easily understandable even to novice readers. This tone of course helps in keeping the readers engaged throughout the book, even when tackling challenging topics.
HEAD FIRST STATISTICS is structured to accompany the readers on their journey from the basics to more advanced statistical concepts. It begins with the fundamental concepts and tools such as data collection, descriptive statistics, and probability, and then gradually progresses to more complex areas like hypothesis testing, regression analysis, and analysis of variance. Each chapter effectively builds upon the previous one, ensuring a logical and comprehensive learning path.
One significant strength of the book is that it provides an extensive number of exercises, quizzes, and puzzles to encourage readers to immediately apply what they’ve learned, and to reinforce their understanding of the material. These practical exercises are a valuable feature, helping to bridge the gap between theory and real-world application.
Another strength of HEAD FIRST STATISTICS is its coverage of a wide range of statistical topics. The book covers everything from basic concepts such as central tendency and variability to more advanced topics such as hypothesis testing and regression analysis, making it a valuable reference for both beginners who need to learn and experts who want to quickly review statistical concepts.
It has to be said that the book’s approach, with its conversational style, even if it is clearly engaging for some students, may feel a bit too casual for others who prefer a more traditional and formal approach to learning – and I am definitely one of them. So I would say that this book is more conceived to provide help to beginners or people seeking a general understanding of statistics. Everyone looking for a deeper dive into the theory, the maths, and the understanding of the more advanced statistical topics could easily find the coverage somewhat limited.
In conclusion, this book is an excellent resource for anyone looking to break into the world of statistics without being overwhelmed. While it cannot replace more in-depth textbooks for advanced studies, it is a fantastic introduction and a useful refresher for those seeking a more intuitive understanding of statistics.
Today’s Book of the Day is HEAD FIRST STATISTICS, written by Dawn Griffiths in 2008 and published by O’Reilly Media.
Dawn Griffiths is a prolific scientific author, trainer, software developer and the co-founder of HereScreen Ltd. She also created the video course The Agile Sketchpad with her husband, David.
I have chosen this book as, using statistics almost every day in my job – I even used it to develop the bias-recognizing algorithm in my thesis, I find it an extremely well-designed book on the subject.
Like all the other books of the Head First Series, this one also provides a unique, engaging, captivating, and even fun point of view on statistics, a subject many consider hard to understand.
One of the things that will immediately strike the reader’s eyes is its immersive and visually stimulating format. The design of the book employs a full array of colourful and easy-to-understand graphics, illustrations, and diagrams to explain statistical concepts, from the easiest to the most complex ones. This approach obviously sets this apart from typical academic statistics textbooks, making it more appealing to those who might otherwise be taken away from the subject.
The writing style of the author is brilliantly kept informal and conversational, which helps to demystify the formulae, jargon, and concepts of the subject. Griffiths uses a good dose of humour and real-world examples to make abstract statistical ideas more relatable and easily understandable even to novice readers. This tone of course helps in keeping the readers engaged throughout the book, even when tackling challenging topics.
HEAD FIRST STATISTICS is structured to accompany the readers on their journey from the basics to more advanced statistical concepts. It begins with the fundamental concepts and tools such as data collection, descriptive statistics, and probability, and then gradually progresses to more complex areas like hypothesis testing, regression analysis, and analysis of variance. Each chapter effectively builds upon the previous one, ensuring a logical and comprehensive learning path.
One significant strength of the book is that it provides an extensive number of exercises, quizzes, and puzzles to encourage readers to immediately apply what they’ve learned, and to reinforce their understanding of the material. These practical exercises are a valuable feature, helping to bridge the gap between theory and real-world application.
Another strength of HEAD FIRST STATISTICS is its coverage of a wide range of statistical topics. The book covers everything from basic concepts such as central tendency and variability to more advanced topics such as hypothesis testing and regression analysis, making it a valuable reference for both beginners who need to learn and experts who want to quickly review statistical concepts.
It has to be said that the book’s approach, with its conversational style, even if it is clearly engaging for some students, may feel a bit too casual for others who prefer a more traditional and formal approach to learning – and I am definitely one of them. So I would say that this book is more conceived to provide help to beginners or people seeking a general understanding of statistics. Everyone looking for a deeper dive into the theory, the maths, and the understanding of the more advanced statistical topics could easily find the coverage somewhat limited.
In conclusion, this book is an excellent resource for anyone looking to break into the world of statistics without being overwhelmed. While it cannot replace more in-depth textbooks for advanced studies, it is a fantastic introduction and a useful refresher for those seeking a more intuitive understanding of statistics.
May 21, 2023
I need to preface this review with what I'm looking for and why I read this book. I own a data science consultancy and do a lot of data science training. I'm increasingly seeing people from a large number of job roles either incorporating data science (and statistics) into their jobs or using data science tools (and therefore needing statistics) to properly analyze data. I'm on a quest to find the best books to recommend to my students, but I have specific criteria. The people I'm looking to help are adults who don't need to be full statisticians but need to understand statistics methods, and how to apply them to find and analyze insights. I'm looking for approachability, lots of concrete examples that can guide people about when to apply specific statistical approaches, and minimal math, because the people I'm working with will be turned off by a ton of math, and we have many tools to do the math for us today.
That said, I was not super happy with this book for my purpose. It is a well-written book, and it advertises itself by saying if you read it and do the exercises, you will learn statistics. I believe that is true. My audience would never get through this book, it is very math-heavy. One major shortcoming is that the math is long-form, done by hand. Professionals know how to do this math but don't. They use tools and programming languages. I think this book is missing an opportunity for broader appeal. For those who aren't going to be full-time statisticians, a second path with recommended tools, or even a programming language like Python, that allows readers to take the approach of viewing the long-form math, but performing with a tool, would make the book more approachable and allow for more experimentation by the reader. That could bring this book up to 4 or 5 stars for me and the audience I'm working with.
My other point of contention is both a point of strength and weakness for the book. They have lots of examples and have worked hard to make the examples work for the book. But the examples are somewhat hard to apply to many everyday jobs. I found myself getting frustrated that we were revisiting the same gumball factory over and over. To make the book more meaningful and drive home how concepts apply outside of the books examples, I think adding two to five pages at the end of each chapter with several different concrete examples of how the concept is used and the problems it helps solves would help connect the dots as to how people can apply this in their lives and jobs.
That said, I was not super happy with this book for my purpose. It is a well-written book, and it advertises itself by saying if you read it and do the exercises, you will learn statistics. I believe that is true. My audience would never get through this book, it is very math-heavy. One major shortcoming is that the math is long-form, done by hand. Professionals know how to do this math but don't. They use tools and programming languages. I think this book is missing an opportunity for broader appeal. For those who aren't going to be full-time statisticians, a second path with recommended tools, or even a programming language like Python, that allows readers to take the approach of viewing the long-form math, but performing with a tool, would make the book more approachable and allow for more experimentation by the reader. That could bring this book up to 4 or 5 stars for me and the audience I'm working with.
My other point of contention is both a point of strength and weakness for the book. They have lots of examples and have worked hard to make the examples work for the book. But the examples are somewhat hard to apply to many everyday jobs. I found myself getting frustrated that we were revisiting the same gumball factory over and over. To make the book more meaningful and drive home how concepts apply outside of the books examples, I think adding two to five pages at the end of each chapter with several different concrete examples of how the concept is used and the problems it helps solves would help connect the dots as to how people can apply this in their lives and jobs.
February 28, 2018
I took me almost a year to go through this book (I was doing about a page a day), and I hardly learned anything new, yet I'm still giving this book full five stars. I can see how it can get repetitive if you try reading through it in one sitting, but with a slow, methodical approach (if you have time for that, of course) it does wonders organizing all the important statistical concepts in your brain. Examples are a bit on the goofy side, but it actually makes it easier to mentally separate the concepts being learned from the fluff they are wrapped into. The whole approach might be somewhat gimmicky, but it worked for me. Now, on to more serious stuff.
January 7, 2018
This is my second time I read a book from the "Head First" type of books. Each time I feel that I am reading a magazine, not a boring book due to the use of images and examples.
I read this book when I was preparing for my Six Sigma Black Belt certificate. Although this certificate needs a higher appreciation for the statistics and the mathematical formulas, I found the book very useful in terms of setting the basic concepts right so I can build upon that.
A highly recommended book for undergraduate students as well.
I read this book when I was preparing for my Six Sigma Black Belt certificate. Although this certificate needs a higher appreciation for the statistics and the mathematical formulas, I found the book very useful in terms of setting the basic concepts right so I can build upon that.
A highly recommended book for undergraduate students as well.
November 16, 2017
I like the Head First series - I always look up if they have a relevant book if I want to start learning about a new field. I enjoyed this book, I think it gave me a great overview about what I should have learned at uni.
In the middle of the book (where probability got a bit more intense) the pace suddenly became very fast - even the spelling took it up. It was full of mistakes, typos and such. But then towards the end of the book it was cool again. Weird.
Anyway, I think it's a great start - now I feel prepared to dive into a few online courses.
In the middle of the book (where probability got a bit more intense) the pace suddenly became very fast - even the spelling took it up. It was full of mistakes, typos and such. But then towards the end of the book it was cool again. Weird.
Anyway, I think it's a great start - now I feel prepared to dive into a few online courses.
October 21, 2024
I like the Head First series. My favorite one is Head First Design Patterns. I did not finish my master's degree, so I did not learn statistics at university. That's why I decided to read this book. The beginning was perfect, but later on, I lost motivation (I realize that it could be more my fault than the book's).
March 24, 2021
Basic Statistics with focus on exams.
If you need Statistics knowledge for Data Science, machine learning then don't spend too much time on this book.
Few topics are explained in details but few topics like sampling and significance test can be explained better.
Overall a nice book which does a good job in explaining basics of one of the matured scientific topic Statistics.
If you need Statistics knowledge for Data Science, machine learning then don't spend too much time on this book.
Few topics are explained in details but few topics like sampling and significance test can be explained better.
Overall a nice book which does a good job in explaining basics of one of the matured scientific topic Statistics.
August 24, 2017
Best book for beginners and some intermediate people because many don't understand the basic concepts clearly with simple examples.
April 25, 2019
By far the best introduction to statistics that I’ve come across. It has helped me tackle a large A-level statistics book with confidence.
January 12, 2021
Great book if you want to learn Statistics from basics. Don't let the size of the book deter you. It is pretty easy read but covers quite a ground. Exercises keep you engaged in learning.
July 13, 2021
Too difficult for me
January 3, 2023
Statistics is now super easy and interesting with this book! Not a single boring page. Everything is explained with understandable examples.
October 20, 2021
I have read 4 Head First books before and really liked each of them, but I can't say the same for this one. What approach may work for coding books may not necessarily work for Math books.
This book looked like taking Head first template and putting Author's Statistics notes into the template. It's not the worst but it looked like at many places explanations and examples were sacrificed for following Head first template. Overall this book is okayish, may work for some and may not work for others.
Blitzstein and Bertsekas/Titskilis Probability books were available with their EdX courses, although those are verbose but both have far better explanations than this.
This book looked like taking Head first template and putting Author's Statistics notes into the template. It's not the worst but it looked like at many places explanations and examples were sacrificed for following Head first template. Overall this book is okayish, may work for some and may not work for others.
Blitzstein and Bertsekas/Titskilis Probability books were available with their EdX courses, although those are verbose but both have far better explanations than this.
June 25, 2024
A very good introduction to statistics.
Although it is very simple, I think the most important thing is that it tells us how to think about probability, for example, one of the lines in this book that really struck me is, "When you encounter a probability problem with repeated experiments, first consider what distribution it conforms to," so don't get hung up on the depth of this book.
But the last two chapters are too simple, and since there are probability density functions, I don't know why they don't talk about probability mass functions, and joint probability is not mentioned. Also, it's better to calculate area strictly by calculus.
But that's okay, just read Introduction to Probability and Statistics for Engineers and Scientists after this one.
Although it is very simple, I think the most important thing is that it tells us how to think about probability, for example, one of the lines in this book that really struck me is, "When you encounter a probability problem with repeated experiments, first consider what distribution it conforms to," so don't get hung up on the depth of this book.
But the last two chapters are too simple, and since there are probability density functions, I don't know why they don't talk about probability mass functions, and joint probability is not mentioned. Also, it's better to calculate area strictly by calculus.
But that's okay, just read Introduction to Probability and Statistics for Engineers and Scientists after this one.
April 12, 2015
Explained some of the basic concepts fairly well. I think the treatment of Binomial and Poisson distributions is probably better than I've seen in most texts. The section on permutations and combinations seemed to spend a lot of content to explain some fairly simple concepts. I liked the treatment of probability and probability distributions.
Overall, it's a readable book...but it didn't seem to offer the same level of pedagogical excellence as other Head First books. Whereas Head First Design Patterns and Head First Object-Oriented Analysis and Design do a fantastic job of synthesizing and explaining software engineering content, this seemed to be targeted more to high school students and sometimes seemed to go to extra lengths to avoid standard mathematical statistics notation.
Overall, it's a readable book...but it didn't seem to offer the same level of pedagogical excellence as other Head First books. Whereas Head First Design Patterns and Head First Object-Oriented Analysis and Design do a fantastic job of synthesizing and explaining software engineering content, this seemed to be targeted more to high school students and sometimes seemed to go to extra lengths to avoid standard mathematical statistics notation.
March 8, 2018
This was probably my favorite book of 2017. I am a big fan of the Head First series, but I have an advanced degree in computer science so I don't find much interest in the Head First programming books.
This one is different, I wanted a smooth introduction to statistics so I could spend some leisure time and study more advanced concept later on.
This book literally covers anything up to highschool statistics in a very pleasing and visual way, and you suddenly understand how to work with hypothesis, bayes rules as well as the main distributions properties. The part about non discrete probabilities just clicked in my head and I understood exactly why it's related to integral.
This one is different, I wanted a smooth introduction to statistics so I could spend some leisure time and study more advanced concept later on.
This book literally covers anything up to highschool statistics in a very pleasing and visual way, and you suddenly understand how to work with hypothesis, bayes rules as well as the main distributions properties. The part about non discrete probabilities just clicked in my head and I understood exactly why it's related to integral.
February 27, 2012
Inteersante modo de enseñar la parte práctica y básica de la estadística.
Desde cuando usar media, mediana y moda hasta test de Chi cuadrado y regresión lineal.
Si quieres aprender lo básido de estadística, puedes soportar que no hagan demostraciones y te agrada un libro que trata de ser entretenido además de didáctico, es para tí
Desde cuando usar media, mediana y moda hasta test de Chi cuadrado y regresión lineal.
Si quieres aprender lo básido de estadística, puedes soportar que no hagan demostraciones y te agrada un libro que trata de ser entretenido además de didáctico, es para tí
November 23, 2015
This is a broad introduction to statistics from the taxonomy of averages to various distributions to hypothesis testing, etc. The author has a spirited, whimsical approach that is engaging and entertaining. In-chapter quizzes and questions help the reader stay on track. A good adjunct for say a first-year college statistics text.
May 26, 2020
The initial chapters guide you so smoothly into the scary world of statistics. But suddenly the book appears to shift gears and sound a little too technical, to prove why statistics, or mathematics as a whole, is a dreaded subject. A good introduction overall, but would recommend a second, even third, reading of the book to make the most out of this. 3.5 stars!
November 29, 2010
Used this to review for my Statistics final. It was decent, but a bit too juvenile.
January 13, 2011
Very good system for introducing statistics, but there were a lot of calculation mistakes and typos that caused some confusion.
May 23, 2011
Painlessly covered more topics than my undergrad stats course did. A shame it wasn't available when I took the course. Would've saved me quite a bit of time.
January 16, 2013
Too basic for anyone that has had an introductory statistics course.
November 24, 2013
great read after completing intro stats course. really wrapped things up.
December 4, 2015
Quick, fun and sometimes silly reference book.
Displaying 1 - 30 of 31 reviews