Statistics without Tears: An Introduction for Non-Mathematicians Rowntree, Derek

by Derek Rowntree

THE CLASSIC GUIDE, NOW FULLY REVISED AND UPDATED

Why do we need Statistics?
What do terms like 'dispersion', 'correlation', 'normal distribution' and 'significance' actually mean?
How can I learn how to think statistically?

This bestselling introduction is for anyone who wants to know how statistics works and the powerful ideas behind it. Teaching through words and diagrams instead of requiring you to do complex calculations, it assumes no expert knowledge and makes the subject accessible even to readers who consider themselves non-mathematical. This clear and informative 'tutorial in print' includes questions for you to respond to in the light of what you have read so far, ensuring your developing ability to think statistically.

Genres: Nonfiction, Science, Mathematics, Reference, Research, Popular Science, Technology

208 pages, Paperback

First published January 1, 1981

Reviews

[Jan-Maat]

True to the promise of the title I didn't cry while reading this book.

Rowntree says at the end If you feel I've raised more questions in your mind than I've answered, I shan't be surprised or apologetic. The library shelves groan with the weight of books in which you'll find answers to such questions (p185), although having said that to my eyes this is pretty comprehensive for a non-technical reader and the kinds of questions it has raised are not ones I require answers to. The book is clear and plainly explained with worked examples it is written in a seminar style - so the flow is interrupted by mini-questions. I was interested by one example which set out how by doing a single tailed analysis in a drugs trial you can potentially skew the presentation of the result to make a drug appear far more effective than it is (Lies, damned lies and statistics afterall)

A nice overview of statistics with a useful review chapter, it will sit naturally on the bookshelf alongside such invaluable tomes as 'subtraction without sorrow', 'addition without anger' and 'multiplication without madness' and many, many others.

[Anna · Rating 4 out of 5]

I have a rather irregular history with statistics. After disliking maths GCSE but getting a very good mark, I avoided A-level maths like the plague. Upon arriving at university as a fresh-faced undergrad, I was disconcerted to discover that the first year of my social science degree included a compulsory statistics module. I passed that, then chose modules with no maths for the remaining two years. My dissertation was entirely qualitative. When I returned to studying as postgrad years later, I’d grudgingly come to accept that statistics are useful. My masters course included two statistics modules, which I appreciated the purpose of without enjoying. Then somehow, during the peculiar derangement of my PhD, I ended up teaching myself to use a fairly complex statistical methodology: multinomial logistic regression. The majority of my PhD research was quantitative. Now I find myself actually teaching statistics to undergrads. My 18 year old self would be amazed and horrified. It’s quite possible that I’m still outgrowing an ingrained dislike of maths that has much more to do with uninspired school teaching than the subject itself. In any case, I have a decent grasp of what stats are and why they’re useful, by social science standards.

So why read this book? Because the undergrads I taught this term, and probably the postgrads I’ll teach next term, appear petrified and confused by quantitative methods. It’s so difficult to tell whether students are really grasping the concepts you explain in lectures, particularly when there’s no exam to test comprehension. These are social science students and their prior exposure to stats seems to have been minimal. When I spotted this book in library, I wondered if it could help me to explain the basics more clearly. And I think it just might. I found it very easy to follow and a helpful reminder. Rowntree’s explanation of the difference between parametric and non-parametric tests is especially lucid and useful. That said, I doubt I'll have time to include such careful and painstaking explanations in my lectures. I’ll definitely recommend the book to students, though. It’s not at all fashionable to suggest students read entire books, but honestly I think this one is much better than an explanatory video, the more trendy teaching medium.

What this book cannot do, of course, is show you how to perform t-tests, correlation analysis, and regression in Excel or a proper stats programme. (I like R and tolerate SPSS.) While use of R or similar enables speedy and convenient quantitative analysis to a degree that was impossible in the era of graphing calculators, it also encourages an air of mystery around statistical techniques generally. The actual theory behind the technique is concealed. This book is brilliant for demystification; it narrates without equations to make clear that stats aren’t some arcane form of computer science. In the absence of basic understanding, it’s pointless to feed your data into a stats programme as you won’t understand the results you get, even if you happen upon a suitable technique for analysis. In a research methods lecture, there is sadly little time to cover explanatory fundamentals as the focus is on applied techniques. Somehow over more than 15 years, my refusal to take A-level maths has evolved into a wish that my students had taken it. Truly academia is fraught with irony.

Be that as it may, if you teach statistics to reluctant students, this book will give you helpful suggestions and food for thought. If you’re a reluctant student, or just wary of statistics, I highly recommend reading it as a short and gentle introduction. If nothing else, statistics are an extraordinary powerful force in the data-saturated world we live in. A basic understanding of their underpinnings and limitations will really help you to make sense of life. As I argued to my students, they can also make you seem like a magician to people who fear statistics. In academia, a clear understanding of stats is essential to enable you criticise other people’s work. Which is surely the whole point of research.

[Sarah · Rating 5 out of 5]

I locked myself in my apartment and read this book one weekend. It made statistics more concrete, clear, and less nebulous. Thanks to this book and some exceptional stats instructors, I now enjoy stats. It is nearly impossible to write a good statistics book. I have seen numerous terrible ones. This one is an accomplishment.

[ไม้ไต่คู้ · Rating 4 out of 5]

สำหรับเด็กอ่อน Stat อย่างผม อ่านแล้วอยากจะดึงคนเขียนมาจุ๊บด้วยความขอบคุณสักที เป็นสถิติแบบที่ใช้เรียนตอนป.ตรีเลย แต่อธิบายด้วยภาษาคน และการใส่ตัวอย่างมาแบบไม่มีกั๊ก ทำให้เนื้อหาหลายๆ อย่างที่ตอนเรียนเรารู้สึกว่า "ทำไมมันนามธรรมจังวะ? ตกลงไอ้ที่เรากำลังคำนวณกันอยู่นี่มันคืออะไร?" เคลียร์ขึ้นมาเยอะเลย

ส่วนตัวแล้วชอบครับ อ่านด้วยความสนุกสนานกว่าตอนเรียนเยอะ แต่สำหรับคนที่เก่งหรือเข้าใจเนื้อหาได้ตั้งแต่ตอนเรียนอยู่แล้ว อาจจะมองว่ามันธรรมดาก็ได้

[Leah · Rating 5 out of 5]

This is an excellent introduction to statistical thinking. The language used is conversational and easy to understand as you are guided through examples and ways of thinking about statistics.
The focus of this book is on the 'why' of performing statistical calculations so that the 'how' of those same calculations makes sense.
This is an ideal resource for anyone who needs to understand statistical concepts for their field of study or is simply interested in what statistics is really all about.

[sammy · Rating 4 out of 5]

I saw this on the shelf and immediately picked it up - I didn't have the best relationship with stats and wanted to try and salvage it before plunging into A Level Further Stats, which would have fully sent me into ruin if I didn’t at least try to attempt to love it.

Essentially, the book covers all the statistics in A Level Maths (and bits of Further Stats), explaining it in an accessible way and actively encourages you to think (so there really is no escape). The hatred of crunching numbers and learning methods without understanding what I was doing has now been rectified.

I've probably picked the best time to read it, warmed up my brain after a summer of not much mathematical thinking - and I am sure I'll be rereading sections throughout next year as we cover them. (I do have to mention that stats does not go only as far as a module in A Level Further Maths, it is very much used around and beyond.. I hope I now think a little more statistically than before)

The book promised no tears, and I haven't cried! Yet, at least…


'the possibility of bias in samples, the distinction between significance and importance, the fact that correlation does not imply causation, and that people sometimes simply get things wrong.'

••••••••••••••••••••••••

15/09/22 - have a stats test tomorrow, revising the concepts actually made sense.. very grateful but we will see how it goes
??/09/22 - I failed my first test ever... lost all marks the large data set
??/10/22 - Further Stats module is very enjoyable so far!!!

[R L · Rating 5 out of 5]

Concise introduction and refresher on statistics that is suitable for both math-intensive and non-math intensive majors.

As someone that has previously studied many of the covered topics, this was a comfortable way of reviewing and organising the subject matter. I found that some of the explanations provided were far more accessible than the way in which I was first taught statistics.

This is not a comprehensive guide to statistics and does not claim to be so. Fortunately, there's an extensive further reading list at the end.

[Mohit Dhanjani · Rating 3 out of 5]

This book was probably the most lucidly written book that I have come across that explains Statistics to a person entirely alien to the field.
Unfortunately, even then I got lost by the end.

Regardless, this should be the first book anyone should read if they want an introduction to the world of statistics. It contains no calculations and it is very engaging.

Though, I might have to read it again and look for more books that can demystify this subject in context of social science.

[Brendan · Rating 2 out of 5]

Eh, it was ok. I'm not sure why these books seem to be so against updating to show use cases with current computational software (R, Python,...even...ugh, Excel), but they do seem to cavil at the idea of it. That would be fine, as I read this book looking for any little intuitions that I may have missed about some basic topics, but unfortunately, both the intuitions and the theoretical portions felt half finished. If you're looking for a refresher on statistics that helps with intuitions, I would definitely go with Head First Statistics over this one.

Note: I recognize that I'm putting commas in all sorts of places, but some days that comma just speaks to you on a deep level. I don't feel gross enough about it to fix it.

[Gary · Rating 3 out of 5]

Book Ranking System:
1 - Bad - Do not read
2 - Okay - Read Once/ Don’t Bother Twice
3 - Good - Read at Least Once
4 - Great - Read at Least Twice
5 - Incredible - Buy Book and Visit Often

It was okay but as someone who has no invested nterest in statistics it did get a little information heavy. If I was more reliant on stats for work or general information I would certainly pick this book up again.

That being said there were some good tidbits of information on misuse of statistics by third parties to strengthen their cause. Biases in marketing is a topic that interests me since I am obviously a consumer myself.

I wish I understood statistics better and would definitely give this book another go if it would help me.

[Jessy Fisk · Rating 4 out of 5]

This is a wonderful little companion for an introductory statistics class, my only qualm is it goes from calling scatter diagrams 'dot diagrams' to suddenly trying to explain chi-squares using only words. Helpful if you prefer to learn by understanding why you are doing something, rather than just cookbook maths.

[Heather · Rating 4 out of 5]

This book was pretty good and cleared up alot of statistical principles for me. It was definitely not a "fun" read for me, but I like how Rowntree used examples with all sorts of things, like gnomes.. to try and lighten the tone.

[Ashok Krishna · Rating 5 out of 5]

A must read if you are interested in statistics. More so, if you are not. A brilliant read!

Will share the complete review soon.

[Keary Birch · Rating 3 out of 5]

An easy and useful read on the subject of Statistics. This is a book for the layman that (by its own definition) does not go into the mathematical equations as "there are enough books on that". What it does, however, is to introduce and explain the concepts in a way that can be easily digested. My one complaint would be that there are some errors in the few equations that it does use.

Still worth a read if you have to understand Stats but really don't want to.

Me? I love Stats!

[Claire · Rating 5 out of 5]

This book is excellent. I'm currently studying for a master in public policy & have to do a course on quantitative data analysis. The course (rightly or wrongly) assumes a basic knowledge of statistics which I did not have (beyond everyday parlance). In plain English (and not scary equations!) this book uses simple everyday examples together with a wry humour. I'd imagine it was hard to cut back the jargon & math heavy terms to make this accessible. Bravo Derek!

[Isabel · Rating 4 out of 5]

Read this to get back into statistics again for my Masters after having a 3 year break from uni so I found this a useful refresher book. It does give an overview of most of the key concepts, but as another person said might be lacking in depth in some places for those without a prior experience of stats.

[Pablo · Rating 5 out of 5]

Very good basic easy to understand introduction to statistics world...without going mental...that much :)

[Darren Cook · Rating 5 out of 5]

A bloody godsend!

[Oona · Rating 3 out of 5]

Honestly, I wanted to cry

[Jad Malaeb · Rating 5 out of 5]

Like many, my relationship with statistics had been one of intrigue but general resignation: My “understanding” of the concepts in class room sessions often failed to translate onto my examination marks. I put off my Statistics course, which was a second-year prerequisite at university, until my last year, and I only ended up getting through it via a “Pass/Fail” credit.

Aside from the mathematical complexities, I was plagued by programming languages that seem to have been designed by dinosaurs (I’m looking at you, “R”) and interaction with material that I thought I would have no relationship with following my graduation.

In retrospect, these appear to be mistakes. As an aspiring trader, my world is deeply tied to statistics and programming languages (although I still think “R” is ugly). Reading “Statistics Without Tears” slowly chipped away at my prejudice toward the subject. Derek Rowntree writes and educates in a way that I believe most statistics teachers can only dream of doing. Instead of dosing off during the book’s “lectures,” like I did in university ones (on the ones I didn’t skip), this book had me hooked from beginning to end.

Rowntree makes statistics more “human” by shedding away complicated statistical formulae and replacing them with robust conversations. He explores the concepts that these formulae describe, pausing throughout the book to ask questions that force you to think. This give-and-take approach made the book feel conversational, a momentous accomplishment in statistics in my view.

Some may suspect that the lack of excessive calculations (you still have to do some calculations, although most are simple enough to be done mentally) would lead to a suboptimal learning experience. I strongly believe this hasn’t been the case. The foundations on which these calculations are based are far more important to understand, in my opinion, than how to derive the numbers. The practical can be learnt through practice, but theory must be explained, and Rowntree does an exceptional job explaining statistical concepts.

I would’ve loved to read this book at university but better late than never. If you’re considering reading this, do it; it’s worth it.

[Simon Fletcher · Rating 5 out of 5]

This is an absolute Ronseal book, it does exactly what it says on the tin.
I have been,over the years, what can only be described as a reluctant mathematician. This largely springs from having been the recipient of a mediocre schooling in basic maths. In turn this has meant that my understanding of the further complexities of maths and statistics has been sketchy in the extreme. And for a Nurse soon about to embark on a PhD that could be considered a big tick in the, oh dear this could be tougher than it looks box.
Roundtree's book though is an absolute God send. It's helped me to understand the principles which lie at the heart of the statistics and what statistics can and can't show. It's not been an easy read. I have had to take it in small bite sized pieces, often re-reading sections to ensure I have what was said pinned down. I would still not claim to be comfortable with stats but I do now feel a little more comfortable with them.
A great and eternally useful book and one I'm sure will be always near at hand to help me refresh my understanding over the next few years as I tackle my PhD.

[Michael · Rating 3 out of 5]

NB: This book sat on my active list until 17/6/19. I just never got around to figuring out when I finished it, as a result the certainty is even less. I believe I didn't list it as finished as I hadn't taken notes on the very last chapter and just simply read it to get it returned, or something. I did eventually go back and finish taking notes (at least I recall doing so, and my notes seem to extend to the end, but perhaps I was intending to do something else with them e.g. annotate, idk). Anyway, the finish date here is based on habit tracker & the date I started reading the next book after this. Close to accurate, i'm sure.


As for the book: A good little book, I read it along side a stats class and found it helped fill some holes that existed in my understanding, yet at the same time simply wasn't deep enough. I think this book is suited better to people with *absolutely no experience* with statistics, as opposed to a little like I had. That's my fault, not the book's. Still worth the read.

[Steve Dragon · Rating 3 out of 5]

The difficulty of rating this book is that I am not entirely convinced it was for me.

It teaches statistics from the very basics and goes to a relatively good degree of depth. It is quick, it is streamlined and it gives you the basic tools you need to interpret statistics. It shies away from some of the terminologies, most notably it refuses to use greek letters, but I think that does not really impact it too much.

A brief and informative read that helped me review the statistics material I had studied, but I need to qualify that by saying this will not be enough. It's a good starting point, and if you've studied statistics before then it will remind you of the terms and help you conceptually. However, you will need to supplement this with other reading and practice centred around why you want to understand statistics and the tools you want to use.

All in all, a good review book that covers all the ground from near-scratch. If that's not what you're looking for, not for you. For me, it worked because I wanted a brief overview before I dived into it in more depth.

[Alistair]

in progress

Contents

Introduction - 9
How to use this book - 10
1. Statistical inquiry - 13
making sense of experience - 14
What is statistics? - 17
Descriptive and inferential statistics - 19
Collecting a sample - 23

2. Describing our sample - 28
Statistical variables - 28
Error, accuracy and approximations - 35

3. Summarizing our data - 38
Tables and diagrams - 38
Central tendency (averages) - 48
Measures of dispersion - 50

4. The shape of a distribution - 57
Skewed distributions - 58
5. From sample to population - 82

6. Comparing samples - 102

7. Further matters of significance - 128

8. Analysing relationships - 155

Postscript - 185
Review - 186
Caution - 188

Further Reading 191

Index - 193

[JH · Rating 5 out of 5]

I consider this a must-read if you've ever taken postsecondary or college-level math (which would have covered the basic statistics mentioned in the book).

This is a chance to finally make (more?) sense out of what you've learnt in school, especially regarding the estimation of a population via sampling (e.g. standard error), how significant a result is (e.g. z-test, t-test).

Rowntree wants you to understand the concepts instead of the formulas, so it makes the read easier. If you ever had to do null-hypothesis testing in school decades ago, the content should come easy to you.

I wish I had this book when I was schooling, as it would have made statistics more meaningful and digestible. Then again, learning to enjoy statistics ... might not be good thing 😆

[Saara · Rating 3 out of 5]

I gave this book 3 stars not due to dislike but the general repetition and the target audience being for non mathematicians, which I did not clearly read on the front cover. It is a very useful summarised guide to A level statistics maths and further statistics, however as someone who took both at A level I did not find any new content in this book apart from these three topics: significance of significance, comparing dispersions and analysing relationships with a link to PMCC and regression. I very much recommend this mini book for sixth formers. I would’ve very much liked to have read something like this when I did my alevels and if you’re sitting the 2018 new spec a level statistics (without pure,trig or calc) maths in the uk, it’s pretty much most of the spec covered.

[Sam · Rating 5 out of 5]

I'm not sure, whether this book is great, or it is just the cumulative result of many months of studying, but after reading it, I finally got the grasp on many basic things in statistics. There is the third option - I'm just too silly for statistics.

Anyway, this is not a professional texbook, but this book introduces and very clearly explains not only basic statistics (mean, standard deviation, etc.) but also clarifies the application of basic statistics tools (significance tests, confidence intervals and so on).

[Jonatan Almfjord · Rating 4 out of 5]

A solid book trying to make statistics just a tad more enjoyable. If you work your way through it, preferably with a pen and paper at hand, you'll surely discover a thing or two that you didn't think of before. Were you totally uninterested by statistics before reading, I doubt you'll feel any more passion for the subject after reading. On the other hand - the statistical probability that you even considered reading this book unless you actually wanted to improve your skills to begin with... is most likely rather low.

[Cod Er · Rating 4 out of 5]

Great little book. I have a decent background in stats from my undergrad days but wanted a refresher to make sure my basics were still solid and this was perfect. For complete newbies, I think this is a great book to wet your appetite without overwhelming you with unnecessarily details.
I LOVE that the author includes questions along the way so that the reader can test their understanding. That’s the best way to make sure that you’re actively processing the material and the reason why I’ve already recommended the book to two friends who are trying to start learning stats.

[Reader · Rating 5 out of 5]

I recommend this if you need to quickly get acquainted with an overview of practical statistics as it’s commonly used. Terrific help for me as prep for reviewing for exams. Typically in a class you learn how to perform the tests and it’s easy to get lost in the details, but this explains why and in what situation you do which test. Concepts are explained with examples but with little to no math. Very helpful bird’s eye view for beginners - puts it all together. I needed 2 days approx. 8 hrs each to finish it.