Renowned for its clear prose and no-nonsense emphasis on core concepts, Statistics covers fundamentals using real examples to illustrate the techniques. The Fourth Edition has been carefully revised and updated to reflect current data.
Good, but perhaps too simple? I can see why some people don't like this book, although it's one of the clearest mathematical textbook I have ever seen in my limited experience. Because it's too clear and easy to understand, it may seem even trivial especially to those who like mathematics for its complexity and sophistication (whether real or not). It is a pretty well-known psychological phenomenon, however: you tend to perceive something to be of high quality if you have a harder time understanding it (one experiment I have in mind is how people's rating of restaurant food changed depending on how hard it was to read the menu). This might in part explain some people's raving reviews of abstruse modernist works of literature (like Joyce's Ulysses or Pynchon's Rainbow's Gravity, both of which I slugged through with guidebooks).
Anyway, though the exercises were a little too easy, this textbook is definitely a GREAT way to start studying statistics, as it requires only the knowledge of some high school algebra and explains everything so well that you really don't need to spend hours trying to decipher what's going on in a proof or an equation.
Will be reading Freedman's more advanced textbook, Statistical Models next, supplemented maybe with some standard college textbook on mathematical statistics, like Wasserman's All of Statistics.
Decent textbook on statistics. The book itself is aimed at both a general public and undergraduates, meaning that the content is not too sophisticated. I read this to freshen up my rusty statistical knowledge (to prepare for some tests), so in this sense the book has served its purpose.
The authors write in an accessibly style and use lots of simple examples to lay down the foundations of the most important statistical theories and tools. Descriptive statistics, inferences, frequency theory of chance, using models, and tests of signicifance like the chi square test (for testing frequencies) and t-tests (both between-group and within-group analysis).
It would have been nice to read some more about the historical context of these ideas and their development over time. Also, it would have been nice to read some more about the philosophical problems surrounding statistics as tool for reliable knowledge. The authors mention that in modern science, especially the alfa sciences, statistics is over-used and in many cases merely used as weighty language to proffer up results.
I can attest to this last point - any analysis based on models is simply based on the assumptions of the model itself. Trash in = trash out. Modern sciences like psychology like to present their results as significant, but they're really only presenting their own assumptions in weighty language. (It is common knowledge that replicability, for example, is a huge issue in psychology and that sociological research is heavily influenced by political-ideological assumptions). Would have been nice to read some famous case studies...
Anyway, the book is decent - I can't really recommend it besides digging up old knowledge. To learn statistics one needs some more guidance, preferably within a course setting.
Any statistics book will teach you how to calculate means, standard deviations and covariances. But this book also teaches you the why behind the equations and when NOT to apply the equations. That is, it teaches you how to sniff out bad experimental design and data sets that do not fit the standard (or normal) distribution.
The authors made a good amount of effort making abstract concepts easy to understand, they didn’t fully succeed but overall the book is really good for having a clear picture about statistics
If you want to learn the ins and outs of statistics, this is the book for you. One wonders why exactly you would have such a desire, but that might just be too much information! This book is extremely well-written, and is designed for those (people like me) who don't have much in the way of advanced mathematical skills. Though I read this for a course I had to take, I actually enjoyed taking on some of the abstruse concepts presented here. It certainly makes much more sense of some of what you read every day when it comes to statistical analysis.
Ever get lost in statistics class or when a mathematical formula is brought you, you instantly feel like giving up because you just aren't a mathematician?
I've always found myself tuning out when some obscure mathematical formula is brought up in a textbook or a reading. The mathematical notations and foreign symbols immediately takes all the joy out of diving into statistics. Statistics though is a critical component to designing a data experiment, and evaluating the data models. Thus this book is designed for those who don't have much in the way of advanced mathematical skills (people like me). No more tedious math jargons and sophisticated formulas
𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐭𝐡𝐚𝐧𝐤𝐬: From my weekly study buddy who resided in Austin, Texas. In our weekly calls, he would constantly refer to this book when we wanted to clarify some steps to calculate a statistic.
𝐒𝐮𝐠𝐠𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝟗/𝟏𝟎: Great for those who want a quick refresher but don't have the patience to go through a whole statistics course again.
This should be everyone's first statistics book. I am still trying to remedy the abysmal statistics education I had and am continually shocked by my lack of understanding of basic concepts. Instead of anything useful, I had two semesters of moving symbols around until we were satisfied we had the right set of formulas to memorize (ie 'proofs').
The following is speculation, but it seems to me that most of the lessons of statistics are like those of quantum mechanics--we don't really know why they work, but we've found them to be true after a lot of trial and error. So much of the scary-looking math in statistics has no proof. We've just found that phenomena in the world can be described by a small family of exponential functions. Why? Well, they have some nice mathematical properties: they're smooth, they never touch 0, and you can take the natural logarithm of them so you can turn multiplication into addition. But we don't really have an answer for why these formulas work and not others. I think it is this lack of explanation at the core of statistics that leads it to be taught so poorly. We focus on what can be 'proved' (ie shown to be equivalent), which is a really small set of things that few people care about. Certainly not people new to the field.
During the fall of 1993, I was in my first semester of college. I took statistics and didn't like it at all. This was likely my own fault, as I was not a very serious student -- occasionally ditching class and frequently staying up much too late. During that fall semester in my statistics class, I wrote what seemed like a massive paper to an 18 year old, at 21 pages long (but it included data). Since I was 16, I had a job at Montgomery Ward at Randhurst shopping mall, where I sold shoes -- perhaps trying to fulfill my lifelong aspirations to be Al Bundy -- that job I kept until I was 21. For my paper, I kept record of customers at Montgomery Ward in the shoe department for an entire day and recorded the amount every single customer spent on items. I also had to record whether shoppers bought with cash or credit, and then conduct an independent samples t-test to compare whether there was a statistically significant difference in average amounts spent by the two types of customers. Sure enough, there was a difference, with credit card customers spending more on average than cash paying customers. While Pisani et al.'s text was useful enough to show me the equation to conduct that t-test, it wasn't a very helpful text. It didn't cover any computer use for statistics, and the problems seemed a bit contrived. However, looking at the text book today, it seems logical and the presentation is fine -- though not particularly wonderful or inspiring. This text is fairly standard in many mathematics and statistics departments. It's now in a new edition, and the main change in the new edition is its data. I might use it if I had to teach stats to a math department, but I'd certainly want to consider options.
I was drawn to this book by its promise of simple explanations and lack of complex mathematical formulas. Now, I think I should have gone for a little more math-heavy book, as this one is way too simplistic at times, and most of it will already be familiar to anyone who had a semi-decent Probability Theory class. There are a lot of examples and exercises (around 50% of the content) which make it more of a textbook rather than an introductory guide. And actually some colleges use it in the curriculum, the "school vibe" can be perceived. I think, "Statistics" deserves a solid 3.5, but having to choose discretely I rate is as 3. I think, there exists other material that's more engaging and challenging.
I have tutored a few college students in statistics and this is the best textbook I have seen. (Including searching through alternative texts for them to use) The sections are clear and brief with good examples and then practice questions with answer checks in the back so a student can learn and practice before moving on. One improvement I would have liked to see is to have, at least some, longer explanations or work shown for answers to help when a student doesn’t yet grasp the concept. This is a textbook for class - I don’t know that it’s a great text to self teach (although Kahn Academy is good for that)
Finally ! book that will learn you statistics in simple way ! I had a lot of statistics books and they all were too complicated. It's like authors on purpose make it hard to learn to make it less accessible for normal people - and by normal I mean people without solid math background.
For me, the biggest feature of this book, are examples - they are very simple and they show you, step by step, how everything is working. They are supported by nice graphs and pictures, which helps a lot. They guide you through the process and in the end everything begins to clarify and became simple - sometimes even too simple :)
Since I remember, I was always struggling with probability. In previous books that I read, it was never explain in simple and easy to understand way. But this book changed it ! Now I have basic understanding and I can use simple probability techniques in real projects. And yes, I wrote `simple and basic` because this book don't learn you advanced topics. It's now going very deep in each subject. If you would like to learn more advanced topics, you must find another book.
In my opinion, this is perfect book to start with. If you don't have good math and statistics knowledge, just buy this book and learn. I can recommend it in 100%.
Don't get me wrong, this is an excellent work, it's just, at this moment in time, not for me. I only realized this very recently too. Though I started from the beginning, after a few chapters, I read some specific chapters out of order. I know some other reviewers have said that someone should start learning statistics with this, but I think that for me atleast I should come back to this book when I already think I know a thing or two about everything this book touches on. The point being that a clear explanation is not always fully appreciated by the person who's being exposed to the topic at hand for the first time. The reason this is clear is simply written in its own description, there aren't any real formulas; there are only ideas, stories, and real life cases discussed. Even the exercises aren't bad, I even thought of the book as being as funny as it gets with math textbooks. I'm just somewhat sure that I'm not going to be building any level of fluency without practicing how the formulae and the rest work, and ideas don't stay without some fluency.
This book is designed from very basic idea, with ample examples, to the very complex hypothesis. Author introduce these statistic ideas gradually with very good points of views, no tedious math jargons nor sophisticated formulas, the declaration is very clear. I high recommend this book to anyone who is devoted himself or herself on the statistics study. Good book!
Very informative. It’s not a typical stats book that tells models and equations, but gets behind the scene and reveals what stats really is, while eliminating all the unnecessary mathematical complications.
This book counts towards my goal purely because at the beginning of the year my professor said “this is not a math class. You will read every page of this book” and I took that SERIOUSLY!
Quite liked this book. It goes through a lot of cute examples from the historical use of statistics and isn't too caught up in modern Bayesian trends to forget to explain them.
I read this book as part of a course in my graduate studies. I'm sure it seems strange to say I really liked a statistics textbook but I have my reasons. The authors make it clear in the introduction that they will not barrage readers with equations and they do an amazing job of teaching statistics without bars, hats, and Greek letters everywhere. They avoid equations by explaining the concepts in complete sentences and I had no problems picking up a calculator and translating those words into actual calculations. They intersperse sample problems that are different than those I am used to seeing in other texts, where the reader is really doing more thinking than calculating. Where other texts spend pages explaining concepts, these authors invite the reader to reason their way through those same concepts. I felt like they did a great job of showing me where to look without telling me what to see.
I saw this on my brothers's old textbook shelf. I deal in statistics so I wanted to brush up using a basic text. I was very pleasantly surprised by the content of this book. It teaches statistics in a way different than the usual manner by using lots of examples, both real and hypothetical. The review questions are also case studies which makes the subject related.
This book is awesome! I read it in conjunction with a statistics course offered on edX, and it was so understandable and readable. I highly recommend it. Although I read the 1978 edition, the content was still relevant as long as I ignored the income levels, etc.
Recently finished this book in conjunction with an intro to statistics course. The book was easy to follow and could, at times, have a sense of humor. Though it did not delve into much theory it served the purpose of education beginners to the basics of statistics.