Apropos of nothing… Sam Sheridan is a tough guy. He’s competed in MMA, worked as a forest firefighter, a sailor, and spent 6-months in Antarctica. But Apropos of nothing… Sam Sheridan is a tough guy. He’s competed in MMA, worked as a forest firefighter, a sailor, and spent 6-months in Antarctica. But after the birth of his son, he becomes pre-occupied with the question of ‘what if?’. What if there is a massive natural disaster, civil war, an EMP strike, or the zombie apocalypse? The preppers called this TEOTWAWKI (The end of the world as we know it), and Sheridan decides to get ready. Each chapter is Sheridan musing on some aspect of TEOTWAWKI – is his house earthquake-proof? could he steal a car? could he kill an animal? could he fight with a knife? would he be fit enough? could he work as a field medic? could he psychologically cope? In each chapter he mixes his experiences meeting with an expert, and doing the training, with some general background and pop science. Early on, particularly, it felt like a bunch of Men’s Health articles. But as the book went on it got better. He told a bit of himself, and also maintained optimism and balance. Even though he is prepping, he doesn’t come across as a whackjob prepper. He trains with guns, but it’s not a book about gun rights, or thinly veiled racial panic. He emphasises the importance of community and dignity, and finishes with a look at how well communities often function in the face of disaster. He includes a bit of a breakdown of the misinformation which occurred around Hurricane Katrina, and how well the community actually functioned. Probably a good one for my martial arts/ self-defence buddies. ...more
OK. So, this is a beast which is neither fish nor fowl. It’s somewhere between popular science and a coursebook.
Many model thinking is so hot right noOK. So, this is a beast which is neither fish nor fowl. It’s somewhere between popular science and a coursebook.
Many model thinking is so hot right now (see Munger, Parish etc etc.). This book kinda fits into that genre.
On the other hand, it is also a much more serious treatment of how to apply analytic models, and it’s almost a textbook for his course: https://www.coursera.org/learn/model-...
That said, the book doesn’t get into the nitty gritty of how to use each approach. That’s not necessarily a problem – learning how to use an analytic technique ‘for realz’ takes time.
What I liked: I’m a researcher/ data analyst. My stats skills are pretty solid, but are very much grounded in a psychology background (almost everything I do belongs to the family of regression/ structural equation models). What this did is blow things wide open and offer a lot of other possible views.
The book uses a variety of examples to make it’s point.
He also makes the argument of multiple models as offering complementary views and tools (a sort of pluralist approach).
My favourite parts: The illustrations of using multiple models to offer complementary explanations of the same phenomenon, e.g. the Global Financial Crisis, the Cuban missile crisis, and rising social inequality.
Minor objections: Page is clearly a strong advocate for combining models (many model thinking). The book could maybe do with a little more discussion on the practicalities of combining models, and also potential errors/ drawbacks.
Given Page talks about causality a bit, I think it could have done with its own chapter. Selfishly, I’d love to see his take on Judea Pearl’s work, and how he compares and contrasts it to other approaches.
TBH, my biggest objection is that some of the images and equations came through with very poor image quality on the kindle. That problem is not unique to this book, but it’s still a bit annoying.
All that said, it was good enough for me to enrol in the Coursera version....more
A drug smuggler’s amazing story about life inside a Bolivian prison. I didn’t bother for fact checking, but a brilliant read. Lots of great stuff aboutA drug smuggler’s amazing story about life inside a Bolivian prison. I didn’t bother for fact checking, but a brilliant read. Lots of great stuff about the economy, day-today life and adventures inside the prison. Also, lots of cocaine. ...more
Very much about mixing easy balance and movement cues into your day to day life. Balance on one foot while burgling teeth, build in a few stretches firVery much about mixing easy balance and movement cues into your day to day life. Balance on one foot while burgling teeth, build in a few stretches first thing in morning, last thing at night, that sort of thing. Not every single suggestion stuck with me, but feel like I got good value. Was reasonably unique in just how clearly structured it was, although I still used a reminder system as well. ...more
This is Gonzales’ free-ranging book on survival. Per the title – who lives, who dies, and why. It’s a mix of pop-psychology, pop-science, case studiesThis is Gonzales’ free-ranging book on survival. Per the title – who lives, who dies, and why. It’s a mix of pop-psychology, pop-science, case studies, biography/autobiography and philosophy. The pop psychology: people make bad decisions because of their mental models, their brains (especially inappropriate emotional cues), and bad habits of attention. The pop-science: disasters are a natural consequence of complex systems. Case studies: a really varied assortment of examples of when people survive (and don’t survive) all sorts of events. Biography/ autobiography: how his father survived being shot down in WWII, and how it impacted Gonzales’ life. Philosophy: what it means to live a present life.
I liked it. It was a fun mix. I should note that It got a bit too literary (flowery) in spots. I don’t think many of his theories can be easily falsified, so it sits somewhere between science journalism, story-telling, and pseudo-science. That’s not an overwhelming negative, the book wasn’t meant as a period reviewed article, but it’s a point to note.
That said, this is the second time I’ve read the book, and I think it holds up well. ...more
If you are a science or stats geek, or frustrated with the replication crisis in across various disciplines, or even a philosophy/ cognitive science bIf you are a science or stats geek, or frustrated with the replication crisis in across various disciplines, or even a philosophy/ cognitive science boffin, this book is highly recommended.
Judea Pearl is a heavy heavy hitter. He was a big deal in Computing and Artificial Intelligence (at the forefront of Bayesian networks, which are central to mobile phone signal technology), before he made the leap to questions of causal inference.
The knock on Pearl has been his writing – it’s so hard to get through, I suspect his work didn’t get serious leverage until better communicators (Greenland, Hernan, Robins etc.) came to the party. I attempted his monolithic ‘Causality: Models, Reasoning and Inference’ but was defeated by it.
This book is the fix. Someone needs to buy Dana Mackenzie a shiny new car, or at least a carton of beer, for his work in helping Pearl get his ideas across in an accessible fashion.
Some of the main complaints from other reviewers are that either: 1) it’s too technical; or 2) it’s not how-to enough. So, yes IT IS A BIT TECHNICAL. And yes, THIS IS NOT A HOW-TO.
1) IT IS A BIT TECHNICAL. I think whether or not it is too technical depends on where you are at – I take this stuff seriously, and I expected a bit of pain, so I think he simplified just enough (I describe my background below, if it helps you orient yourself to the review). The book is not at all mathematical, although it is brutally logical in spots.
2) THIS IS NOT A HOW-TO. It’s a big picture overview (I suggest a few how-to’s below).
The third major criticism of Pearl is about where he sits into other approaches to causality, particularly those in economics (and to a lesser extent machine learning) – I don’t know enough about this yet but I’ll add an appendix to my review as I build sufficient background.
The book is about what Pearl calls the Causal Revolution. It’s about scientists (especially in social science and epidemiology) taking the question of when you can (and cannot) infer causality seriously. The book gives an excellent review of the evolution of ideas in statistical and science about causality, and lays down a serious challenge to the mantras ‘no causality in observational studies’ and ‘correlation does not imply causality’. At the very least, Pearl helps make explicit when these mantras make sense — Pearl makes extensive use of the debate over smoking and lung cancer to illustrate his point. As Hernan and Robins point out in their book, how many of us need evidence from an RCT to confidently deduce that putting your hand on a hot stove causes burning?
(As an analyst/ research fellow working in social science I’m often struck by how we make a statement in our limitations along the lines of ‘this study is observational, we cannot infer causality’ and then make an implicitly causal recommendation like ‘support mothers with mental health issues’, ‘don’t smoke’, ‘eat less fatty food’ or ‘school attendance is good for your grades’ (incidentally, these are all likely sound recommendations and it’s really our tradition of denying causality as a matter of course that’s the issue.))
Pearl is the originator of the Directed Acyclic Graph (the DAG), that is causal graphs, and a formal logic of causality. He is a relentless evangelist for these ideas. He has converted me to his religion (Judea-ism?) but it’s important to recognise that he offers a particular perspective on the issue of causal inference. There are other views out there (particularly in economics) that differ on some issues with Pearl (if/ when I come up with a good summary of their issues with Pearl I will add it as an appendix to the review).
Pearl does a good potted history of statistics, science and causal inference, with a lot of love for Sewell-Wright and his guinea pigs. He devotes a chapter to an overview of the Bayes rule and it’s applications. Including the Monty Hall problem, which unfortunately still confuses me (I don’t blame Pearl for this).
The book itself makes extensive use of causal diagrams to help build the reader’s intuition. This covers off a more systematic approach to selecting which covariates an analyst should (and shouldn’t) adjust for, and the language of common causes and common effects. He also gives an accessible review of Simpson’s and Berkson’s paradoxes.
Using causal diagrams offers an accessible tool for communicating instrumental variable and Mendelian randomisation analyses.
Pearl thinks about causal inference in mind-bogglingly abstract terms. The weakness is that (until now), it’s been left to others to help communicate his ideas. The strength is the sheer power and imaginativeness of his approach. Pearl offers up several extensions of his work that I was less aware of from the work of others. In particular, he is a strong advocate of the front-door adjustment method (basically the piece-wise synthesis of causal models from separate studies).
Another ‘innovation’ from the book is Pearl’s way of thinking about the problem of ‘transportability’ (I’d always called it generalisation) – how do we apply results from one context, population or setting to another? Again, Pearl uses the causal diagram to communicate his ideas.
As behoves his background in AI and Cognitive Science, the book is also rich with speculation about intelligence and consciousness (human and artificial). I found all this entertaining and thought-provoking. He contrasts his approach to the Big Data approach, but also proposes a marriage between the approaches.
I’ll give the caveat – I didn’t come to this book cold. I’ve worked in research for about 8 years with a bachelor’s degree in psychology and a Masters in Applied Stats. Over the last year I’ve been to several short courses on this issue, and I’ve done a lot of reading on the topic. Despite that, I’d recommend this as a good place to start (possibly in conjunction with working through all the examples and quizzes on DAGitty.net, and Miguel Hernan’s excellent HarvardX course).
It is not a “how to” for applying causal models to a specific analysis. Depending on the reader’s specific needs and interests, there are a few good resources out there but I quite liked Bill Shipley’s Cause and Correlation in Biology. The DAGitty web package is also excellent. Tyler VanderWeele’s book. OR, cross over to the dark side and look into econometrics.
******
Critiques of Pearl (work-in-progress)
The criticism of Pearl — He’s partisan. In presenting his history of causality, he emphasises his own contribution, and de-emphasises the contribution of others.
This is true. This doesn’t diminish his approach or the utility of his methods, but if you want balance, you’ll need to shop around for other points of view.
A few other reviews note that causality in social sciences is maybe not the new thing that Pearl argues it is. It’s an interesting area – economists have been on the causality bandwagon for years – but the other social and behavioural sciences are replete with examples of poor choice of control variables reflecting a lack of causal reasoning (and the explicit denial of it).
Pearl reviews examples where we would accept causality has been proven without his formal causal logic (e.g. smoking and lung cancer, John Snow’s cholera studies). What he communicates well is that, without a clear causal logic, it quickly got messy.
From where I’m sitting the causal diagrams offer a tool of communicating with other branches of the social sciences, and also offer a useful means for interrogating the assumptions behind economic causal models.
Don Rubin (the king of missing data and potential outcomes), disagrees on the value of causal diagrams. I’ve only seen the argument well articulated from the Pearl camp, and I’m not sure if this is purely a matter of ‘who owns causality’ or if there are worthwhile lessons in here for practicing scientists/ analysts (to be continued...).
There is also a back and forth series of letters in the International Journal of Epidemiology between Pearl on the one hand and Nancy Krieger/ George Davey-Smith on the other hand. The latter camp are arguing for a more pluralistic approach, and point to some instances where using DAGs and DAGitty has produced some implausible models. This intrigues me. I’ll add some notes on this later.
Solid, basic financial advice. Some good tips (think of personal finance like weights - start small, incremental improvements). Maybe a bit too AmericSolid, basic financial advice. Some good tips (think of personal finance like weights - start small, incremental improvements). Maybe a bit too American for an Australian audience.
____ Update 24/02/18 Upgraded this from 3 to 4 stars.
Incredibly basic, but I did get quite a bit of personal benefit from implementing these:
RULE #1: Strive to Save 10 to 20 Percent of Your Income Save 10-20% or more. Steps: 1) Monitor your spending (in detail for 3 months) 2) Confront your spending 3) Refine your expenses over time 4) Create a plan 5) Be sure to leave room for fun
Set money aside for an emergency
Set up an automatic savings plan.
Start by lifting 1-pound weights.
Side-note: I love all the negative reviews because so many Americans think any form of social security is a Ponzi scheme. Can you say fuckwit on Goodreads?...more
Excellent. A nicely told catalogue of cognitive errors. He doesn’t let the science get in the way of a good story, which I think was the right choice.Excellent. A nicely told catalogue of cognitive errors. He doesn’t let the science get in the way of a good story, which I think was the right choice. Recommending it broadly....more
Another successful book club joint! First, you have to admire the audacity of the author - I'm going to summarise as much as I can of human history (anAnother successful book club joint! First, you have to admire the audacity of the author - I'm going to summarise as much as I can of human history (and pre-history) in 500 pages, and I'm going to do it with a background in ornithology and linguistics! Then, you have to admire that he somehow successfully drew it all together. The book is dense with information, all there to bolster his argument that geography matters a ton (or as summarised at book club, life is about shit dumb luck). I really liked the study of Polynesia as a microcosm of his theory. If there were crtitiques it'd be that it gets a bit repetitive by the end, and that he's so focussed on his theory he maybe doesn't consider other aspects of humanity (in that sense Sapiens makes an excellent companion volume). Definitely worth a future re-read and note-taking....more
Crime novel set in Tibet. Lead character a Chinese political prisoner in a prison otherwise full of Tibetan prisoners (mostly for religious conscienceCrime novel set in Tibet. Lead character a Chinese political prisoner in a prison otherwise full of Tibetan prisoners (mostly for religious conscience purposes it would seem). Very heavily trades on the themes of the Chinese occupation of Tibet. What struck me about this was the 'world building'. In some ways it reminded me of a science fiction novel, where the world was painstakingly described. The author had an incredible amount to tell, but I found that the context loomed so large that it overtook the crime story. I also found the characterisations a little limp - if you were Chinese you were a variation on chain-smoking party-apparatchik baddy, if you were a Tibetan you were a variation on inscrutable mystic. No guessing where the author's sympathies lie. Recent pieces in The Economist on Chinese occupation of Western China reinforce this characterisation, but some exploration of the downsides of the Tibetan theocracy might have lent a bit more suspense (i.e. if we could entertain the possibility that Tibetan mystics weren't all goodies all the time)....more
The author comes across as a charming toff, a skilled raconteur, and maybe a bit of a fibber (he's at pains throughout to make sure we know his recollThe author comes across as a charming toff, a skilled raconteur, and maybe a bit of a fibber (he's at pains throughout to make sure we know his recollections are uncertain).
It's a biography, delivered in a series of anecdotes, and it's a sympathetic view of current affairs in the second half of the 20th century.
The bits that got to me were his outrage at how former Nazis were absorbed into the German intelligence system after WWII because of paranoia over communism, and his sympathetic way of describing the various rebels and rascals he meets along his way. ...more
A brutal and honest discussion of addiction from an actor-comedian-writer. He certainly doesn’t seem to be trying too hard to convince us what a good gA brutal and honest discussion of addiction from an actor-comedian-writer. He certainly doesn’t seem to be trying too hard to convince us what a good guy he is (quite the opposite). Some of the drug use, and the behaviour that went with it was deeply disturbing. Some of the humour is outstanding. My only criticisms: 1) Meanders a bit in the middle chapters. 2) Psychologically, I felt drained at the end. ...more
The book is a mix of home-spun philosophy, aphorisms, pop-psychology, and some nice sweary quote-able observations. You can imagine this as someone’s The book is a mix of home-spun philosophy, aphorisms, pop-psychology, and some nice sweary quote-able observations. You can imagine this as someone’s really well-edited blog, although it has an overall thesis: “Whether or not you realize it, you are always choosing what to give a fuck about.” Aim: turn your problems into slightly better problems. “If you find yourself consistently giving too many fucks about trivial stuff that bothers you… chances are you don’t have much going on in your life to give a legitimate fuck about” When there are no problems, your mind invents some. “…It follows that finding something important and meaningful in your life is perhaps the most important use of your time and energy… Because if you don’t find that meaningful something, your fucks will be given over to meaningless and frivolous causes.” “Don’t hope for a life without problems. There is no such thing. Instead, hope for a life full of good problems.” You have a limited number of fucks to give while you are alive, so choose wisely. Good values 1) Radical responsibility. 2) Uncertainty 3) Failure 4) Rejection. 5) Contemplation of one’s own mortality.
What I liked, it was well-argued, it was sweary and funny, and a Iot of what he said resonated with me really well. What I didn’t like. He referenced a bit of science here and there, but this is basically a manifesto cobbled together from anecdote, logic, and other people’s ideas. Nothing at all wrong with that, but it felt like it was missing something for me. Unfortunately, I can't say what. ...more
Can't remember how long ago I read this, but the simple lessons in it (or my weak recollections) have stuck with me.Can't remember how long ago I read this, but the simple lessons in it (or my weak recollections) have stuck with me....more
Another bookclub joint. I’m still not sure what to make of it. Bits were incredibly well-observed (particularly around the church), but I struggled withAnother bookclub joint. I’m still not sure what to make of it. Bits were incredibly well-observed (particularly around the church), but I struggled with a lot of it. Less the lack of cohesiveness (I took the book as a love letter to Ireland, ancestry, poetry), more the author’s overplayed pseudo-Irish voice. That said: 1) Still got a good conversation going at bookclub. I still love the hive-mind effect of getting people together. 2) I liked his point about ‘singing along until you find your own voice’. ...more
Loading...
