The Best Textbooks on Every Subject
lesswrong.com
lesswrong.com
For one, you often start a field with a specific book. If you pour a lot of time into that book, you often feel more attached to it. Then, when trying to evaluate another textbook, it's hard (impossible?) to go through that same experience and understand if you would have had an easier time with the material. There are definitely some obvious cases, but it isn't always.
Second, sometimes people just have different learning styles and have a preference for them. Landau and Lifshitz has a reputation for being very hard (but rewarding!) to parse, and that is easily a showstopper for some people. Other books might only have relatively easy exercises (Axler's Linear Algebra Done Right, for example), which can help you gain a lot of confidence, while others might have many very difficult or very tedious problems. Some might have solutions to problems, some might not.
Really, I think the best we can do is put a list of "top books" for each subject rather than the "best textbooks" for each subject.
But these lists do help in decreasing the search space when trying to find material to learn a new subject.
https://www.theguardian.com/education/2017/mar/13/teachers-n...
I used to believe this nonsense myself.
look, sure this broad idea about learning styles may be false, but you cannot I think disagree that a book may be more or less suitable for someone depending on their particular strengths and weaknesses, and that OP's point.
Different ways of learning different subjects will be more or less effective for different students. All the studies linked in the article show that students perform best when presented new information in multiple representations, so they can then focus on the style that is working best for them in that case.
My main point being: maybe learning styles don't exist in the traditional sense, but external factors (ADD being just one of them) can lead to another type of "learning styles" that manifest in effectively the same way.
It doesn't mean that people won't learn differentially. It just means that specific model is wrong.
Feel free to replace his or her shorthand “learning style” with something like “personal preference, past experience, and miscellaneous psychological factors”.
Whether or not the published work about “learning styles” was solid science with meaningful conclusions for guiding formal pedagogy, it is all but impossible to argue that different students don’t respond better to different books.
In any case, whether learning styles are a myth or not, learning preferences about teaching styles are very real, and what works for someone to keep them engaged can bore someone else to tears and drive them off a course.
The brain needs to be progressively challenged just like any muscle and achieving a state of mild confusion while consuming new information does just that.
Exactly what I noticed about other types of comparisons. People conflate familiarity with quality. That's why loyalty wars, like vim vs emacs, verilog vs vhdl, python vs ruby, etc, have significant components of subjectivity. It's not a purely objective debate about vim vs emacs, rather a debate between a comfortable user of vim and a comfortable user of emacs. That's why when someone decides to learn the rival tool properly before bashing it, they end up not being too radical in their views.
Of course, as your second point gets to; a book that's generally considered "best" won't always be the best for a specific reader and their circumstance.
Has anyone had a professor that tried something like this?
I hated math when I was in secondary-school, but loved computers so did a computer science course which was heavy-ish math in its final year.
Passed that course and now am in a pretty decent programming role, but I feel like my maths is just built on such a shaky foundation that I maybe could improve my programming and problem solving if I solidified the base.
Is there any one text book I could get which would teach me up to that level of Math?
I suspect no, because Math is so broad, but generally if I could get an entire pre-university schooling in Math I would be very happy.
You do need calculus for non-trivial statistics and even for some topics of discrete mathematics where continuous approximations are useful. For example Stirling's approximation [1] which if I recall well is on the first page of McKay's Information Theory, Inference, and Learning Algorithms.
I think that if we talk about more modern approaches for mathematics, logic, type theory and interactive theorem proving could be great. I've been toying with this idea for teaching a course, but I haven't found suitable materials.
[1] https://en.wikipedia.org/wiki/Stirling%27s_approximation
You don't have to read it cover to cover, but this is the book that will be very helpful in shaping the right perspective.
As a side note, a friend of mine gave it to me in high school. It was probably the book that influenced me the most mathematically. I ended up getting a PhD in math last year.
For example, the first dozen pages on Calculus have imparted a better understanding of the subject than all the indecipherable (if only due to sheer volume) tomes of Stewart. It was an invaluable boost.
I never liked math that much, but as a professional programmer I don't typically find that the programming I do requires any advanced math.
If your job needs math, learn that math. If your job doesn't need math, there's not a lot of point in learning it because you will forget it again due to non-use.
I don't remember any calculus for example, because I've never needed it since I've been out of school.
It is a great overview of calculus and linear algebra, leading up to PDE and chaos theory. It starts with the discrete models (kirchoff's law on graphs) and then moves on to continuous models as an approximation of the discrete case, which is quite neat.
What I found was that going through a proper high-school textbook was the best way to cover all the topics systematically and in a focused manner. If you can get your hands on some such books (such as a text for the International Baccalaureate Higher Mathematics or the UK Advanced Levels), that would be the ideal solution.
You can also look at Schaum's series at this level (search them on Amazon). Some useful books are Schaum's Basic Mathematics, Intermediate Algebra, Precalculus, and Calculus. These have the advantage that many problems are solved and the text is completely waffle-free. I myself enjoyed working through Schaum's Calculus whenever I had to brush-up my calculus skills in the university.
Yet another option is to go through the texts by "Art of Problem Solving" (https://artofproblemsolving.com/). From what I have seen so far, these are beautiful texts that stress on improving your problem solving skills along with acquiring technical knowledge. However, I haven't taught from these, so I can't vouch for how the learning experience with them will be like.
1/ Geometry and the Imagination. Yes, it's geometry. Yes, it's written in a somewhat older style. No, it doesn't do a lot of hand-holding. But if you can spend the time to really understand the dazzling intellectual fireworks going on there it will reward you with a very strong intuitive understanding of a lot of practical mathematics. The key goal of this book was to teach insight and it totally hits the mark.
2/ Contemporary Abstract Algebra by Gallian. This helped me learn more of the language of modern mathematics, so I could be more comfortable approaching recent developments in my field. It is an approachable, not-excessively-rigorous text and again, emphasizes intuition over deep rigor. Even if you don't really need abstract algebra, I'd recommend this book.
3/ Proofs From The Book. This is a brief survey of a selection of especially elegant and beautiful proofs. This is partly valuable for the immediate facts you'll learn-- I have surprised coworkers with a solution to a seemingly difficult problem that closely mirrors something in here more than once-- but is mostly about understanding mathematical standards of beauty and why proofs might be structured the way they are.
4/ TEA's problem solvers for whatever you actually need (calculus, etc). These books are just piles of worked out problems. Personally I found it useful to study several of the hard problems, understand the mechanics of solving them, and then go back to the easy ones and make sure I could work all the way through them without error. In my opinion, combining this practical and detail-oriented legwork with the above theoretical material helps avoid fooling yourself into thinking you can solve problems you really can't.
I'll caution that in math there is no substitute for hard work. Where in programming being lazy is often a virtue, learning math was something that I really had to grind through even when I was enjoying it. It's just a guess, but I suspect the same might be true for you; best to expect it.
I would definitely not recommend it for someone working on high school level math. If I had made an attempt at that in high school, being told it was something I should be capable of then, I probably would have totally given up on any ideas I had about being able to do math well.
If you look at a lot of reviews for math books, you'll find there is a major split between folks who, on one side, believe a math book should should be a sort of pure, elegant, perfect thing with barely anything in it but statements of definitions, theorems and proofs. It should be difficult above all. There should be no trace of how the contents within it came to be, just a pure presentation of some set of mathematical truths. The other side values pedagogy. The mathematical results in themselves are not considered sufficient on their own to be good teachers; instead, attention must be paid to the psychology of one's readers, and in consideration of it, the best route for making contact from the reader's knowledge to the author's must be taken. A typical trend is that the presentation includes context on why and how the results were developed.
I've seen a similar split in CS, and I can say at least here, that I haven't seen any correlation between those insisting on doing everything the hard/austere way and doing interesting/technically impressive work. That said, I haven't personally done anything particularly impressive in mathematics, so I'll refrain from making too strong a comment about the necessity of any particular pedagogical style in that realm.
But I would bet two things: 1) We lose many folks who could have become good mathematicians because they were freaked out by the sort of attitude and presentation making up the first half of the 'split' I describe above 2) It is probably significant that not all excellent mathematicians choose the trial by fire pedagogical approach in their own works.
Overall I agree that too much of mathematics is obfuscated. Whether that's because it makes the author sound smart or because excellent prose isn't a big timesaver for a reader who has to grapple with a complex proof anyway I don't know. Could be both.
But I will reiterate is what I said above: deeply understanding an unfamiliar result or method often is irreducibly hard work that simply must be ground through. That's no reason to make simple things needlessly hard but when it's time to work through something tricky, well, people should expect to spend some time on it. Importantly, they should not feel stupid or bad at math when they have to do so, which I think is probably the thing that loses us the most mathematics besides obfuscated intro calculus.
Just out of curiosity, what was the problem with Khan Academy? Was it the video format, the pace of explanations, or something else?
Thanks for the recommendations, obviously the title of your book appeals to me. I will check them out.
[1]https://www.amazon.com/Basic-Mathematics-Serge-Lang/dp/03879...
This concept map might also help situate you about which math concepts to review: https://minireference.com/static/tutorials/conceptmap.pdf and since you're a coder, you should also look into SymPy which is the best thing since sliced bread when you're learning math, see https://minireference.com/static/tutorials/sympy_tutorial.pd...
Also, +1 to other comments that recommend solving exercises/problems. It's very easy to fall into the trap of "I already know this" when reading math, so always good to try things out on your own and, literally, exercise those new knowledge pathways.
However, I think your faith that it's easy to find good recommendations by subject matter experts underestimates the difficulty of finding them in the mass of things on the internet. To take one example, I remember reading a post about two approaches to denotational semantics, along with recommendations about the best textbooks, but have never subsequently been able to find that link.
The books in the OP's list might not work for everyone, so you have to do your own searching, sorting and analysis. This is especially true if you are a self-learner and much more so if the subject you want to learn is math because in math you are the one who has to prove every one of your assertions and be as independent as possible.
tl; dr:
don't worry about the "expert opinion". Instead collect data, clean it, analyze it and the consume the parts you need. That way you avoid 'expertise' that comes bundled with traditionalisms, bureaucracy, calcified thinking and other undesirable bullshit.
You can't read Jackson if you haven't taken Griffiths or an equivalent! Jackson is a graduate textbook whereas Griffiths is undergraduate. And if you don't have a strong math background (knowing multivariate calculus and differential equations) neither of those are recommended.
I think the hard thing about lists like this is that it doesn't specify who it is best for. At least compare books on the same level...
I could take a stab at an actual list like this with better organization by recommending books for each course in the more or less standard undergraduate core physics curriculum, but I'm sure different professors would make different choices (and even for me, I know that my choices would be situation dependent). It's a hard problem, and it doesn't translate well to the very short summaries shown here.
I think most of us would recommend books that we used. Or adamantly say "stay away from this one!" Like you said, it isn't easy.
But there seem to be a few good options in each level, and usually only a few. I think the best thing to do would be to categorize them by level and say "Here's the most popular books, this is the one I recommend." It is impossible to be unbiased but I think that's about as close as you can expect to get.
[1] https://github.com/minireference/structure-api/blob/master/d...
An example: Classical Mechanics.
Goldstein is the de facto graduate text on the subject.
I haven't used Hand, but what I could get with the "Surprise Me" feature on Amazon, it looks like a Undergraduate text. I however used Marion and Thornton[0].
There also seems to be some misunderstanding in HOW to order it too. Like you have Mechanics in the beginning. What do you mean by that? The first round? ie: not Classical Mechanics (Junior year). If so, those books are typically a trifecta, containing: mechanics, E&M, some waves, and some modern. Those are typically Young or Halliday and Resnik.
You also separate electricity and magnetism into different sections, in the undergrad section. Why?
You have QM but don't have Griffiths? You have E&M but don't have Griffiths?
Why do you have Sakurai and don't specify which one?! If anything says "Modern" in the title it is probably a graduate book. I can't see inside that one but it is frequently bought with Jackson (E&M) and Goldstein, so I would take a stab at it being a graduate text.
[0] https://smile.amazon.com/Classical-Dynamics-Particles-System...
Intro Physics (Mechanics, E&M, waves, etc.):
* Six Ideas That Shaped Physics, by Tom Moore: Conservation laws first, and a nice conceptual approach (and can incorporate "modern physics" along the way).
* Matter and Interactions, by Chabay and Sherwood: Integrated VPython programming, and uses "true" relativistic mechanics right from the start (and quantum's built in, too).
* Physics for Scientists and Engineers, by Randall Knight: As close to a "traditional" intro book as you can get while still paying attention to physics education research. It's very good, though I feel like the latest edition has veered back a bit to a bit more traditional order, perhaps to make it smoother for old professors to switch.
Uncertanity/Error Analysis: (Essential for understanding experimental physics)
* An Introduction to Error Analysis, by John Taylor: Such a beautiful little book!
"Modern Physics": (Is a class whose content mostly ends before 1950 really "modern"?)
* Six Ideas That Shaped Physics (Units R and Q), by Tom Moore: A very nice first introduction to both special relativity and quantum physics. Might need some supplemental content if you have time for more advanced quantum/nuclear stuff.
[* Special Relativity, by Tom Helliwell: I learned out of this, and it was very good. I haven't taught out of it.]
[* Quantum Physics of Atoms, Molecules, Solids, Nuclei, and Particles, by Eisberg and Resnick: I learned out of this, but haven't taught out of it. Comprehensive.]
Intermediate Classical Dynamics: (I haven't taught this one!)
* ?Classical Mechanics, by John Taylor: I've heard very good things about this one.
[* Classical Dynamics of Particles and Systems, by Thornton and Marion: I learned out of it. It was fine.]
Intermediate Electromagnetism:
* Introduction to Electrodynamics, by David Griffiths: Truly excellent introduction to analysis of electric and magnetic fields using vector calculus and partial differential equations.
[* ?Classical Electromagnetic Radiation, by Heald and Marion: I learned out of this. Not my favorite book, but it did the job.]
Intermediate Quantum Mechanics:
* A Modern Approach to Quantum Mechanics, by John Townsend: Inspired by Sakurai's graduate text, Townsend starts by studying spin and Stern-Gerlach experiments in depth using Dirac bra-ket notation, and then progresses to time evolution and position space. The chapter on the path integral formulation is fun but optional, and there's good stuff on perturbation theory and scattering and some hints toward field theory. (This may work best if students had a strong "Modern Physics" course first that studied wavefunctions in some depth.)
[* Introduction to Quantum Mechanics, by David Griffiths: I haven't used this myself. An excellent quantum book with a more "traditional" organization, starting with wavefunctions and only later talking about Dirac notation and spin.]
Thermodynamics and Statistical Mechanics:
* An Introduction to Thermal Physics, by Daniel Schroeder: A fantastic, multi-pass blend of statistical mechanics and classical thermodynamics. It starts with basic classical definitions of thermal concepts, then introduces explicit state counting in medium-sized systems with the help of Excel, then discusses classical thermodynamics in depth, and finally goes into a full discussion Boltzmann factors and statmech.
* Fundamentals of Statistical and Thermal Physics, by Frederick Reif: This was (for me) the least bad of the books that I used to teach myself undergraduate statmech while I was in graduate school. (I foolishly arranged to avoid the class as an undergrad.)
More related to software, I have another rule: read the official documentation first before going somewhere else. Though often less polished than external books, it comes from the creator and it usually worth the effort.
When open source was getting rolling in the 90s I don't remember it being nearly so polished.
And at least there's some kind of acknowledged API now (even if the first class languages shift with the slightest breeze).
The official Postgres manual instantly comes to mind whenever I think about great documentation. There's just something about the way it's split up, and especially the typical length of a leaf page, that makes it absurdly helpful.
It's a joy.
Based on the Amazon reviews it seems like it might be the sort of book I'm looking for, I'll continue to check through those and for other reviews later.
The solution to your surprise will be a re-calibration of the expectations you have, not them magically becoming more like you :)
http://www.thinking.net/Systems_Thinking/OverviewSTarticle.p...
Kind of gets at what I'm wanting to convey to people. Often (especially with technical people) we focus on a narrow thing. I have a problem, I will fix it. We don't examine the environment in which the problem exists to actually understand its causes and impacts. Maybe my problem is actually not a problem for the organization, it may actually be a benefit. Example:
A friend works in aircraft maintenance. They do something called "bonded repair", using adhesives to apply patches rather than other techniques. It's remarkably effective. But when the patch is later removed during a big maintenance effort, the technicians have to remove the remaining adhesives. They've been given a plastic (consumable) tool, it's slow and breaks but they're cheap and ultimately effective. The technicians look at the "problem" (too slow, breaks) and go find a metal tool. It's faster, doesn't break, they can get the whole area cleared by lunch. Great!
No! The metal tool introduces scratches. Scratches become failure points in the future so they have to be repaired before the aircraft is released. The local optimum introduced a 2-week delay in releasing every aircraft while damage detection and repair was conducted. And potentially worse failures in the future if the scratches aren't detected.
A systems thinker would examine the whole of the operation before solving their local problem. This is the thing I want to convey to my colleagues.
For developers, the locally (to you or maybe even your team) optimal decision to use language X may seem great. But then it turns out you aren't the one maintaining it in 5 years. Your choice to use Rust in 2011 was ok. But now in 2018 none of your code compiles because of changes to the language in the intervening 7 years [0]. Now the maintainers have to rewrite things, or stick with a now very outdated and potentially unstable compiler and tool suite. C++ may have been unpleasant to use, but it may have been a better choice within the environment of the decision.
Other times, by not applying systems thinking, you find yourself solving the same or similar problems over and over. Perhaps your code review process is incomplete, or your use of version control is non-existent or haphazard. Have you ever been in a shop where the same damn bug showed up every second or third build? Why? Because they solved the problem (the bug) but failed to understand the process and systemic problems that permitted the regression in the first place. And if that regression-permission-failure isn't addressed, other regressions will happen in the future and may go undetected.
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Long story short: Systems engineering applies systems thinking to the design and development of, well, systems. Software engineers should definitely study it, at least if they want to be called engineers. But systems thinking is a component of systems engineering that can go way beyond that one area in terms of applications. The more people can view things this way, the better off your team, your office, your company, your world can be. My problem is not just conveying the value of it (I have anecdotes galore), but actually bringing people up to the level where they can do it themselves, independent of my prodding and guiding.
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[0] Not a dig on Rust. They've stabilized the language specification, but this is a thing that can and does happen.
Get you a copy of "Permaculture: A Designer's Manual" by Bill Mollison.[1] Never mind that it's technically about farming. It's the finest manual of abstract design I've ever encountered.
I promise you, it's what you're looking for.[2]
[1] This is the publisher's site but it might be faster/cheaper to order from e.g. Amazon, as they are in Australia: http://www.tagari.com/store/books/permaculture-a-designers-m...
[2] Did you ever read "Mote in God's Eye" by Larry Niven? This book teaches Motie engineering.
You may take a look.
I believe this is what you're referring to. This seems useful as a reference, but not what I'm looking for.
I can recommend "Feedback Control for Computer Systems" by Philipp Janert [2], but the real underlying treasure is understanding Cybernetics. For that, try "Introduction to Cybernetics" by W. Ross Ashby [3].
[1] https://en.wikipedia.org/wiki/Control_theory
[2] http://shop.oreilly.com/product/0636920028970.do
[3] PDF available from http://pespmc1.vub.ac.be/ASHBBOOK.html
Quantum mechanics: Cohen-Tannoudji et al. Simply sublime. Read the first chapter and you will understand the physics of quantum mechanics. Read the second chapter and you will understand the mathematics. The rest of the book is a reference of nearly every basic topic in nonrelativistic quantum mechanics.
Classical Mechanics: Landau and Lifshitz. Simply my kind of book. Terse, to the point, no faffing about, yet detailed and rich in discussion and physical insight. In other words, does not say anything it doesn't need, and doesn't omit anything that it shouldn't.
QFT: Peskin and Schroeder. The clearest introduction I found of this difficult topic.
What I use:
Public Speaking: http://www.publicspeakingproject.org/
Intro to Comm: http://kell.indstate.edu/public-comm-intro/ (I helped revise this and edited together one of the chapter from existing OER chapters with my own material)
Intro to Media Studies: http://open.umn.edu/opentextbooks/BookDetail.aspx?bookId=143
An approach I have used in the past: given a field F, find universities best known in F, and see what textbooks they use in their courses.
"On analysis in Rn, orthonormal recommends Strichartz's The Way of Analysis over Rudin's Principles of Mathematical Analysis and Kolmogorov & Fomin's Introduction to Real Analysis."
Rudin or Kolmogorov & Fomin are waaaay more advanced than Strichartz. If they wanted a more conceptual but still advanced book they could recommend e.g. Hubbard & Hubbard which is a marvelous book IMHO. I'd put it on par with SICP and CTM in terms of the enormous amount of ground it covers and the insights a novel reader can get.
But I feel like this sort of list is basically misguided, because the textbook that best suits a reader depends crucially on (a) the reader’s particular background and (b) the reader’s goals in learning a subject. Every textbook on a particular subject is written for a different target audience and emphasizes different aspects of the subject, so in addition to trying to identify overall quality of exposition, prospective readers should try to identify the text that best suits their knowledge and interests as they sit down to read. And after reading one text, a reader’s knowledge and interest in the subject should have changed substantially: his or her interest may be exhausted, but if it’s piqued the reader should then move on to another text that covers the subject more deeply or from a different perspective.
In short, there is no such thing as a “best” textbook. There are good and bad texts, but they’re good and bad for different readers. Well, there are some texts that are just bad and will be bad for just about any reader, but the good ones are all good only for a certain subset of readers whose background in the subject and its prerequisites, and whose goals in learning it, best match what the author had in mind (or implicitly assumes).
This is why the list was great you got to read a bunch of reviews that didn't just talk about one book but compared them. With people making lots of comments about what they got out of each textbook.
Combine with the oldish, but still unbeatable in their clarity and charisma, video lectures by Herbert Gross and you can have tons of pure, free fun.
The usual undergraduate textbook that people recommend is Griffiths, though I definitely disagree with its usefulness (the book often opts for doing a bunch of calculations to 'get the intuition,' as opposed to explaining some points clearly, which is fine but I dislike this approach).
If you're up for a fantastic, but quite dense, reading, Bohm's Quantum Theory holds a special place in my heart for its brilliant motivation and fairly clear exposition of foundational QM (note that it doesn't concern itself with the notion of Bohmian mechanics at all). This book sits on my bookshelf with hundreds of notes all over its pages. Of course, there is a good chunk of physics expected to be able to read this book, but you should skim it and skip to the chapters of interest as a good reference !
Of those, I would say Griffiths is the best option for someone with your background. It's short enough that you have some hope of going through the entire book, and it has you doing real calculations. The writing is good.
Shankar has lots of good stuff, but its 600+ pages long, so a bit overwhelming. I also found the explanations not as clear as in Griffiths.
The perspective in Feynman and Sakurai is quite different than in Griffiths, and it is possibly a better approach. But Sakurai is much more challenging than Griffiths and not nearly as well written. Feynman lacks the worked examples and exercises that Griffiths has, so is not (IMO) appropriate as your sole textbook, but definitely worth looking at for the different perspective. A text taking the Feynman (or Sakurai) approach, but at the length and level of Griffiths, would be valuable.
(I taught myself basic QM prior to going to grad school in physics, with a background similar to your, so I have some direct experience here. This was about 12 years ago. Perhaps there are better options now.)
I will say I found Griffiths incredibly difficult (it was the official text for the first course). Admittedly this is in part because my maths background was not as strong as it should have been (the quality of my school's advising was poor, and indicated that I didn't need linear algebra - among other faults). I found myself regularly consulting Eisberg and Resnick's Quantum Physics which had a nice logical structure and fully worked paradigm cases. I thought Zettili was an excellent reference as well.
I'd like to revisit all this at some point. If anyone has a link to a recommended course of study for refreshing physics majors, I'd love to have a look.
https://www.alibris.com/search/books/subject/Computers-Progr...
I want "widely accepted as great" or maybe even "good." Great or Good books may not cover exactly the same material, but any given one is likely to cover most of the material (all of the material that author/team considers most important) and avoid mistakes.
[0] Vim, Emacs, Sublime2, Sublime3, Atom, VSCode, Scintilla-based stuff, various IDEs, etc.
For Analysis, I'd rather recommend Tao's "Analysis I". Tao has the style that I really enjoy where he uses a mix of intuition and light mathematical maturity to build basic Analysis from first principles. Not everyone benefits from this approach, but if you're the person who enjoys discussing and debating with the author as you develop the fundamentals, then Tao's Analysis is fantastic.
What a rat. Recommends his own book over two others. This is exactly what is wrong with University textbook selection. They're often just picking their friends, or someone who picked their textbook. Crooked and corrupt.
> "I'm the author, so feel free to discount appropriately."
The process of consolidating all the recommendations into a list didn't leave room to say that sort of thing, though.
I mean this in general, this example here where an author is promoting his own book without hiding his name is borderline. Says more about the site's reliability than the author's honesty to me.
It’s like the process of a journalist writing a book on a topic they have only the vaguest idea about, there’s a lot of reading and at some stage hopefully some understanding slips in. Except Josh has a business degree and worked at Procter & Gamble so he actually knew what he was on about before he started writing.
I mean, if I thought someone had written a better book on a subject than I could, I doubt I'd bother writing the book!
Or, if better books existed after they wrote theirs, why would they bother mentioning theirs at all?
If you write your own textbook, you had better be prepared to explain why your book is better than other books on the same subject.
It's just business. Every business does it. Get used to it. Have an iPhone are forced to buy things from the App Store? Crooked and corrupt...? Bought a Tesla and cant use it for independent ride sharing? Crooked and corrupt? It's just business.
> It's just business. Every business does it. Get used to it.
No, that's how you get endemic corruption, which eventually leads to things like people dying from deliberately tainted food and shoddy medicine.
Widespread intolerance of corruption and scams eventually builds a trustworthy environment that's better for everyone.
Sometimes "business" must bow down to things like ethics, otherwise it tends towards corruption and exploitation.
Hocking your own book in a list of the "best textbooks on every subject" is definitely a kind of corruption. It may get you some sales but it abuses the list and any trust placed in it. Recommendations like that should be made without such conflicts of interest.
Also, repeating "it's just business" a bunch of times isn't a very good argument in favor of anything, it's nearly totally free of any content.
That's if you get caught. On paper I completely agree with you, but in reality I think you'll find many many many businesses and industry that skirt ethically and moral behavior to cement their bottom line.
I keep repeating its just business because it is, ultimately everything comes down to money especially in business. Is it inappropriate to charge people a higher price for an airline ticket because they browse your website with a macbook? It happens. What about amazon raising the price for an item because you've browsed it several times in the past already? Recommending your own book because you believe in its contents but also helps to put a roof over your head? It's all just business.
> That's if you get caught. On paper I completely agree with you, but in reality I think you'll find many many many businesses and industry that skirt ethically and moral behavior to cement their bottom line.
No, businesses, and the people who they're composed of, must bow down to things like ethics, even when they wouldn't get "caught" behaving unethically.
> I keep repeating its just business because it is, ultimately everything comes down to money especially in business.
That's a morally bankrupt sentiment. Don't hold up a descriptive model of sociopathic behavior as a normative model of social behavior.
Simple models can be intellectually compelling, but neither correct nor complete. Simple economic theories, especially not the ones laymen read, do not represent the bedrock principles of society or human behavior. There's much they leave out and more that's orthogonal to them.
Do you use Uber, Apple, Github or Amazon? Because if you do you are accepting these principals as just being part of business and it comes down to money. Most CEOs and/or founders exhibit a significant degree of sociopathic behavior and it's clearly accepted (evidenced by the support seen in HN discussions). Yes simple models can be neither 100% or complete but do show a general trend. Move fast and break things, easier to ask for forgiveness than permission, all is fair in love andwar (and business). Im not saying its right, Im saying Im not surprised and expect this behavior from most companies and also expect some sort of insane justification when caught.
Not that tired pseudoargument again. "Don't you exist in the imperfect world? Therefore you must be OK with its deficiencies." With few exceptions, the inhabitants of Earth are unable to conjure bubbles perfectly isolated from contact with any of the world's imperfections. That doesn't mean we're unjustified or hypocritical for criticizing those flaws or using our limited influence to try to smooth out those we can.
Also, there's that misleading blurring between the normative, circumstantial, and explanatory again.
> Most CEOs and/or founders exhibit a significant degree of sociopathic behavior and it's clearly accepted (evidenced by the support seen in HN discussions).
It's really odd how adamant you are that we should accept corrupt or sociopathic behavior as normal, and how resistant you are to criticism of it or calls for its curtailment.
> Move fast and break things, easier to ask for forgiveness than permission, all is fair in love andwar (and business).
For the most part, those are shitty ideas used to justify shitty actions.
>> The textbook industry is well known for its shady practices that go beyond "just doing business."
> Most industries have practices that can be considered shady. It's not unique to the text book industry is my point.
Ah, the famous "I claim everyone's doing it without proof, so it's OK" argument.
Being OK, and something happening all the time are different arguments. Im just saying it happens everywhere, not OK but also unavoidable.
You're saying such behavior should be accepted and left without comment, because you claim "everyone's doing it." At best, that's and argument for apathy that rejects the idea that progress is possible.
What are you trying to accomplish by saying stuff like this? The subject of your sentence is "corruption and shady behavior." It's false that corruption and shady behavior are "accepted everyday by people everywhere now" without extraordinary evidence that you fail to provide.
That is, unless when you say "accepted" you mean "endured," and you just chose your words poorly.
Even in your further explanations of your repeated use of the phrase, you continue to say things like "it's not corrupt, it's just business". That makes no sense. Something can be both. These are not the same thing. Business is not always corrupt, and corruption isn't always "just business"
A view that "much of business is corrupt" may be true but there is no nuance in your (confusing) statements.
Come again?
My professor for Political Science recommended his own book.
He also donated all of the money he would have made on it for our class into the general fund for the students. Which meant that he lost money because not everybody in the class bought the book.
Textbooks are a racket. Especially the "rental" model which effectively admits that the textbook has zero utility beyond the class.
However, the professors are neither the cause nor gaining the profits from that racket. The act of writing a textbook takes so much time and effort, that it really isn't profitable for the vast majority of professors.
The real value of it, at least for me, is inspiration. I read a small chapter (which is often just a page or half) and think how it relates to my actual situation. This gives me some food for thought, and very often for action, for a couple of days. Then I go back to the book, read the next piece, and so on. I sometimes disagree with the author, but it's a positive experience overall.
0: https://www.lesswrong.com/posts/xg3hXCYQPJkwHyik2/the-best-t...
Edit: I have not read this book or any others in the domain, just wanted to add some context I did not already see in this thread.
The Personal MBA is also great, but I do agree that it's poor form for Josh to recommend his own book.
https://web.archive.org/web/20180726150520/https://www.lessw...
Note that I had to disable JavaScript to prevent it from hiding the content and displaying "Sorry, we couldn't find what you were looking for."
[0]: https://web.archive.org/web/20180220101251/http://lesswrong....
But now that you remind me of that, I think we now have the relevant technology and understanding of the old DB to make it do the correct thing. I will give it a shot in the next few days.