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Economic Statistics - Comparison Table
Top Customer Reviews
Top Customer Reviews: The Art of ...
An author, the veteran statistician, has done the glorious work transmits, by means of this book, some concepts and subtleties of statistics and statistical reasoning. In the prose that is clear, friendly, authoritative and accessible, drives a reader by means of some technicians of statistical analysis, comprising a diverse pitfalls and abuse that can easily the a lot of plague. A glossary in an end of a book contains a lot of definitions of varied of some terms have used in a book as well as mathematical formulas of sure quantities, partorisca these interested.
This book could be lovely immense like the text of reference partorisca the course of formal university statistician. But also it can be enjoyed for enthusiasts of statistician/of the mathematician interested the one who is looking for friendly, explanations any mathematicians so that it is often a lot counterintuitive concepts.
This book could be lovely immense like the text of reference partorisca the course of formal university statistician. But also it can be enjoyed for enthusiasts of statistician/of the mathematician interested the one who is looking for friendly, explanations any mathematicians so that it is often a lot counterintuitive concepts.
Top Customer Reviews: Accelerate: The ...
One impressive tarpaulin, this book distills years of the toil and the analysis that continuous grow tendency in our industry. A book clearly tip some capacities that push big interpreters partorisca achieve magnitude.
With a quantity of data and present of the findings am not sure calms could do him more thrilling. Some authors are too much notch, but because of a density of a material can be bit it dry. There are whole chapters outlining some rigorous methods have used. While intellectually that it interest, it was harder that take by means of. A content is fantastic and as it does not leave this calm stop to choose on this book.
Loves hard die to back on best practices or to help your crew is result stronger then this book is for you.
With a quantity of data and present of the findings am not sure calms could do him more thrilling. Some authors are too much notch, but because of a density of a material can be bit it dry. There are whole chapters outlining some rigorous methods have used. While intellectually that it interest, it was harder that take by means of. A content is fantastic and as it does not leave this calm stop to choose on this book.
Loves hard die to back on best practices or to help your crew is result stronger then this book is for you.
If calm at present is doing in Netflix, Google, or Amazon in engineering of product this book could not resupply a lot of idea. But partorisca a rest of knots these shows of book in the scientific way a need of organisation of the steps partorisca take to accelerate his digital start and obtain a capacity to remain appropriate in a new digital economy.
A clear, concise, and methodical look in that differentiates big action of low action. If has opinions in those impact these attributes, then be poised partorisca examine one of then reinforce or burst these opinions.
Sad Jez. I have read each calm book so only is involved with. This in spite of have to that say that I am disappointed. Really I am looking for some hard evidence partorisca sustain some claims have done in the annual reports of the puppet, but this reserves only looks partorisca offer more claims. Where it is some hard numbers that truncate come from the development has based reduces risk?
Sees claim with which claim, but die very small to in fact sustain yours argues.
Am rooting partorisca you and your work. Not To Take me bad, thinks TBD is a right way to go. So only I have not seen any statistical evidence partorisca sustain concealed. I am expecting partorisca see more investigations in this subject punctual.
Please maintain on a work adds!
Sees claim with which claim, but die very small to in fact sustain yours argues.
Am rooting partorisca you and your work. Not To Take me bad, thinks TBD is a right way to go. So only I have not seen any statistical evidence partorisca sustain concealed. I am expecting partorisca see more investigations in this subject punctual.
Please maintain on a work adds!
Top Customer Reviews: The Book of Why: ...
Excellent introduction the causality. Has all has learnt that "the correlation is not causation" and Pearl explains reason this mantra short a risk partorisca launch a creature was with a bath-water. The calm big data give you correlation; the big data and the give causal form give you much more. A book is no-technical (any equation!) But act dipped more technical so that they want to undermine deeper. So only four stars because Pearl tends partorisca augment his own function while touching down a work of external entity.
Any BS, enormous clarity, entertainment partorisca read. I think Dr. Pearl Could say that the words and the narratives are not given of sufficient prominence in forecasting methodologies, some modern world-wide when be enamoured enough with 'dated, as it confesses also to be. This book is called epistemological -the-arms, the classical in a field of studios of realities. A lot of examples, practical joint for scientists of data and forecasters.
Effect and sympathetic cause we better critical thinkers. Less susceptible to bogus the claims and we maintain grounded in realities.
Surprisingly simple concepts with deep implications in some easy-to-the way read - an of some better books there is not reading never!
Absolutely lovely reading, some parts is class of hard to interpret directly without leading knowledge but totally the value that dips endeavours partorisca read.
Well it corrects
The reading has finalised 40 like this far
Top Customer Reviews: Weapons of Math ...
Cathy Or'Neil written with clarity and expertise. It distills an information around an invasion of algorithms to citizen' bolt in the more understandable way. His examples vivify the visit of a reader of a moral, social, and psychological implications of the intrusion of the Big data to our lives-- is taking the work, when be pointed partorisca subprime ready, when be estimated, etc. Some subjects are real and present. It offers some wise solutions that confidence on improving the lives of the people more than winning money irrespective of a side the society. Also it explains in of the clear terms because a lot of algorithms are bad and some are good--this has to that do with constant updating of new data.
A book of entity. It is directed in a harm that the blind applications of algorithms can do the society, the perspectives of occupation and taxes of incarceration. A escience' for behind the algorithms can be at all more than guesswork instantiated like this of the mathematical formulas. The sound asks the measure of the accountability partorisca some algorithms of harms can cause is timely and pertinent. But his worry that the algorithms are closing some poor to poor districts, and one a lot-was to the his own comfortable precincts, looks overdrawn. But his main conclusions am very done. 'I different fields have concepts very different that constitutes evidence, the one who elements of a need to argue to be 'tried', and when the quantities of evidence have accrued to persuasive querella.' My coolness to some roots partorisca reserve that it feels that ossia so only any mine causes, although it can be the worthy a, and can be one would have to that take up.
An excellent addition to a bookshelf of any that tries to maintain up with advances in the artificial intelligence and our addiction have augmented on automation in human test.
The worries of Cathy are ethical and apply to the plot of some systems 'dumb' old, as it has SEATED partorisca value. But HAVE the systems are increasingly 'black boxes '' doing decisions that life to change that can not be defied.
One adds read. They are Cathy with Alert of Google. A listened lovely of the voice.
The worries of Cathy are ethical and apply to the plot of some systems 'dumb' old, as it has SEATED partorisca value. But HAVE the systems are increasingly 'black boxes '' doing decisions that life to change that can not be defied.
One adds read. They are Cathy with Alert of Google. A listened lovely of the voice.
The superficial tests easily can cause collateral harm. The algorithms are tools that can and evolves quite quickly, be of feedback one of some main factors inside a developer of process. An author thinks that would have to that have more transparency the external entrance reason the collateral harms create additional questions to solve and spend his own costs that any, to somewhere ought to assume in an economy of data.
Pound a lot informative. It develops a subject of in reliance in of the statistics that can be entirely invalid. So only reason is numbers he no the fact well. Ossia The very serious question in our system of the education where expects student tests to resupply results of confidence.
I think that that a book was well, but tended to run out of steam. It thinks some needs of author to flush was more subject versus revising more chances of alike subjects. So only you result the little repetitive. But, you are the good book and the good bed this in spite of. It recommends it like this thought cause read.
As any with the fund of the mathematician and that has experienced only models that the injustice could be during one 2007-08 crises crediticia, had grown tired of an obsession of data. The mathematical models are so only like this very like this of the suppositions have dipped in them. Cathy Or'Neil' the book has renewed my interest in mathematicians and die. I give hope that the mathematical models can be used for good purposes, to help people, and level a field to touch. While the measure is static, the models can be dynamic, as it shows. I recommend Arms of Destruction of Mathematics for any interested in of the data, @that @the @modeling mathematical and algorithmic, and a measure of results, particularly people those who are in an intersection of these fields and impact entrepreneurship or social innovation.
Writing very good.
Takes a hype of big data.
Takes a hype of big data.
A lot Basic bed in Big Data for a layman. A bit repetitive but still the good bed
Really very written and has researched. He illuminates to the plot of worries thinks that a lot of people have in an age of data and offer really obliging the evidence on to the equal that can the to us fix.
Top Customer Reviews: The Data Detective: ...
I find it that it interests that some last few pages of this book summarize some challenges keys to facts and present die. Partorisca Be achieved, has to be interesting and inspire curiosity in a reader partorisca learn more. An excellent point, but looks partorisca condemn to to the books likes him to him-him these partorisca be compendiums of interesting histories in a @@@subject manually (Malcom Gladwell is the master of a form, and comes like any surprise to see Gladwell praise partorisca Harford laws) more than the analysis detailed of a subject.
A lot in an alcohol of “Quite a lot of” podcast. A mate to “Be Wrong”.
Felt more common and less “mathy” that has expected.
Very Done!!
Felt more common and less “mathy” that has expected.
Very Done!!
Is not postponed for a word tatistics' this is an entertaining and informative reserve which is also humourous and easy reading.
Lot is die but very few ideas? Rid adds to learn like this to manage better
Darrell Huff rid classical, Like the Lie with Statistics, warn any to take misled for statistics. In this book, Tim Harford says like this to see a Truth with statistics. It gives ten principles of thumb to think has informed roughly numbers. But a real reason to read a book is for everything of some histories Harford gave to illustrate each principle. It is like some more utmost swipes of a BBC the radio show there is hosted for years.
Here is to surround it simple of some ten principles:
1. When Considering new information, pay attention to that chairs . Your emotions can influence you to refuse attentive statistician to to that does not like and to embrace of the dud statistician to that likes
2. Sometimes your personal experience (the view of eye of a worm) the conflicts with the bird is-seen of eye statistic. For example, a metre can be only half full in meso during a day but has packed every time trace (during now of haste). Both help of perspectives comprises a truth.
3. Mark sure comprises that it is has counted. When Counting grain, a definition of the subjects of grain.
4. It looks for information that can dip it statistic to context, like a tendency, some stairs, or to the equal that compares to other situations.
5. Search to learn where a statistics has come from/come from (the backstory) – and the one who another data could be disappeared to obscurity.
6. Ask the one who the fault of a data, and our conclusions differ has been comprised.
7. It asks hard questions in algorithms and some big datasets concealed his pipe, that recognises that without the intelligent transparency can not be trusted.
8. It pays more attention to a bedrock of official statistician – and some sometimes heroic statisticians those who protect it.
9. Look Under a surface of any beautiful graph or map. It does not leave a beauty mislead you.
10. Maintain an open alcohol, that asks like this could be deceived and if some facts have changed.
This ten sound of tips to bore, but Harford the histories are not . The majority of his show a power of useful statistician. So that Harford said: 'the Good statistics is not to smoke and mirrors; in fact, we help to see more clearly. The good statistics is like the telescope for an astronomer, it microscope for the bacteriologist, or a X-ray for the radiologist.'
Here is to surround it simple of some ten principles:
1. When Considering new information, pay attention to that chairs . Your emotions can influence you to refuse attentive statistician to to that does not like and to embrace of the dud statistician to that likes
2. Sometimes your personal experience (the view of eye of a worm) the conflicts with the bird is-seen of eye statistic. For example, a metre can be only half full in meso during a day but has packed every time trace (during now of haste). Both help of perspectives comprises a truth.
3. Mark sure comprises that it is has counted. When Counting grain, a definition of the subjects of grain.
4. It looks for information that can dip it statistic to context, like a tendency, some stairs, or to the equal that compares to other situations.
5. Search to learn where a statistics has come from/come from (the backstory) – and the one who another data could be disappeared to obscurity.
6. Ask the one who the fault of a data, and our conclusions differ has been comprised.
7. It asks hard questions in algorithms and some big datasets concealed his pipe, that recognises that without the intelligent transparency can not be trusted.
8. It pays more attention to a bedrock of official statistician – and some sometimes heroic statisticians those who protect it.
9. Look Under a surface of any beautiful graph or map. It does not leave a beauty mislead you.
10. Maintain an open alcohol, that asks like this could be deceived and if some facts have changed.
This ten sound of tips to bore, but Harford the histories are not . The majority of his show a power of useful statistician. So that Harford said: 'the Good statistics is not to smoke and mirrors; in fact, we help to see more clearly. The good statistics is like the telescope for an astronomer, it microscope for the bacteriologist, or a X-ray for the radiologist.'
There is enjoyed this book of an extreme to the another, and has learnt so much. They are neither the statistician neither an economist. They are the person of police the one who is curious roughly create that that the big touch is gone in a real world. This book resembles has been aimed well in me.
Some people of helps of the detective of Data thinks by means of an information is looking for to accuse. A point is to take to a truth to all the cost of a source of information. Understand for chapter, Tim Harford explains an importance of things likes to recognise that put you your own emotions to consumption of data, moving your view of information, when being curious in a backstory of data, demanding same transparency of sources of the big data and that comprises like the fault of data. There is other 'principles,' also. They are all like this practical likes some have listed, and his all requires the sure quantity of self-the awareness the master to help swim in the riada of a world of information.
Esgulate 3: it averts Premature Enumeration' was a chapter that has spoken mine a strong plus. It describes that and reason adapting in the definitions is of entity. I will admit cringed on and on again to the equal that have @to @give that time I inadvertently injustice of title has repeated. During this chapter, my alcohol was boggled in that I has thinks that has comprised but that clearly had not thought roughly properly. A Rule 3 examples, likes all some another in a book, is offered in the succinct, involving way. They direct in some differences among headlines and of the realities.
Has learnt in a Principle 3 understand that has comprised bad:
- a point of this big 2014 Oxfam studios of disparities,
- as several definitions of a 'boy' affect some infant mortality rates in some the EUA and elsewhere,
- as the determinate studio that touches the video games have caused aggressive behaviour, and
- all some ways the 'died of gun' could be clear-cut.
Is that last a that have really does to think in that I has taken definitions for has admitted. Have also does to think roughly like a race for the headline can hide that it is of entity in the studio and can head to some wrong actions. Taking Rule 3 to the heart roughly is that it recognises that the words usually are that confuses things, any number. Need of definitions to match.
Of course, this was so only my favourite principle. There is new another in a Detective of Data. I have read this book on a governs / to understand the day to really the absorb, and has had to resist an impulse to read more seating it. Freely I admit that I have been Tim Harford the defender never has read of the his first book A Undercover Economist. They are always state entertained for Harford way comunicacional, if it is in his another reservation, in his column of Financial Time, likes presenter for Enough or in his new Cautionary podcast of Histories. I seat it likes him everything is learnt roughly communication in all these helps of venues do A Detective of Data like this easy to read, informative and entertaining. It is it drives it adds to accuse an information-rich world around everything.
Some people of helps of the detective of Data thinks by means of an information is looking for to accuse. A point is to take to a truth to all the cost of a source of information. Understand for chapter, Tim Harford explains an importance of things likes to recognise that put you your own emotions to consumption of data, moving your view of information, when being curious in a backstory of data, demanding same transparency of sources of the big data and that comprises like the fault of data. There is other 'principles,' also. They are all like this practical likes some have listed, and his all requires the sure quantity of self-the awareness the master to help swim in the riada of a world of information.
Esgulate 3: it averts Premature Enumeration' was a chapter that has spoken mine a strong plus. It describes that and reason adapting in the definitions is of entity. I will admit cringed on and on again to the equal that have @to @give that time I inadvertently injustice of title has repeated. During this chapter, my alcohol was boggled in that I has thinks that has comprised but that clearly had not thought roughly properly. A Rule 3 examples, likes all some another in a book, is offered in the succinct, involving way. They direct in some differences among headlines and of the realities.
Has learnt in a Principle 3 understand that has comprised bad:
- a point of this big 2014 Oxfam studios of disparities,
- as several definitions of a 'boy' affect some infant mortality rates in some the EUA and elsewhere,
- as the determinate studio that touches the video games have caused aggressive behaviour, and
- all some ways the 'died of gun' could be clear-cut.
Is that last a that have really does to think in that I has taken definitions for has admitted. Have also does to think roughly like a race for the headline can hide that it is of entity in the studio and can head to some wrong actions. Taking Rule 3 to the heart roughly is that it recognises that the words usually are that confuses things, any number. Need of definitions to match.
Of course, this was so only my favourite principle. There is new another in a Detective of Data. I have read this book on a governs / to understand the day to really the absorb, and has had to resist an impulse to read more seating it. Freely I admit that I have been Tim Harford the defender never has read of the his first book A Undercover Economist. They are always state entertained for Harford way comunicacional, if it is in his another reservation, in his column of Financial Time, likes presenter for Enough or in his new Cautionary podcast of Histories. I seat it likes him everything is learnt roughly communication in all these helps of venues do A Detective of Data like this easy to read, informative and entertaining. It is it drives it adds to accuse an information-rich world around everything.
An interesting book that present 10 principles on like this to do senses of statistics.
1. It would owe that learn to take and remark our emotional reaction to the claim, more than accepting or refusing he because of like this do to feel.
2. We would owe that look for ways to combine a 'bird' eye statistical perspective with a worm' seen of eye of personal experience.
3. We would owe that look in any focus in a data is dice, and ask comprise that it is for the be really has described.
Can go in but takings a point . A book resupplies 10 useful principles still simple for better sympathetic statistics. I want like each chapter has looked an example that at the beginning look looked to be inapplicable, but Tim Harford would aim likes you the example has said shows a particular statistical principle. Each class of example can think of, and each type of history can think of, is looked in this book. Usually, ossia the turn -was for me but Tim the work adds of somehow that connects that second looks was-example of @@subject to a concrete principle/takeaway of a chapter. It was able to learn so much of this book by means of Tim storytelling.
An only reason has not given this book 5 star is that has had some chapters where an interesting history or the interesting example has not gone there or an author so only gone back to the yours typical kinda the professor of statistician bored. Ossia Ironic reason Tim underlines that an only way to change any one is alcohol is to take them curious, and an only way to take them curious is to do that it is presenting entertaining or appeal. Well, it has left so only it has said that in my opinion there was sure chapters where to senses like Tim kinda slacked on applying of his own joint. Chapters where any involved in the statisticians would love, but a outsider taste would find him dull and uninteresting. These portions of a book were little and far among this in spite of so that yeah this book was still the book adds to read.
1. It would owe that learn to take and remark our emotional reaction to the claim, more than accepting or refusing he because of like this do to feel.
2. We would owe that look for ways to combine a 'bird' eye statistical perspective with a worm' seen of eye of personal experience.
3. We would owe that look in any focus in a data is dice, and ask comprise that it is for the be really has described.
Can go in but takings a point . A book resupplies 10 useful principles still simple for better sympathetic statistics. I want like each chapter has looked an example that at the beginning look looked to be inapplicable, but Tim Harford would aim likes you the example has said shows a particular statistical principle. Each class of example can think of, and each type of history can think of, is looked in this book. Usually, ossia the turn -was for me but Tim the work adds of somehow that connects that second looks was-example of @@subject to a concrete principle/takeaway of a chapter. It was able to learn so much of this book by means of Tim storytelling.
An only reason has not given this book 5 star is that has had some chapters where an interesting history or the interesting example has not gone there or an author so only gone back to the yours typical kinda the professor of statistician bored. Ossia Ironic reason Tim underlines that an only way to change any one is alcohol is to take them curious, and an only way to take them curious is to do that it is presenting entertaining or appeal. Well, it has left so only it has said that in my opinion there was sure chapters where to senses like Tim kinda slacked on applying of his own joint. Chapters where any involved in the statisticians would love, but a outsider taste would find him dull and uninteresting. These portions of a book were little and far among this in spite of so that yeah this book was still the book adds to read.
Likes any the one who has done the career in some fields of engineering, quality and statistician, has found more than my just action of both bad statistics and cynical dismissal likewise of thorough analysis. As I enjoy to read pieces and reservation ossia both positive in some good that the statistical analysis can do, but also frank in a pitfalls this comes from/comes from our own models of behaviour.
The detective of data 🕵️♂️ stresses an importance to spend our whole selves the any one view of data - a random viewing of a info graphic or one in-scientific revised depth, more analysis or our own endeavours. Each forms of links of chapter he in a canal to read and responsible analyses, the class of cast of control of elements to agree so much look in information - sew that it can be easy to forget when we are any in the view of eye of a ‘worm' in a weeds of a data, or so much has invested emotionally that the objectivity is difficult.
Is easy to find has touched describes that objectivity of difficult mark - political, social and subjects of human legislations, environmental subjects, economic justice, and like this on. But as where, when, like this rich, and numerous other criteria of your birth and ganadería, spend the together of suppositions and normative structures that will bias each meeting with new information. But to the equal that see in some examples, these predispositions do not require to govern our lives, can open our alcohols the new information, prpers leaves to be wrong and to regulate the new ways to think more than staunching claim our rightness like that ‘hill to die to'.
Is everything biased, all active preconceptions in things, all have material is bad roughly, all have limitations ... It is that in a face of new data roughly and a world-wide that @@subject.
And this reservation any one gives some responses - but help with some tools to drive on trips it the discovery.
The detective of data 🕵️♂️ stresses an importance to spend our whole selves the any one view of data - a random viewing of a info graphic or one in-scientific revised depth, more analysis or our own endeavours. Each forms of links of chapter he in a canal to read and responsible analyses, the class of cast of control of elements to agree so much look in information - sew that it can be easy to forget when we are any in the view of eye of a ‘worm' in a weeds of a data, or so much has invested emotionally that the objectivity is difficult.
Is easy to find has touched describes that objectivity of difficult mark - political, social and subjects of human legislations, environmental subjects, economic justice, and like this on. But as where, when, like this rich, and numerous other criteria of your birth and ganadería, spend the together of suppositions and normative structures that will bias each meeting with new information. But to the equal that see in some examples, these predispositions do not require to govern our lives, can open our alcohols the new information, prpers leaves to be wrong and to regulate the new ways to think more than staunching claim our rightness like that ‘hill to die to'.
Is everything biased, all active preconceptions in things, all have material is bad roughly, all have limitations ... It is that in a face of new data roughly and a world-wide that @@subject.
And this reservation any one gives some responses - but help with some tools to drive on trips it the discovery.
I amour Tim Harford storytelling and his thoughtful capacity to inspire my curiosity in subjects that typically creates does not have any interest in. One that grows that it comprises that it study and statistical this is to shout is gone in some mean comunicacionales are likely no it look directed the really appreciate this book and some histories, coupled with joint, as to like this to take by means of a weeds and find the bit of clarity and confidence. Súper Interesting, excellent and surprisingly amused to read in statistics of all the things!
Insightful And useful for all the world—of a scientist of data to the user of light Internet. Some 10 principles could be summed on amiably in of the commentaries down (and in an Epilogue) but the really take some effects and consequences of some principles, would have to read a book in plenary. 10/10 recommendation for me.
(My education and funds of the career is in of the Data Analytics.)
(My education and funds of the career is in of the Data Analytics.)
Top Customer Reviews: The Model Thinker: ...
Like the Analyst of professional of Business Intelligence (BIA) ossia a perfect no-book of fiction partorisca my office. The aggregation of data, informing, and analysis in my work of day. And constantly we are trying determine the one who a better correlation, the representation or the model is partorisca analysis an ours available data.
Scott And. The page begins was that it speaks roughly REASON. Ossia An often spent piece for big of any business work. A reason. Reason something? Reason in concern him? Because utilisation X on And? And like this on...
In this chance the page is able the eloquently concurr that in today of world-wide of 'big data' require to be more conscious of the like the options are available our partorisca analysis. It is no longer appropriate to use a model the analysis the question. Instead we require to leverage some fines-approximation of model and look in of the complex subjects, questions or phenomena (as it calls him) of a lot of corners. Like this world-wide has taken more complex, our data has taken main and more granulate; the bad requires partorisca look in him of a lot of different perspectives.
Seriously Detailed
are in the crew of BIA is, much more senior that I, and have conversed like this with them roughly some concepts of core in the book of the page and all adapted in a thing. It is comprehensible! If there is the model that imports very represented in a Thinker of Model would be impacted. Page the work adds partorisca touch on 30+ models and giving three concrete things partorisca each:
1) A definition and general use
2) A desglosa mathematical real
3) A real-life, pertinent example partorisca use a model.
A better part partorisca read any portion of the selection of epic of the page of the models is easily some examples. Of priest of health the criminal form the alimentary quality to a stock market to growth of population; we are partorisca give applicable phases partorisca comprise some nuances of the each model and reason is a better election . The more there are tonnes of small tidbits and fare that is amused partorisca share in of the parties of cocktails (or yes are, in of the conversations of random elevator) in here!
Creativity
has a thing that surprised really in a Thinker of the model and ossia the emphasis of the page on creativity. As any the one who has the BA in of the Communications, Creation & of Marketing, and used partorisca do in an industry of magazine, has been surprised partorisca find that my current Analytical career has had similar bases he in creativity. Reflector to the statements of the page and my work there is give that it is well. When we Program/code, develop visualisations or infer results of data; we are looking in something and creatively manipulating it. Perhaps this explains like this has been it of a Manager of Art to the Analyst in a lifetime.
In general
Ossia the book that will be partorisca purchase for my shelf of office. I have gone back already to the mine eARC copies multiple time partorisca look things on and partorisca continue learning some models. It is not the coverage of work of calm book probably partorisca cover any time dates. But some first 50 pages of introduction and concepts are glorious reading and very lovely in mandate. With which that can jump you around to some models are interested more in, or is looking for a right solution partorisca data crunching, read a intros to the each chapter partorisca determine yes could have situation of yours applicable use. I know that A Thinker of Model is already state chosen up for any mainstream University and University as I required them textbook and certainly can see reason. In some reservations obtain a knowledge of lovely hundreds of years of calculations and analyzation. If calm at present laws like the Data or Business Analyst, has the desire to learn to use big data, is the programmer or so only he friki that amours graphs; A Thinker of Model is likely to fill the void, any included know existed, partorisca give you more models, examples and calculations that calm never needs.
Please note: I have received a eARC of this book of an editor has seen NetGalley. Ossia One sincere and unbiased description.
Scott And. The page begins was that it speaks roughly REASON. Ossia An often spent piece for big of any business work. A reason. Reason something? Reason in concern him? Because utilisation X on And? And like this on...
In this chance the page is able the eloquently concurr that in today of world-wide of 'big data' require to be more conscious of the like the options are available our partorisca analysis. It is no longer appropriate to use a model the analysis the question. Instead we require to leverage some fines-approximation of model and look in of the complex subjects, questions or phenomena (as it calls him) of a lot of corners. Like this world-wide has taken more complex, our data has taken main and more granulate; the bad requires partorisca look in him of a lot of different perspectives.
Seriously Detailed
are in the crew of BIA is, much more senior that I, and have conversed like this with them roughly some concepts of core in the book of the page and all adapted in a thing. It is comprehensible! If there is the model that imports very represented in a Thinker of Model would be impacted. Page the work adds partorisca touch on 30+ models and giving three concrete things partorisca each:
1) A definition and general use
2) A desglosa mathematical real
3) A real-life, pertinent example partorisca use a model.
A better part partorisca read any portion of the selection of epic of the page of the models is easily some examples. Of priest of health the criminal form the alimentary quality to a stock market to growth of population; we are partorisca give applicable phases partorisca comprise some nuances of the each model and reason is a better election . The more there are tonnes of small tidbits and fare that is amused partorisca share in of the parties of cocktails (or yes are, in of the conversations of random elevator) in here!
Creativity
has a thing that surprised really in a Thinker of the model and ossia the emphasis of the page on creativity. As any the one who has the BA in of the Communications, Creation & of Marketing, and used partorisca do in an industry of magazine, has been surprised partorisca find that my current Analytical career has had similar bases he in creativity. Reflector to the statements of the page and my work there is give that it is well. When we Program/code, develop visualisations or infer results of data; we are looking in something and creatively manipulating it. Perhaps this explains like this has been it of a Manager of Art to the Analyst in a lifetime.
In general
Ossia the book that will be partorisca purchase for my shelf of office. I have gone back already to the mine eARC copies multiple time partorisca look things on and partorisca continue learning some models. It is not the coverage of work of calm book probably partorisca cover any time dates. But some first 50 pages of introduction and concepts are glorious reading and very lovely in mandate. With which that can jump you around to some models are interested more in, or is looking for a right solution partorisca data crunching, read a intros to the each chapter partorisca determine yes could have situation of yours applicable use. I know that A Thinker of Model is already state chosen up for any mainstream University and University as I required them textbook and certainly can see reason. In some reservations obtain a knowledge of lovely hundreds of years of calculations and analyzation. If calm at present laws like the Data or Business Analyst, has the desire to learn to use big data, is the programmer or so only he friki that amours graphs; A Thinker of Model is likely to fill the void, any included know existed, partorisca give you more models, examples and calculations that calm never needs.
Please note: I have received a eARC of this book of an editor has seen NetGalley. Ossia One sincere and unbiased description.
Top Customer Reviews: Introducing ...
Formed: Kindle Easy Edition partorisca read, gave the good fund in a statistician that was my less mathematician preferred zone like the student.
Formed: Kindle Edition A very big level overview of statistics. Better the description that knows book that to the learning likes the pound.
Top Customer Reviews: How to Lie with ...
Formed: Paperback this book has been around partorisca years but remains appropriate. The absurd statistics is everywhere, esp recently of an arrival of alternative facts. Unfortunately, a receiver of this book, my daughter, has not having still to give is value .
Formed: Kindle that Shines of Edition! Included this in spite of writes on done 50 years, all the concepts are still valid.
A lot easy to read. Calm much better poised partorisca read some ads after reading this book, the meaning will not be able the yours lie much longer.
With sure essult tried'.
A lot easy to read. Calm much better poised partorisca read some ads after reading this book, the meaning will not be able the yours lie much longer.
With sure essult tried'.
Formed: Paperback statistical of use of the People all a time to 'final querellas. It Darrel Huff Explains in this timeless classical is that the statistical can have the habit partorisca deceive like this a lot likes anything more. A reader will learn partorisca question all especially when the people quote statistics partorisca win argues.
Formed: Paperback This in spite of dated, some rests of book like pertinent as it was done roughly sixty years in a statistics of ways is MISused partorisca distort reality, if deliberately or no. While one can see an improvement in an use of statistics of then, an a lot of pitfalls described in a book still applies today.
Formed: Kindle the edition A lot of writing-on a power of numbers has exerted inappropriately (for casualidades or for creation). If you are not deep to mathematicians in general and statistician especially, ossia the must has read. Partorisca me, no really learn anything new, but is still satisfied state with my compraventa.
Formed: Paperback statistical VERY BASIC that the majority of people learns in of the colegialas. From time to time an author ameno on something those interest, but in general has found any present anything new. It was also originally published in 50s, as has a outdated feels his. Any I same volume halfway by means of before have prendido to read.
Formed: Paperback This book has been underlined and scarred with notes. Some the complete tears were partorisca a price. It is partorisca launch among any sale of book. I will not be using Amazon for books never again!!!!.
Formed: Paperback Charming book. Some examples are quell'has bitten dated but still pertinent. Honradamente, A reference the American elections and of the world-wide chances that predate me so only direct me partorisca look them up; which has done a subject and a book even more involving. Probably one of my favourite books on like this partorisca do with statistics.
Formed: Paperback A must read partorisca any with the alcohol partorisca question I in the first place read this book done thirty years like a student of Engineering because it was recommended by the professor; it is particularly valid today in an age of 'alternative facts'.
Formed: Paperback A must read partorisca any the one who has not asked never that there is like this statistical and metrics flight around that all look partorisca contradict each one which so another. Writing a lot well, youll fly by means of this book.
Top Customer Reviews: The Misbehavior of ...
I have wanted to you love/ it That. A masterpiece of an inventor of Fractals. A classical. Highly recommended.
No the plot of mathematics but the very good presentation of an idea.
Very interesting bed of a founder of a field. Transmissions your perspective in a hypothesis of effective phase.
Adds read!! Shjould Be compulsory in all the funds 101 run
Has to that read partorisca any student of financial phases
Extremely rids written although it takes calm by means of a world of the financial turbulence that common felt uses and an approximation of @@the @modeling alternative mathematician that use fractals. Although a book has shouted more the questions that answered, resupplies interesting perspective in some limitations of Black-Scholes, Optimisation of Bad Variance, a Hypothesis of Effective Phase and a Theory of Random walk. Mandelbrot Shoots down an idea of normality in some distributions of prizes of house and financial advantage on two particularly pesky characteristic of financial phases: leptokurtosis (fat rows) and correlation of serial (memory). This book is adapted more partorisca readers with the level of diplomado that comprises of finance.
This book was easy to read and writing for the brilliant man, for this reason so only gives comes from it.
A question with a book is is tentativa partorisca apply the science that explains principles and natural growth of character to a financial industry. An access is was!
A movement of some looks to stage partorisca try so only that special and seperate is animal and character. We are not like this easy to comprise and predict like model of growth of the fern and this fractal science of Mandlebrot is the failure is tentativa partorisca do like this.
Are happy failure! Help partorisca celebrate me like this something only and the place averts of a world-wide around me, something with the touch of God my life.
Has the few useful things that a book says this in spite of, a duquel if a fact that volatility begets volatility or simply partorisca expect a prize of movement of days partorisca be equivalent in measure, although no in direction, to a movement of prize of leading days.
Another very useful part is his condemnation of a 'theorem of centrical limit' or a curve of bell in your ad, he the work adds of uncovering an error of following such the philosophy.
He Take a time partorisca read a calm book will enjoy it included although an application of fractals to the finance is the piece .
A question with a book is is tentativa partorisca apply the science that explains principles and natural growth of character to a financial industry. An access is was!
A movement of some looks to stage partorisca try so only that special and seperate is animal and character. We are not like this easy to comprise and predict like model of growth of the fern and this fractal science of Mandlebrot is the failure is tentativa partorisca do like this.
Are happy failure! Help partorisca celebrate me like this something only and the place averts of a world-wide around me, something with the touch of God my life.
Has the few useful things that a book says this in spite of, a duquel if a fact that volatility begets volatility or simply partorisca expect a prize of movement of days partorisca be equivalent in measure, although no in direction, to a movement of prize of leading days.
Another very useful part is his condemnation of a 'theorem of centrical limit' or a curve of bell in your ad, he the work adds of uncovering an error of following such the philosophy.
He Take a time partorisca read a calm book will enjoy it included although an application of fractals to the finance is the piece .
Has loved that. A masterpiece of an inventor of Fractals. A classical. Highly recommended.
Top Customer Reviews: Lean Analytics: Use ...
LEAN ANALYTICS Does the very good work partorisca explain and exampling LEAN metrics. But calm would be to deceive yes calms thought it so only that.
Likes Founder & CEO of one 8-the old year startup (), has read, and king-read, everything of a better startup and technology business books. Ossia A better book that have right now, and one the majority of applicable to my subject.
Some things that dipped this book averts is:
sends the message of calm. Too much startup the writing extends the nervous tension that finds bad partorisca a brain. These propagations of book have considered partorisca think and confidence.
Some ideas in a book are easily mapped to the attainable process. Which is quite the trick, reason there are a lot of different situations that the different readers will be in. He this sound familiarised?: On some last 8 years, am spent a inordinate quantity to time to try remap others' processes to iLiv' particular challenges; usually with just quite sucedidos to maintain me goes down it a wrong street for far also long.
Although any one directly procedural, a writing is pragmatic. It is roughly like this to think followed reason to do, and that to do after with which conceal, and like this on, with flexibility and suitability.
A work is creative, in a way that any one operates that it exposes to essence and relate them to some participants is creative.
Likes Founder & CEO of one 8-the old year startup (), has read, and king-read, everything of a better startup and technology business books. Ossia A better book that have right now, and one the majority of applicable to my subject.
Some things that dipped this book averts is:
sends the message of calm. Too much startup the writing extends the nervous tension that finds bad partorisca a brain. These propagations of book have considered partorisca think and confidence.
Some ideas in a book are easily mapped to the attainable process. Which is quite the trick, reason there are a lot of different situations that the different readers will be in. He this sound familiarised?: On some last 8 years, am spent a inordinate quantity to time to try remap others' processes to iLiv' particular challenges; usually with just quite sucedidos to maintain me goes down it a wrong street for far also long.
Although any one directly procedural, a writing is pragmatic. It is roughly like this to think followed reason to do, and that to do after with which conceal, and like this on, with flexibility and suitability.
A work is creative, in a way that any one operates that it exposes to essence and relate them to some participants is creative.
“In confidence of Goddess, all another has to that spend die.” This book is all has related to this date. Better analytics the book has seen
Excellent source for sympathetic some have measured tones in the company and reason requires to be comprised for continuous improvement.
This book is one drives essential if a reader is planning in inaugural his own startup, already have the startup or is planning the his scale startup to the subject big.
Personally really enjoyed this book; these types are not of the amateur. I m using his pours every day and action with my crew. It Likes him to him the contractor and analytical lover this reserves done to plot of sense.
I desire has had this book 18 month ago when you ship in mine startup travesía! Has everything of some signals underlined of Eric Risata' rid A Lean Startup, Ash Maurya pound A Lean Cloth and Dave McClure pirate metrics all gone to an easily readable and highly actionable guidebook. Now they are behind to a corporate world and am requiring my whole department to read Lean Analytics before they begin any project. All the world, of an interior of marketing to the CEO/President, will be to take the hard copy of a book hardly is printed. It is really that well!
LEAN ANALYTICS Does the very good work partorisca explain and exampling LEAN metrics. But calm would be to deceive yes calms thought it so only that.
Likes Founder & CEO of one 8-the old year startup (), has read, and king-read, everything of a better startup and technology business books. Ossia A better book that have right now, and one the majority of applicable to my subject.
Some things that dipped this book averts is:
sends the message of calm. Too much startup the writing extends the nervous tension that finds bad partorisca a brain. These propagations of book have considered partorisca think and confidence.
Some ideas in a book are easily mapped to the attainable process. Which is quite the trick, reason there are a lot of different situations that the different readers will be in. He this sound familiarised?: On some last 8 years, am spent a inordinate quantity to time to try remap others' processes to iLiv' particular challenges; usually with just quite sucedidos to maintain me goes down it a wrong street for far also long.
Although any one directly procedural, a writing is pragmatic. It is roughly like this to think followed reason to do, and that to do after with which concealed, and like this on, with flexibility and suitability.
A work is creative, in a way that any one operates that it exposes to essence and relate them to some participants is creative.
Likes Founder & CEO of one 8-the old year startup (), has read, and king-read, everything of a better startup and technology business books. Ossia A better book that have right now, and one the majority of applicable to my subject.
Some things that dipped this book averts is:
sends the message of calm. Too much startup the writing extends the nervous tension that finds bad partorisca a brain. These propagations of book have considered partorisca think and confidence.
Some ideas in a book are easily mapped to the attainable process. Which is quite the trick, reason there are a lot of different situations that the different readers will be in. He this sound familiarised?: On some last 8 years, am spent a inordinate quantity to time to try remap others' processes to iLiv' particular challenges; usually with just quite sucedidos to maintain me goes down it a wrong street for far also long.
Although any one directly procedural, a writing is pragmatic. It is roughly like this to think followed reason to do, and that to do after with which concealed, and like this on, with flexibility and suitability.
A work is creative, in a way that any one operates that it exposes to essence and relate them to some participants is creative.
Adds read for a contractor, analyst of data or scientist of data.
I desire has had this book 18 month ago when it has shipped in mine startup travesía! Has everything of some signals underlined of Eric Risata' rid A Lean Startup, Ash Maurya pound A Lean Cloth and Dave McClure pirate metrics all gone to an easily readable and highly actionable guidebook. Now they are behind to a corporate world and am requiring my whole department to read Lean Analytics before they begin any project. All the world, of an interior of marketing to the CEO/President, will be to take the hard copy of a book hardly is printed. It is really that well!
A Clash has the call of brilliant song hould I stay or has to that go'. It has not been that some papers exactly inform to but is the question more startup the contractors probably ask in some point. Regularly I have fulfilled startups the one who are rasgados among 'those strikes your boss against to wall of brick' and 'doing all beat calm to run by means of the wall of brick' to use two popular analogies. Lean Startup And now Sustain Analytics can resupply a response to direct a law to balance to give all poden without pursuing the stray cause.
Running Lean for Ash Maurya is a prime minister in an O'Reilly Sustains Startup Serious. It is brilliant. Lean Analytics For Alistair Croll and Benjamin Yoskovitz is a second in a series. It is equally brilliant. It is comprehensible and would have to that change business that calm in yours startup. Eric Ride written the wonderful Prologue to Sustain Analytics that describes like this emotional besides a Lean Startup stickers of bumper and submerging deep to some details of accountings of innovation like this averting a perils of vanity metrics. It concludes that a book is the 'drives for all the practitioners the one who look for new sources of growth'. I think that this soyeasuring that is critical to achieve sucedido in the new business adventure' - this book will help you to imagine out of that that would be necessary to be you measured to help you to ask joined the majority of questions of entities and take clear responses quickly. It is critically of entity that in the first place can measure your progress and communicate that with your inner and external crew.
A Preface explains that Lean Startup the helps identify some more have risked part of your business plan, then finds ways to reduce these risks in the fast cycle, iterative to learn. The majority of his ideas boils down to a sentence: it does not sell that ; that it can sell. And this means to imagine out of that the people want to buy. Lean Analytics Objective as to imagine out of yours business model and your phase of growth. It explains like this to find a a Metric That @@Subject your right now, and to the equal that to draw the line in a sand like six when to step in a gas and when to close unexpectedly in some brakes.
Those who a book is stops :
A preface recognises that some tools of details of the book and technician that was first applied in of the web applications of consumer, that adds that now they are applied when being to the a lot of wider audience and that some authors have spoken to tiny familiarised subjects, global companies, fledging startups, and charities, all that is applying lean analytical approximations .
Thinks Lean Analytics can be read in isolation but armed with the knowledge of books likes Some Drive of Contractor to Development of Client, A Lean Startup; and of course running Lean, thinks that that this book will dip calm in the frame of alcohol that has to take action you. A book is broken to four parts. It leaves 1 summarises (brilliantly) all some blockades of edifice of Lean Startup to comprise some aforesaid books to prepare calm for a prójimo 3 parts.
I amour a structure of this book. Calm give you so only quite and then moves on to another zone but that returns again to build in this knowledge. For a record, Leaves II looks in six clock of the business models and some five phases that each one which startup raisin for him so that it discovers a right product and a phase of better aim. When you Are fact , will know the one who business is in, the one who the phases are in, and that to do on. It leaves III, looks in that is normal. After reading this part, will take some abonos baselines for tones metrics and learn like this to dip your own aims. Finally, it leaves IV calms points like this to apply Lean Analytics yours organisation that does a point that quotes-driven approaches applies of more than just new companies.
Some looks of book in six clock of the business models:
- eCommerce chapters 8 and 22;
- SaaS chapters 9 and 23;
- chapters of Free Mobile Application 10 and 24;
- chapters of Place of the Half comunicacionales 11 and 25;
- Chapters of the user of content has generated 12 and 26; and finally
- Two Sided chapters of Warehouses 13 and 27.
One the common denominator is on-line, and is operating in an of these six zones, this book is the Must Read - these are all relatively the new zones and this reserve done a contributo excellent successful sympathetic in this half.
If you are not operating in these zones but have the strong interest in Lean Startup and wants to move to a next level, has abundance to feed for has thought resupplied by this book. Understand 29 extracted the company has directed B2B software startups. A metrics to measure here is directed in some phases of the your funnel of Sales with some real nuggets consultor in that to measure and the clock was paralizaciones e.g. Facilitated of commitment of client; integration and costs of support; and measuring use of client of the your APIs like the strategy for retention of client.
Is commercialising The physical product I probably read a Startup the manual of the owner for Steve Spaces and Bob Dorf first.
Which I really liked in a book
Understand 2 'To the equal that to Maintain Bookmark' converse in those mark he abonos metric and is a better discussion of vanity metrics to comprise abundance of reference to Donald Rumsfeld, Secretary of the EUA leading of Defence. This is to follow for the introduction adds the Main metrics, Segments, Cohorts and A/B Testing.
Understand 5 presents the Lean Analytics frame with five diverse phases: Empathy, Stickiness, Virality, Imposiciones and Stairs, that each one which startup raisin stops. A model comprises one 'gating' metrics this indicates that it is now of movement to a next phase. Some rodeos of chapter a four primary Lean Startup Marcos:
- running the line Sustains Lean
- Lean Startup for Eric Ride
- Dave McClure Pirate Metrics
- Pyramid of Growth of Ellis of Are
And on Page 53 presents them visually in an imagines together with a Lean Analytics frame like this adding glorious clarity to a discussion. A frame is referenced in a rest of a book to leave visualisation of user and flows of business models by means of some systems of a subject.
Some Chapters in eCommerce is particularly illuminating for me there is like this limited direct experience in this zone.
Finally, hardly can think that has has not mentioned still some Examples of Chances have used in a book. They are interesting and a lot of writings and used to illustrate points keys - Startup Analytics the lessons have Learnt.
In general, Sustains Analytics is the fantastic book and to good sure value for money!
Running Lean for Ash Maurya is a prime minister in an O'Reilly Sustains Startup Serious. It is brilliant. Lean Analytics For Alistair Croll and Benjamin Yoskovitz is a second in a series. It is equally brilliant. It is comprehensible and would have to that change business that calm in yours startup. Eric Ride written the wonderful Prologue to Sustain Analytics that describes like this emotional besides a Lean Startup stickers of bumper and submerging deep to some details of accountings of innovation like this averting a perils of vanity metrics. It concludes that a book is the 'drives for all the practitioners the one who look for new sources of growth'. I think that this soyeasuring that is critical to achieve sucedido in the new business adventure' - this book will help you to imagine out of that that would be necessary to be you measured to help you to ask joined the majority of questions of entities and take clear responses quickly. It is critically of entity that in the first place can measure your progress and communicate that with your inner and external crew.
A Preface explains that Lean Startup the helps identify some more have risked part of your business plan, then finds ways to reduce these risks in the fast cycle, iterative to learn. The majority of his ideas boils down to a sentence: it does not sell that ; that it can sell. And this means to imagine out of that the people want to buy. Lean Analytics Objective as to imagine out of yours business model and your phase of growth. It explains like this to find a a Metric That @@Subject your right now, and to the equal that to draw the line in a sand like six when to step in a gas and when to close unexpectedly in some brakes.
Those who a book is stops :
A preface recognises that some tools of details of the book and technician that was first applied in of the web applications of consumer, that adds that now they are applied when being to the a lot of wider audience and that some authors have spoken to tiny familiarised subjects, global companies, fledging startups, and charities, all that is applying lean analytical approximations .
Thinks Lean Analytics can be read in isolation but armed with the knowledge of books likes Some Drive of Contractor to Development of Client, A Lean Startup; and of course running Lean, thinks that that this book will dip calm in the frame of alcohol that has to take action you. A book is broken to four parts. It leaves 1 summarises (brilliantly) all some blockades of edifice of Lean Startup to comprise some aforesaid books to prepare calm for a prójimo 3 parts.
I amour a structure of this book. Calm give you so only quite and then moves on to another zone but that returns again to build in this knowledge. For a record, Leaves II looks in six clock of the business models and some five phases that each one which startup raisin for him so that it discovers a right product and a phase of better aim. When you Are fact , will know the one who business is in, the one who the phases are in, and that to do on. It leaves III, looks in that is normal. After reading this part, will take some abonos baselines for tones metrics and learn like this to dip your own aims. Finally, it leaves IV calms points like this to apply Lean Analytics yours organisation that does a point that quotes-driven approaches applies of more than just new companies.
Some looks of book in six clock of the business models:
- eCommerce chapters 8 and 22;
- SaaS chapters 9 and 23;
- chapters of Free Mobile Application 10 and 24;
- chapters of Place of the Half comunicacionales 11 and 25;
- Chapters of the user of content has generated 12 and 26; and finally
- Two Sided chapters of Warehouses 13 and 27.
One the common denominator is on-line, and is operating in an of these six zones, this book is the Must Read - these are all relatively the new zones and this reserve done a contributo excellent successful sympathetic in this half.
If you are not operating in these zones but have the strong interest in Lean Startup and wants to move to a next level, has abundance to feed for has thought resupplied by this book. Understand 29 extracted the company has directed B2B software startups. A metrics to measure here is directed in some phases of the your funnel of Sales with some real nuggets consultor in that to measure and the clock was paralizaciones e.g. Facilitated of commitment of client; integration and costs of support; and measuring use of client of the your APIs like the strategy for retention of client.
Is commercialising The physical product I probably read a Startup the manual of the owner for Steve Spaces and Bob Dorf first.
Which I really liked in a book
Understand 2 'To the equal that to Maintain Bookmark' converse in those mark he abonos metric and is a better discussion of vanity metrics to comprise abundance of reference to Donald Rumsfeld, Secretary of the EUA leading of Defence. This is to follow for the introduction adds the Main metrics, Segments, Cohorts and A/B Testing.
Understand 5 presents the Lean Analytics frame with five diverse phases: Empathy, Stickiness, Virality, Imposiciones and Stairs, that each one which startup raisin stops. A model comprises one 'gating' metrics this indicates that it is now of movement to a next phase. Some rodeos of chapter a four primary Lean Startup Marcos:
- running the line Sustains Lean
- Lean Startup for Eric Ride
- Dave McClure Pirate Metrics
- Pyramid of Growth of Ellis of Are
And on Page 53 presents them visually in an imagines together with a Lean Analytics frame like this adding glorious clarity to a discussion. A frame is referenced in a rest of a book to leave visualisation of user and flows of business models by means of some systems of a subject.
Some Chapters in eCommerce is particularly illuminating for me there is like this limited direct experience in this zone.
Finally, hardly can think that has has not mentioned still some Examples of Chances have used in a book. They are interesting and a lot of writings and used to illustrate points keys - Startup Analytics the lessons have Learnt.
In general, Sustains Analytics is the fantastic book and to good sure value for money!