Modern Statistics Is Very Different From The Dry And Dusty Discipline Of The Popular Imagination In Its Place Is An Exciting Subject Which Uses Deep Theory And Powerful Software Tools To Shed Light And Enable Understanding And It Sheds This Light On All Aspects Of Our Lives, Enabling Astronomers To Explore The Origins Of The Universe, Archaeologists To Investigate Ancient Civilisations, Governments To Understand How To Benefit And Improve Society, And Businesses To Learn How Best To Provide Goods And Services Aimed At Readers With No Prior Mathematical Knowledge, This Very Short Introduction Explores And Explains How Statistics Work, And How We Can Decipher Them

Is a well-known author, some of his books are a fascination for readers like in the Statistics: A Very Short Introduction (Very Short Introductions) book, this is one of the most wanted David Hand author readers around the world.

ebook

137 pages

Statistics: A Very Short Introduction (Very Short Introductions)

David Hand

07 June 2019

David Hand

9780191552786

David Hand

10 thoughts on “Statistics: A Very Short Introduction (Very Short Introductions)”

Statistics a very short introduction Very Short Introductions 196 , David J HandModern statistics is very different from the dry and dusty discipline of the popular imagination In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them 2015 1391 177 9786005492514 21

Statistical analysis underlies much of the modern scientific research In fact, it is not too much of a stretch to say that many scientific fields have come of age and many other fields have become scientific thanks to the extensive use of statistics that they employ The turning point seems to have been the advent of modern computer For the first time in history the raw computational power has not been an issue any , and the only limits on the quality of research became the amount of data that can be collected and the understanding of statistical methods that need to be employed for analysis This very short introduction deals with statistics as a method for analyzing empirical data As such, it does not present statistics as a dry and self contained mathematical subject All the statistical methods are introduced in conjunction with particular practical problems that those methods are developed to address The author, David Hand, is trying to convey the message that statistics is as much of an art as it is a rigorous mathematical method No two research projects are the same, so no simple statistical procedure could be used to describe them all A careful analysis of the problem at hand and a judicial choice of statistical methods are the most likely to yield the most useful information The book is divided in seven chapters and each one deals with a particular statistical concept or a particular way in which the statistics is used The chapters are short but informative, and the whole book makes for one smooth read It will not overburden you with mathematical detail, and it can be used as a springboard for further reading into the field of statistics.

The Good In my mind, statistics isolated from its application in real world problems is triviality, and frankly a rather dull form of triviality This form of statistics and math in general is what I remember learning in school So, I was pleasantly surprised with this book, which provides a holistic overview of statistics, providing context of why s when s where s instead of just the how s I mean, there is an entire chapter called Collecting good data Since you should not expect advanced details in A Very Short Introduction , you are looking for a presentation that places the topic in time and space, and opens interesting doors for further investigation In this sense, this book does the job It seems exciting reads would tackle stats applied to a particular topic My go to is Ben Goldacre esp public health epidemiology Been meaning to read Nate Silver as well

A nice little book for those who have already done a basic statistics course, but would like to review or systematise the concepts behind the mathematical tools I doubt that it can be of much use for those who have never learned any statistics, even though it seems to be aimed at readers unfamiliar with the topic.

Was looking for a qualitative introduction to convey something of the excitement and philosophical importance the art of discovering anything which isn t bleedin obvious nor knowable apriori This has bits of that Statistics is applied philosophy of science it is the technology for handling uncertainty but is still too dry to recommend as a first exposure He diagnoses the worst parts of university teaching hand calculations, canned inference, and the exhausting, interminable bag of tools approach, rather than computers and The Framework But the latter have steep learning curves I think the biggest thing missing is simple tailoring of datasets let them pick something they care about to study, to learn how to study on Lots of ML methods covered, without a single mention of the phrase machine learning This is fair enough if you consider how much of enterprise ML hype is just rebranded 40 year old stats.Hand notes the origins of the field as State istics , i.e as the beginning of bureaucracy and surveillance But he doesn t feel the tension of this fact that it helped to transform us, for good and ill, into legible people.One dodgy idea he claims that numbers offer a direct apprehension of reality than words, that they re realer But this isn t why they re better they re better because they re sensitive it s at least possible for them to track any size change in the world, while words are mostly stuck to medium sized dry goods and because they are easier to spot errors in.

Contents view spoiler PrefaceList of illustrations1 Surrounded by statistics Modern statistics Some definitions Lies, damned lies, and setting the record straight Data Greater statistics Some examples Example 1 Spam filtering Example 2 The Sally Clark case Example 3 Star clusters Example 4 Manufacturing chemicals Example 5 Customer satisfaction Example 6 Detecting credit card fraud Example 7 Inflation Conclusion2 Simple descriptions Introduction Data again Simple summary statistics Averages Dispersion Skewness Quantiles3 Collecting good data Incomplete data Incorrect data Error propagation Preprocessing Observational versus experimental data Experimental design Survey sampling Conclusion4 Probability The essence of chance Understanding probability The laws of chance Random variables and their distributions5 Estimation and inference Point estimation Which estimate is best Interval estimation Testing Decision theory So where are we now 6 Statistical models and methods Statistical models putting the blocks together Statistical methods statistics in action Statistical graphics Conclusion7 Statistical computing Statistics changes its spotsFurther readingEndnoteIndex hide spoiler

This is not a practical book, but rather a short description of statistics, from its worth to its methods And I struggle to conceive of how it could have been better written OK, the penultimate chapter is essentially just a slightly staccato series of mini introductions to various aspects of stats too involved to cover in greater detail, but up to that point the book is engaging, concise, and witty a real breath of fresh air.I may not know much about stats now than I did when I started reading speaking purely personally, not for every potential reader , but I do know one thing David J Hand can write a book.

This book does what it s supposed to Give a gentle introduction to topics in statistics and probability theory, culminating in a high level description of statistical methods these days associated with the field of machine learning But pretty much everything is explained just in a couple sentences, with examples rather than the theoretical underpinnings So don t expect to understand why things work the way they work or become a well versed practitioner after this book Rather see it as an overview, a pointer to topics to be read about in detail In other books.

Statistics a very short introduction Very Short Introductions 196 , David J HandModern statistics is very different from the dry and dusty discipline of the popular imagination In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them 2015 1391 177 9786005492514 21

Statistical analysis underlies much of the modern scientific research In fact, it is not too much of a stretch to say that many scientific fields have come of age and many other fields have become scientific thanks to the extensive use of statistics that they employ The turning point seems to have been the advent of modern computer For the first time in history the raw computational power has not been an issue any , and the only limits on the quality of research became the amount of data that can be collected and the understanding of statistical methods that need to be employed for analysis This very short introduction deals with statistics as a method for analyzing empirical data As such, it does not present statistics as a dry and self contained mathematical subject All the statistical methods are introduced in conjunction with particular practical problems that those methods are developed to address The author, David Hand, is trying to convey the message that statistics is as much of an art as it is a rigorous mathematical method No two research projects are the same, so no simple statistical procedure could be used to describe them all A careful analysis of the problem at hand and a judicial choice of statistical methods are the most likely to yield the most useful information The book is divided in seven chapters and each one deals with a particular statistical concept or a particular way in which the statistics is used The chapters are short but informative, and the whole book makes for one smooth read It will not overburden you with mathematical detail, and it can be used as a springboard for further reading into the field of statistics.

The Good In my mind, statistics isolated from its application in real world problems is triviality, and frankly a rather dull form of triviality This form of statistics and math in general is what I remember learning in school So, I was pleasantly surprised with this book, which provides a holistic overview of statistics, providing context of why s when s where s instead of just the how s I mean, there is an entire chapter called Collecting good data Since you should not expect advanced details in A Very Short Introduction , you are looking for a presentation that places the topic in time and space, and opens interesting doors for further investigation In this sense, this book does the job It seems exciting reads would tackle stats applied to a particular topic My go to is Ben Goldacre esp public health epidemiology Been meaning to read Nate Silver as well

A nice little book for those who have already done a basic statistics course, but would like to review or systematise the concepts behind the mathematical tools I doubt that it can be of much use for those who have never learned any statistics, even though it seems to be aimed at readers unfamiliar with the topic.

Was looking for a qualitative introduction to convey something of the excitement and philosophical importance the art of discovering anything which isn t bleedin obvious nor knowable apriori This has bits of that Statistics is applied philosophy of science it is the technology for handling uncertainty but is still too dry to recommend as a first exposure He diagnoses the worst parts of university teaching hand calculations, canned inference, and the exhausting, interminable bag of tools approach, rather than computers and The Framework But the latter have steep learning curves I think the biggest thing missing is simple tailoring of datasets let them pick something they care about to study, to learn how to study on Lots of ML methods covered, without a single mention of the phrase machine learning This is fair enough if you consider how much of enterprise ML hype is just rebranded 40 year old stats.Hand notes the origins of the field as State istics , i.e as the beginning of bureaucracy and surveillance But he doesn t feel the tension of this fact that it helped to transform us, for good and ill, into legible people.One dodgy idea he claims that numbers offer a direct apprehension of reality than words, that they re realer But this isn t why they re better they re better because they re sensitive it s at least possible for them to track any size change in the world, while words are mostly stuck to medium sized dry goods and because they are easier to spot errors in.

DATA datum dare 1999 .

Good high level intro of statistical discipline in general

Contents view spoiler PrefaceList of illustrations1 Surrounded by statistics Modern statistics Some definitions Lies, damned lies, and setting the record straight Data Greater statistics Some examples Example 1 Spam filtering Example 2 The Sally Clark case Example 3 Star clusters Example 4 Manufacturing chemicals Example 5 Customer satisfaction Example 6 Detecting credit card fraud Example 7 Inflation Conclusion2 Simple descriptions Introduction Data again Simple summary statistics Averages Dispersion Skewness Quantiles3 Collecting good data Incomplete data Incorrect data Error propagation Preprocessing Observational versus experimental data Experimental design Survey sampling Conclusion4 Probability The essence of chance Understanding probability The laws of chance Random variables and their distributions5 Estimation and inference Point estimation Which estimate is best Interval estimation Testing Decision theory So where are we now 6 Statistical models and methods Statistical models putting the blocks together Statistical methods statistics in action Statistical graphics Conclusion7 Statistical computing Statistics changes its spotsFurther readingEndnoteIndex hide spoiler

This is not a practical book, but rather a short description of statistics, from its worth to its methods And I struggle to conceive of how it could have been better written OK, the penultimate chapter is essentially just a slightly staccato series of mini introductions to various aspects of stats too involved to cover in greater detail, but up to that point the book is engaging, concise, and witty a real breath of fresh air.I may not know much about stats now than I did when I started reading speaking purely personally, not for every potential reader , but I do know one thing David J Hand can write a book.

This book does what it s supposed to Give a gentle introduction to topics in statistics and probability theory, culminating in a high level description of statistical methods these days associated with the field of machine learning But pretty much everything is explained just in a couple sentences, with examples rather than the theoretical underpinnings So don t expect to understand why things work the way they work or become a well versed practitioner after this book Rather see it as an overview, a pointer to topics to be read about in detail In other books.