For years, my self-education was stupid and wasteful. I learned by consuming blog posts, Wikipedia articles, classic texts, podcast episodes, popular books, video lectures, peer-reviewed papers, Teaching Company courses, and Cliff's Notes. How inefficient!
I've since discovered that textbooks are usually the quickest and best way to learn new material. That's what they are designed to be, after all. Less Wrong has often recommended the "read textbooks!" method. Make progress by accumulation, not random walks.
But textbooks vary widely in quality. I was forced to read some awful textbooks in college. The ones on American history and sociology were memorably bad, in my case. Other textbooks are exciting, accurate, fair, well-paced, and immediately useful.
What if we could compile a list of the best textbooks on every subject? That would be extremely useful.
Let's do it.
There have been other pages of recommended reading on Less Wrong before (and elsewhere), but this post is unique. Here are the rules:
- Post the title of your favorite textbook on a given subject.
- You must have read at least two other textbooks on that same subject.
- You must briefly name the other books you've read on the subject and explain why you think your chosen textbook is superior to them.
Rules #2 and #3 are to protect against recommending a bad book that only seems impressive because it's the only book you've read on the subject. Once, a popular author on Less Wrong recommended Bertrand Russell's A History of Western Philosophy to me, but when I noted that it was more polemical and inaccurate than the other major histories of philosophy, he admitted he hadn't really done much other reading in the field, and only liked the book because it was exciting.
I'll start the list with three of my own recommendations...
Subject: History of Western Philosophy
Recommendation: The Great Conversation, 6th edition, by Norman Melchert
Reason: The most popular history of western philosophy is Bertrand Russell's A History of Western Philosophy, which is exciting but also polemical and inaccurate. More accurate but dry and dull is Frederick Copelston's 11-volume A History of Philosophy. Anthony Kenny's recent 4-volume history, collected into one book as A New History of Western Philosophy, is both exciting and accurate, but perhaps too long (1000 pages) and technical for a first read on the history of philosophy. Melchert's textbook, The Great Conversation, is accurate but also the easiest to read, and has the clearest explanations of the important positions and debates, though of course it has its weaknesses (it spends too many pages on ancient Greek mythology but barely mentions Gottlob Frege, the father of analytic philosophy and of the philosophy of language). Melchert's history is also the only one to seriously cover the dominant mode of Anglophone philosophy done today: naturalism (what Melchert calls "physical realism"). Be sure to get the 6th edition, which has major improvements over the 5th edition.
Recommendation: Cognitive Science, by Jose Luis Bermudez
Reason: Jose Luis Bermudez's Cognitive Science: An Introduction to the Science of Mind does an excellent job setting the historical and conceptual context for cognitive science, and draws fairly from all the fields involved in this heavily interdisciplinary science. Bermudez does a good job of making himself invisible, and the explanations here are some of the clearest available. In contrast, Paul Thagard's Mind: Introduction to Cognitive Science skips the context and jumps right into a systematic comparison (by explanatory merit) of the leading theories of mental representation: logic, rules, concepts, analogies, images, and neural networks. The book is only 270 pages long, and is also more idiosyncratic than Bermudez's; for example, Thagard refers to the dominant paradigm in cognitive science as the "computational-representational understanding of mind," which as far as I can tell is used only by him and people drawing from his book. In truth, the term refers to a set of competing theories, for example the computational theory and the representational theory. While not the best place to start, Thagard's book is a decent follow-up to Bermudez's text. Better, though, is Kolak et. al.'s Cognitive Science: An Introduction to Mind and Brain. It contains more information than Bermudez's book, but I prefer Bermudez's flow, organization and content selection. Really, though, both Bermudez and Kolak offer excellent introductions to the field, and Thagard offers a more systematic and narrow investigation that is worth reading after Bermudez and Kolak.
Subject: Introductory Logic for Philosophy
Recommendation: Meaning and Argument by Ernest Lepore
Reason: For years, the standard textbook on logic was Copi's Introduction to Logic, a comprehensive textbook that has chapters on language, definitions, fallacies, deduction, induction, syllogistic logic, symbolic logic, inference, and probability. It spends too much time on methods that are rarely used today, for example Mill's methods of inductive inference. Amazingly, the chapter on probability does not mention Bayes (as of the 11th edition, anyway). Better is the current standard in classrooms: Patrick Hurley's A Concise Introduction to Logic. It has a table at the front of the book that tells you which sections to read depending on whether you want (1) a traditional logic course, (2) a critical reasoning course, or (3) a course on modern formal logic. The single chapter on induction and probability moves too quickly, but is excellent for its length. Peter Smith's An Introduction to Formal Logic instead focuses tightly on the usual methods used by today's philosophers: propositional logic and predicate logic. My favorite in this less comprehensive mode, however, is Ernest Lepore's Meaning and Argument, because it (a) is highly efficient, and (b) focuses not so much on the manipulation of symbols in a formal system but on the arguably trickier matter of translating English sentences into symbols in a formal system in the first place.
I would love to read recommendations from experienced readers on the following subjects: physics, chemistry, biology, psychology, sociology, probability theory, economics, statistics, calculus, decision theory, cognitive biases, artificial intelligence, neuroscience, molecular biochemistry, medicine, epistemology, philosophy of science, meta-ethics, and much more.
Please, post your own recommendations! And, follow the rules.
Recommendations so far (that follow the rules; this list updated 02-25-2017):
- On history of western philosophy, lukeprog recommends Melchert's The Great Conversation over Russell's A History of Western Philosophy, Copelston's History of Philosophy, and Kenney's A New History of Western Philosophy.
- On cognitive science, lukeprog recommends Bermudez's Cognitive Science over Thagard's Mind: Introduction to Cognitive Science and Kolak's Cognitive Science.
- On introductory logic for philosophy, lukeprog recommends Lepore's Meaning and Argument over Copi's Introduction to Logic, Hurley's A Concise Introduction to Logic, and Smith's An Introduction to Formal Logic.
- On economics, michaba03m recommends Mankiw's Macroeconomics over Varian's Intermediate Microeconomics and Katz & Rosen's Macroeconomics.
- On economics, realitygrill recommends McAfee's Introduction to Economic Analysis over Mankiw's Principles of Microeconomics and Case & Fair's Principles of Macroeconomics.
- On representation theory, SarahC recommends Sternberg's Group Theory and Physics over Lang's Algebra, Weyl's The Theory of Groups and Quantum Mechanics, and Fulton & Harris' Representation Theory: A First Course.
- On statistics, madhadron recommends Kiefer's Introduction to Statistical Inference over Hogg & Craig's Introduction to Mathematical Statistics, Casella & Berger's Statistical Inference, and others.
- On advanced Bayesian statistics, Cyan recommends Gelman's Bayesian Data Analysis over Jaynes' Probability Theory: The Logic of Science and Bernardo's Bayesian Theory.
- On basic Bayesian statistics, jsalvatier recommends Skilling & Sivia's Data Analysis: A Bayesian Tutorial over Gelman's Bayesian Data Analysis, Bolstad's Bayesian Statistics, and Robert's The Bayesian Choice.
- On real analysis, paper-machine recommends Bartle's A Modern Theory of Integration over Rudin's Real and Complex Analysis and Royden's Real Analysis.
- On non-relativistic quantum mechanics, wbcurry recommends Sakurai & Napolitano's Modern Quantum Mechanics over Messiah's Quantum Mechanics, Cohen-Tannoudji's Quantum Mechanics, and Greiner's Quantum Mechanics: An Introduction.
- On music theory, komponisto recommends Westergaard's An Introduction to Tonal Theory over Piston's Harmony, Aldwell and Schachter's Harmony and Voice Leading, and Kotska and Payne's Tonal Harmony.
- On business, joshkaufman recommends Kaufman's The Personal MBA: Master the Art of Business over Bevelin's Seeking Wisdom and Munger's Poor Charlie's Alamanack.
- On machine learning, alexflint recommends Bishop's Pattern Recognition and Machine Learning over Russell & Norvig's Artificial Intelligence: A Modern Approach and Thrun et. al.'s Probabilistic Robotics.
- On algorithms, gjm recommends Cormen et. al.'s Introduction to Algorithms over Knuth's The Art of Computer Programming and Sedgwick's Algorithms.
- On electrodynamics, Alex_Altair recommends Griffiths' Introduction to Electrodynamics over Jackson's Electrodynamics and Feynman's Lectures on Physics.
- On electrodynamics, madhadron recommends Purcell's Electricity and Magnetism over Griffith's Introduction to Electrodynamics, Feynman's Lectures on Physics, and others.
- On systems theory, Davidmanheim recommends Meadows' Thinking in Systems: A Primer over Senge's The Fifth Discipline: The Art & Practice of The Learning Organization and Kim's Introduction to Systems Thinking.
- On self-help, lukeprog recommends Weiten, Dunn, and Hammer's Psychology Applied to Modern Life over Santrock's Human Adjustment and Tucker-Ladd's Psychological Self-Help.
- On probability theory, SarahC recommends Feller's An Introduction to Probability Theory + Vol. 2 over Ross' A First Course in Probability and Koralov & Sinai's Theory of Probability and Random Processes.
- On probability theory, madhadron recommends Grimmett & Stirzaker's Probability and Random Processes over Feller's Introduction to Probability Theory and Its Applications and Nelson's Radically Elementary Probability Theory.
- On topology, jsteinhardt recommends Munkres' Topology over Armstrong's Topology and Massey's Algebraic Topology.
- On linguistics, etymologik recommends O'Grady et al.'s Contemporary Linguistics over Hayes et al.'s Linguistics: An Introduction to Linguistic Theory and Carnie's Syntax: A Generative Introduction.
- On meta-ethics, lukeprog recommends Miller's An Introduction to Contemporary Metaethics over Jacobs' The Dimensions of Moral Theory and Smith's Ethics and the A Priori.
- On decision-making & biases, badger recommends Bazerman & Moore's Judgment in Managerial Decision Making over Hastie & Dawes' Rational Choice in an Uncertain World, Gilboa's Making Better Decisions, and others.
- On neuroscience, kjmiller recommends Bear et al's Neuroscience: Exploring the Brain over Purves et al's Neuroscience and Kandel et al's Principles of Neural Science.
- On World War II, Peacewise recommends Weinberg's A World at Arms over Churchill's The Second World War and Day's The Politics of War.
- On elliptic curves, magfrump recommends Koblitz' Introduction to Elliptic Curves and Modular Forms over Silverman's Arithmetic of Elliptic Curves and Cassel's Lectures on Elliptic Curves.
- On improvisation, Arepo recommends Salinsky & Frances-White's The Improv Handbook over Johnstone's Impro, Johnston's The Improvisation Game, and others.
- On thermodynamics, madhadron recommends Hatsopoulos & Keenan's Principles of General Thermodynamics over Fermi's Thermodynamics, Sommerfeld's Thermodynamics and Statistical Mechanics, and others.
- On statistical mechanics, madhadron recommends Landau & Lifshitz' Statistical Physics, Volume 5 over Sethna's Entropy, Order Parameters, and Complexity and Reichl's A Modern Course in Statistical Physics.
- On criminal justice, strange recommends Fuller's Criminal Justice: Mainstream and Crosscurrents over Neubauer & Fradella's America's Courts and the Criminal Justice System and Albanese' Criminal Justice.
- On organic chemistry, rhodium recommends Clayden et al's Organic Chemistry over McMurry's Organic Chemistry and Smith's Organic Chemistry.
- On special relativity, iDante recommends Taylor & Wheeler's Spacetime Physics over Harris' Modern Physics, French's Special Relativity, and others.
- On abstract algebra, Bundle_Gerbe recommends Dummit & Foote's Abstract Algebra over Lang's Algebra and others.
- On decision theory, lukeprog recommends Peterson's An Introduction to Decision Theory over Resnik's Choices and Luce & Raiffa's Games and Decisions.
- On calculus, orthonormal recommends Spivak's Calculus over Thomas' Calculus and Stewart's Calculus.
- 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.
- On real analysis and measure theory, orthonormal recommends Stein & Shakarchi's Measure Theory, Integration, and Hilbert Spaces over Royden's Real Analysis and Rudin's Real and Complex Analysis.
- On partial differential equations, orthonormal recommends Strauss' Partial Differential Equations over Evans' Partial Differential Equations and Hormander's Analysis of Partial Differential Operators.
- On introductory real analysis, SatvikBeri recommends Pugh's Real Mathematical Analysis over Lang's Real and Functional Analysis and Rudin's Principles of Mathematical Analysis.
- On commutative algebra, SatvikBeri recommends MacDonald's Introduction to Commutative Algebra over Lang's Algebra and Eisenbud's Commutative Algebra With a View Towards Algebraic Geometry.
- On animal behavior, Natha recommends Alcock's Animal Behavior, 6th edition over Dugatkin's Principles of Animal Behavior and newer editions of the Alcock textbook.
- On calculus, Epictetus recommends Courant's Differential and Integral Calculus over Stewart's Calculus and Kline's Calculus.
- On linear algebra, Epictetus recommends Shilov's Linear Algebra over Lay's Linear Algebra and its Appications and Axler's Linear Algebra Done Right.
- On numerical methods, Epictetus recommends Press et al.'s Numerical Recipes over Bulirsch & Stoer's Introduction to Numerical Analysis, Atkinson's An Introduction to Numerical Analysis, and Hamming's Numerical Methods of Scientists and Engineers.
- On ordinary differential equations, Epictetus recommends Arnold's Ordinary Differential Equations over Coddington's An Introduction to Ordinary Differential Equations and Enenbaum & Pollard's Ordinary Differential Equations.
- On abstract algebra, Epictetus recommends Jacobson's Basic Algebra over Bourbaki's Algebra, Lang's Algebra, and Hungerford's Algebra.
- On elementary real analysis, Epictetus recommends Rudin's Principles of Mathematical Analysis over Ross' Elementary Analysis, Lang's Undergraduate Analysis, and Hardy's A Course of Pure Mathematics.
books added since the list was last updated -
On applied Bayesian statistics, Dr_Manhattan recommends Lambert's A student's guide to Bayesian Statistics over McEarlath's Statistical Rethinking, Kruschke's Doing Bayesian Data Analysis, and Gelman's Bayesian Data Analysis.
On Functional Analysis, krnsll recommends Brezis's Functional Analysis, Sobolev Spaces and Partial Differential Equations over Kreyszig's and Lax's.
On Probability Theory, crab recommends Feller's An Introduction to Probability Theory over Jaynes' Probability Theory: The Logic of Science and MIT OpenCoursewar's Introduction to Probability and Statistics.
On History of Economics, Pablo_Stafforini recommends Sandmo's Economics Evolving over Robbins' A History of Economic Thought and Schumpeter's History of Economic Analysis.
On Relativity, PeterDonis recommends Carroll's Spacetime and Geometry over Taylor & Wheeler's Spacetime Physics, Misner, Thorne, & Wheeler's Gravitation, Wald's General Relativity, and Hawking & Ellis's The Large Scale Structure of Spacetime.
On Category Theory, adamShimi recommends Awodey's Category Theory over Maclane's category theory for the working mathematician.
On General Psycology, J... (read more)
Music theory: An Introduction to Tonal Theory by Peter Westergaard.
Comparing this book to others is almost unfair, because in a sense, this is the only book on its subject matter that has ever been written. Other books purporting to be on the same topic are really on another, wrong(er) topic that is properly regarded as superseded by this one.
However, it's definitely worth a few words about what the difference is. The approach of "traditional" texts such as Piston's Harmony is to come up with a historically-based taxonomy (and a rather awkward one, it must be said) of common musical tropes for the student to memorize. There is hardly so much as an attempt at non-fake explanation, and certainly no understanding of concepts like reductionism or explanatory parsimony. The best analogy I know would be trying to learn a language from a phrasebook instead of a grammar; it's a GLUT approach to musical structure.
(Why is this approach so popular? Because it doesn't require much abstract thought, and is easy to give students tests on.)
Not all books that follow this traditional line are quite as bad as Piston, but some are even worse. An example of not-quite-so-bad would be Aldwel... (read more)
In ITT itself, Westergaard offers the following summary (p.375):
(This, of course, is very similar to the methodology of theoretical linguistics.)
Westergaard basically considers tonal music to be a complex version of species counterpoint --- layers upon layers of it. He inherits from Schenker the idea of systematically reversing the process of "elaboration" to reveal the basic structures underlying a piece (or passage) of music, but goes even further than Schenker in completely explaining away "harmony" as a component of musical structure.
Notes are considered to be elements of lines, not "chords". They operations by which they are generated within lines are highly intuitive. They essentially reduce to two: step motion, and borrowing from othe... (read more)
Subject: Representation Theory
Recommendation: Group Theory and Physics by Shlomo Sternberg.
This is a remarkable book pedagogically. It is the most extremely, ridiculously concrete introduction to representation theory I've ever seen. To understand representations of finite groups you literally start with crystal structures. To understand vector bundles you think about vibrating molecules. When it's time to work out the details, you literally work out the details, concretely, by making character tables and so on. It's unique, so far as I've read, among math textbooks on any subject whatsoever, in its shameless willingness to draw pictures, offer physical motivation, and give examples with (gasp) literal numbers.
Math for dummies? Well, actually, it is rigorous, just not as general as it could potentially be. Also, many people's optimal learning style is quite concrete; I believe your first experience with a subject should be example-based, to fix ideas. After all, when you were a kid you played around with numbers long before you defined the integers. There's something to the old Dewey idea of "learning by doing." And I have only seen it tried once in advanced m... (read more)
Update see my comment for new thoughts
Topic: Introductory Bayesian Statistics (as distinct from more advanced Bayesian statistics)
Recommendation: Data Analysis: A Bayesian Tutorial by Skilling and Sivia
Why: Sivia's book is well suited for smart people who have not had little or no statistical training. It starts from the basics and covers a lot of important ground. I think it takes the right approach, first doing some simple examples where analytical solutions are available or it is feasible to integrate naively and numerically. Then it teaches into maximum likelihood estimation (MLE), how to do it and why it makes sense from a Bayesian perspective. I think MLE is a very very useful technique, especially so for engineers. I would overall recommend just Part I: The Essentials, I don't think the second half is so useful, except perhaps the MLE extensions chapter. There are better places to learn about MCMC approximation.
Why not other books?
Bayesian Data Analysis by Gelman - Geared more for people who have done statistics before.
Bayesian Statistics by Bolstad - Doesn't cover as much as Sivia's book, most notably doesn't cover MLE. Goes kinda slowly and spends a lot of time on comparin... (read more)
Brandon Reinhart used both Sivia's book and Bolstad's book and found (3rd message) Bolstad's book better for those with no stats experience:
Based on these comments, I think I was underestimating inferential distance, and I now change my recommendation. You should read Bolstad's book first (skipping the parts comparing bayesian and frequentist methods unless that's important to you) and then read Sivia's book. If you have experience with statistics you may start with Sivia's book.
Business: The Personal MBA: Master the Art of Business by Josh Kaufman.
I'm the author, so feel free to discount appropriately. However, the entire reason I wrote this book is because I spent years searching for a comprehensive introductory primer on business practice, and I couldn't find one - so I created it.
Business is a critically important subject for rationalists to learn, but most business books are either overly-narrow, shallow in useful content, or overly self-promotional. I've read thousands of them over the past six years, including textbooks.
Business schools typically fragment the topic into several disciplines, with little attempt to integrate them, so textbooks are usually worse than mainstream business books. It's possible to read business books for years (or graduate from business school) without ever forming a clear understanding of what businesses fundamentally are, or how they actually work.
If you're familiar with Charlie Munger's "mental model" approach to learning, you'll recognize the approach of The Personal MBA - identify and master the set of business-related mental models that will actually help you operate a real business successfully.
Because mak... (read more)
Wow, Duke - that's a bit harsh.
It's true that the book is not densely written or overly technical - it was created for readers who are relatively new to business, and want to understand what's important as quickly as possible.
Not everyone wants what you want, and not everyone values what you value. For most readers, this is the first book they've ever read about how businesses actually operate. The worst thing I could possibly do is write in a way that sounds and feels like a textbook or academic journal.
I don't know you personally, but from the tone of your comment, it sounds like you're trying to signal that you're too sophisticated for the material. That may be true. Even so, categorical and unqualified statements like "terrible" / "cotton candy" / and "little value to offer" do a disservice to people who are in a better position to learn from this material than you are.
That said, I'll repeat my earlier comment: if you've read another solid, comprehensive primer on general business practice, I'd love to hear about it.
I suppose I can think up a few tomes of eldritch lore that I have found useful (college math specifically):
Recommendation: Differential and Integral Calculus
Author: Richard Courant
Stewart, Calculus: Early Transcendentals: This is a fairly standard textbook for freshman calculus. Mediocre overall.
Morris Kline, Calculus: An Intuitive and Physical Approach: Great book. As advertised, focuses on building intuition. Provides a lot of examples that aren't the usual contrived "applications". This would work well as a companion piece to the recommended text.
Courant, Differential and Integral Calculus (two volumes): One of the few math textbooks that manages to properly explain and motivate things and be rigorous at the same time. You'll find loads of actual applications. There are plenty of side topics for the curious as well as appendices that expand on certain theoretical points. It's quite rigorous, so a companion text might be useful for some readers. There's an updated version edited by Fritz John (Introduction to Calculus and Analysis), but I am unfamiliar with it.
Recommended Text: Linear Algebra
Author: Georgi Shilov
David Lay, L... (read more)
I can't help but question this post.
Textbook recommendations are all over. From the old SIAI reading shelf to books individually recommended in articles and threads to wiki pages to here (is this even the first article to try to compile a reading list? I don't think it is.)
Maybe we would be better off adding pages to the LW wiki. So for
[[Economics]]a brief description why economics is important to know, links to relevant LW posts, and then a section
== Recommended reading ==. And so on for all the other subjects here.
Work smarter, not harder!
The problem is that lots of textbook recommendations are not very good. I've been recommended lots of bad books in my life. That's what is unique about this post: it demands that recommendations be given only by people who are fairly well-read on the subject (at least 3 textbooks).
But yes, adding this data to the Wiki would be great.
Since the parent omitted a link: singinst.org/reading/
Lists of textbook award winners like this list might also be useful.
Introduction to Neuroscience
Recommendation: Neuroscience:Exploring the Brain by Bear, Connors, Paradiso
Reasons: BC&P is simply much better written, more clear, and intelligible than it's competitors Neuroscience by Dale Purves and Fundamentals of Neural Science by Eric Kandel. Purves covers almost the same ground, but is just not written well, often just listing facts without really attempting to synthesize them and build understanding of theory. Bear is better than Purves in every regard. Kandel is the Bible of the discipline, at 1400 pages it goes into way more depth than either of the others, and way more depth than you need or will be able to understand if you're just starting out. It is quite well-written, but it should be treated more like an encyclopedia than a textbook.
I also can't help recommending Theoretical Neuroscience by Peter Dayan and Larry Abbot, a fantastic introduction to computational neuroscience, Bayesian Brain, a review of the state of the art of baysian modeling of neural systems, and Neuroeconomics by Paul Glimcher, a survey of the state of the art in that field, which is perhaps the most relevant of all of this to LW-type interests. The second tw... (read more)
Everyone should pass this post along to their favorite professors.
Professors will have read numerous textbooks on several subjects, and can often say which books work best for their students.
General programming: Structure and Interpretation of Computer Programs. Focuses on the essence of the subject with such clarity that a novice can understand the first chapter, yet an expert will have learned something by the last chapter.
Specific programming languages: The C Programming Language, The C++ Programming Language, CLR via C#. Informative to a degree that rarely coexists with such clarity and readability.
AI: Artificial Intelligence: a Modern Approach. Perhaps the rarest virtue of this work is that not only does it give about as comprehensive a survey of the field as will fit in a single book, but casts a cool eye on the limitations as well as strengths of each technique discussed.
Compiler design: Compilers: Principles, Techniques and Tools. The standard textbook for good reason.
I don't agree on the dragon book (Compilers: Principles, Techniques and Tools). It focuses too much on theory of parsing for front end stuff, and doesn't really have enough space to give a good treatment on the back end. It's a book I'd recommend if you were writing another compiler-compiler like yacc.
I'd rather suggest Modern Compiler Implementation in ML; even though there are C and Java versions too, a functional language with pattern matching makes writing a compiler a much more pleasant experience.
(I work on a commercial compiler for a living.)
Calculus: Spivak's Calculus over Thomas' Calculus and Stewart's Calculus. This is a bit of an unfair fight, because Spivak is an introduction to proof, rigor, and mathematical reasoning disguised as a calculus textbook; but unlike the other two, reading it is actually exciting and meaningful.
Analysis in R^n (not to be confused with Real Analysis and Measure Theory): Strichartz's The Way of Analysis over Rudin's Principles of Mathematical Analysis, Kolmogorov and Fomin's Introduction to Real Analysis (yes, they used the wrong title; they wrote it decades ago). Rudin is a lot of fun if you already know analysis, but Strichartz is a much more intuitive way to learn it in the first place. And after more than a decade, I still have trouble reading Kolmogorov and Fomin.
Real Analysis and Measure Theory (not to be confused with Analysis in R^n): Stein and Shakarchi's Measure Theory, Integration, and Hilbert Spaces over Royden's Real Analysis and Rudin's Real and Complex Analysis. Again, I prefer the one that engages with heuristics and intuitions rather than just proofs.
Partial Differential Equations: Strauss' Partial Differential Equations over Evans' Partial Differential Equations and Ho... (read more)
Subject: Problem Solving
Recommendation: Street-Fighting Mathematics The Art of Educated Guessing and Opportunistic Problem Solving
Reason: So, it has come to my attention that there is a freely available .pdf for the textbook for the MIT course Street Fighting Mathematics. It can be found here. I have only been reading it for a short while, but I would classify this text as something along the lines of 'x-rationality for mathematics'. Considerations such as minimizing the number of steps to solution minimizes the chance for error are taken into account, which makes it very awesome.
in any event, I feel that this should be added to the list, maybe under problem solving? I'm not totally clear about that, it seems to be in a class of its own.
On (real) analysis: Bartle's A Modern Theory of Integration.
Even Bayesian statistics (presumably the killer app for analysis in this crowd) is going to stumble over measure theory at some point. So this recommendation is made with that in mind.
The traditional textbooks for modern integration in this context are (the first chapters of) Rudin's Real and Complex Analysis and (the first chapters of) Royden's Real Analysis.
I can't recommend Rudin because in the second chapter he goes on this ridiculously long tangent on Urysohn's lemma that makes absolutely no sense to anyone who hasn't seen topology before. Further, the exercises tend to have a difficulty curve that starts a bit too high for the non-mathically inclined.
Royden is slightly better in this respect. The first four chapters are excellent, but still probably too theoretical. Further, eventually one will encounter measure spaces that aren't based on the real numbers and the Lebesgue measure, and because of the way Royden is set up the sections on Lebesgue theory and abstract measure theory are separated by a refresher on metric spaces and topology. Unlike the tangent in Rudin, this digression isn't as avoidable.
My recommendat... (read more)
Recommending Ben Lambert's "A student's guide to Bayesian Statistics" as the best all-in-one intro to *applied* Bayesian statistics
The book starts with very little prerequisites, explains the math well while keeping it to a minimum necessary for intuition, (+has good illustrations) and goes all the way to building models in Stan. (Other good books are McEarlath Statistical Rethinking, Kruschke's Doing Bayesian Data Analysis and Gelman's more math-heavy Bayesian Data Analysis). I recommend Lambert for being the most holistic coverage.
I have read McEarlath Statistical Rethinking and Kruschke's Doing Bayesian Data Analysis, skimmed Gelman's Bayesian Data Analysis. Recommend Lambert if you only read 1 book or as your first book in the area.
PS. He has a playlist of complementary videos to go along with the book
Subject: Introductory Decision Making/Heuristics and Biases
Recommendation: Judgment in Managerial Decision Making by Max Bazerman and Don Moore.
This book wins points by being comprehensive, including numerous exercises to demonstrate biases to the reader, and really getting to the point. Insights pop out at every page without lots of fluffy prose. The recommendations are also more practical than other books.
Here is a very similar post on Ask Metafilter. (It is actually Ask Metafilter's most favorited post of all time.)
Luke -- I wonder if either permalinks to comments answering the task, or direct quotes of them could be added to your main post (say, after two+ weeks have passed)? I know in other posts where a question is asked it can be very difficult to sift through the "meta" comments and the actual answers, especially as comments get into the 100-200+ range!
I'd love to give recommendations on probability, but I learned it from a person, not a book, and I have yet to find a book that really fits the subject as I know it. The one I usually recommend is Grimmett and Stirzaker. It develops the algebra of probability well without depending on too much measure theory, has decent exercises, and provides a usable introduction to most of the techniques of random processes. I found Feller's exposition of basic probability less clear, though his book's a useful reference for the huge amount of material on specific distribution in it. Feller also naturally covers much less ground (probability and stochastic processes has developed a lot since he wrote that book). Kolmogorov's little book (mentioned elsewhere in the threads) is typical Kolmogorov: deliciously elegant if you know probability theory and like symbols. I would love to be able to recommend Radically Elementary Probability Theory by Nelson, and it's certainly worth a read as a supplement to Grimmett and Stirzaker, but I would hesitate to hand it to someone trying to understand the subject for the first time.
For statistics, I favor Kiefer's 'Introduction to Statistical Inference'. It beg... (read more)
Subject: Basic mathematical physics
Recommendation: Bamberg and Sternberg's A Course in Mathematics for Students of Physics. (two volumes)
Reason: It is difficult to compare this book with other text books since it is extremely accessible, going all the way from 2D linear algebra to exterior calculus/differential geometry, covering electrodynamics, topology and thermodynamics. There is potential for insights into electrodynamics even compared to Feynman's lectures (which I've slurped) or Griffith's. For ex: treating circuit theory and Maxwell's equations as the same mathematical thing. The treatment of exterior calculus is more accessible than the only other treatment I've read which is in Misner Thorne Wheeler's Gravitation.
In Bayesian statistics, Gelman's Bayesian Data Analysis, 2nd ed (I hear a third edition is coming soon) instead of Jaynes's Probability Theory: The Logic of Science (but do read the first two chapters of Jaynes) and Bernardo's Bayesian Theory.
Subject: Warfare, History Of and Major Topics In
Recommendation: Makers of Modern Strategy from Machiavelli to the Nuclear Age, by Peter Paret, Gordon Craig, and Felix Gilbert.
I recommend this book specifically over 'The Art of War' by Sun Tzu or 'On War' by Clausewitz, which seem to come up as the 'war' books that people have read prior to (poorly) using war as a metaphor. The Art of War is unfortunately vague- most of the recommendations could be used for any course of action, which is sort of a common problem with translations from chinese due to the hea... (read more)
I don’t know how relevant improv is to Less Wrongers, but I find it helpful for everyday social interactions, so:
Primary recommendation: Salinsky & Frances-White’s The Improv Handbook.
Reason It’s one of the only improv books which actually suggests physical strategies for you to try out that might improve your ability rather than referring to concepts that the author has a pet phrase for that they use as a substitute for explaining what it means. Not all of the suggetions worked for me, and they’re based on primarily on anecdotal evidence (plus the s... (read more)
Non-relativistic Quantum Mechanics: Sakurai's Modern Quantum Mechanics
This is a textbook for graduate-level Quantum Mechanics. It's advantages over other texts, such as Messiah's Quantum Mechanics, Cohen-Tannoudji's Quantum Mechanics, and Greiner's Quantum Mechanics: An introduction is in it's use of experimental results. Sakurai weaves in these important experiments when they can be used to motivate the theoretical development. The beginning, using the Stern-Gerlach experiment to introduce the subject, is the best I have ever encountered.
While the following isn't really a textbook, I highly recommend it for helping you to improve your skill as a reader. "How to Read a Book" by Mortimer Adler and Charles Van Doren. It covers a variety of different techniques from how to analytically take apart a book to inspectional techniques for getting a quick overview of a book.
I never knew how to read analytically, I had never been taught any techniques for actually learning from a book. I always just assumed you read through it passively.
Subjects: algorithms/computational complexity, physics, Bayesian probability, programming
Introduction to Algorithms (Cormen, Rivest) is good enough that I read it completely in college. The exercises are nice (they're reasonably challenging and build up to useful little results I've recalled over my programming career). I think it's fine for self-study; I prefer it to the undergrad intro level or language-specific books. Obviously the interesting part about an algorithm is not the Java/Python/whatever language rendering of it. I also prefer it to Knuth's t... (read more)
Request for textbook suggestions on the topic of Information Theory.
I bought Thomas & Cover "Elements of Information Theory" and am looking for other recommendations.
For Elliptic Curves:
I recommend Koblitz' "Elliptic Curves and Modular Forms"
It stays more grounded and focused than Silverman's "Arithmetic of Elliptic Curves," and provides much more detail and background, as well as more exercises, than Cassel's "Lectures on Elliptic Curves."
Is this thread still being maintained? There was a recommendation for it to be a wiki page which seems like a great idea; I'd be willing to put the initial page together in a couple weeks if it hasn't been done but I don't think I can commit to maintaining it.
World War II.
"A World at Arms" by Gerhard L. Weinberg is my preferred single book textbook (as a reference) on World War II.
It is a suitably weighty volume on WW2, and does well in looking at the war from a global perspective, it's extensive bibliography and notes are outstanding. In comparison with Churchill's "The Second World War" - in it's single volume edition, Weinburg's writing isn't as readable but does tend to be less personal. Churchill on the other hand is quite personal, when reading his tome, it's almost as if he is sitti... (read more)
For topology, I prefer Topology by Munkres to either Topology by Amstrong or Algebraic Topology by Massey (the latter already assumes knowledge of basic topology, but the second half of Munkres covers some algebraic topology in addition to introducing point-set topology in the first half).
Both Armstrong and Massey try to make the subject more "intuitive" by leaving out formal details. I personally just found this confusing. Munkres is very careful about doing everything rigorously at the beginning, but this lets him cover much more material more ... (read more)
It really depends on your learning style, and whether you learn best through examples=>generalizations or generalizations=>examples.
Similarly, some people may learn faster from a non-rigorous approach (and fill in the gaps later), while others may learn faster from a more rigorous approach. Some people might stare at a text for hours, but might be able to motivate themselves to learn the material much faster if they had some concrete examples first (using the Internet as a supplementary resource can help in that). I actually find it easier to learn ... (read more)
I made a post with ideas for what to do if you can't find a textbook in this thread that covers the subject you want to learn.
Subject: Introductory Real (Mathematical) Analysis:
Recommendation: Real Mathematical Analysis by Charles Pugh
The three introductory Analysis books I've read cover-to-cover are Lang's, Pugh's, and Rudin's.
What makes Pugh's book stand out is simply that he focuses on building up repeatedly useful machinery and concepts-a broad set of theorems that are clearly motivated and widely applicable to a lot of problems. Pugh's book is also chock-full of examples, which make understanding the material much faster. And finally, Pugh's book has a very large number of e... (read more)
For abstract algebra I recommend Dummit and Foote's Abstract Algebra over Lang's Algebra, Hungerford's Algebra, and Herstein's Topics in Algebra. Dummit and Foote is clearly written and covers a great deal of material while being accessible to someone studying the subject for the first time. It does a good job focusing on the most important topics for modern math, giving a pretty broad overview without going too deep on any one topic. It has many good exercises at varying difficulties.
Lang is not a bad book but is not introductory. It covers a huge amoun... (read more)
It's not exactly a textbook series, but I've found the videos at khan academy http://www.khanacademy.org/#browse to be really helpful with getting the basics of a lot of things. The most advanced math it covers is calculus, which will get you a long way, and the language of the videos is always simple and straightforward.
... Guess I need to recommend it against other video series, to keep to the rules here.
I do recommend watching the stanford lecture videos http://www.youtube.com/user/StanfordUniversity?blend=1&ob=5 , but I recommend Khan over them fo... (read more)
Subject: Electromagnetism, Electrodynamics
Recommendation: Introduction to Electrodynamics by David J. Griffiths
I first received this textbook for a sophomore-level class in electrodynamics. It was reused for a few more classes. I admit that I don't have much to compare it with, though I have looked at Feynman's lectures, a couple giant silly freshman physics tomes, and J. D. Jackson's Electrodynamics, and I know what textbooks are like in general.
I was repeated floored by the quality of this book. I felt personally lead through the theory of electrodynami... (read more)
Recommendation: Introduction to Economic Analysis (www.introecon.com)
This is a very readable (and free) microecon book, and I recommend it for clarity and concision, analyzing interesting issues, and generally taking a more sophisticated approach - you know, when someone further ahead of you treats you as an intelligent but uninformed equal. It could easily carry someone through 75% of a typical bachelor's in economics. I've also read Case & Fair and Mankiw, which were fine but stolid, uninspiring texts.
I'd also recommend Wilkinson's ... (read more)
Since many people will be buying books here, this is a good place to recommend that people use a book-price search engine to find the best possible price on a book. I have found the best one to be BooksPrice. DealOz is also decent. I am not affiliated with either of these in any way.
Recommendation: My Textbook
Obviously I have some massive bias issues in evaluating my own book, but the kind of person who regularly reads and contributes to LessWrong is probably the kind of person who would write a textbook LessWrongers might want to read. Plus, a used copy costs only $3 at Amazon.
My book even briefly discusses the singularity.
Mankiw's Principles of Microeconomics and Heyne's The Economic Way of Thinking are also good.
I don't have any recommendations yet, but want to note that some Books can be read and downloaded at archive.org, for example Spivak's Calculus: https://archive.org/details/Calculus_643. For some Books you'll have to sign up to "loan" a Book Online.
It would be useful for me if some of you guys shared your methodology of choosing textbook / course / whatever for learning X, especially if X has something to do with math, computer science or programming.
My methodology (in no particular order):
Subject: Commutative Algebra
Recommendation: Introduction to Commutative Algebra by Atiyah & MacDonald
Contenders: the introductory chapters of Commutative Algebra With a View Towards Algebraic Geometry by Eisenbud and the commutative algebra chapters of Algebra by Lang.
Atiyah & MacDonald is a short book that covers the essentials of Commutative Algebra, while most books cover significantly more material. So this review should be seen as comparing Atiyah & MacDonald to the corresponding chapters of other Commutative Algebra books. There are a few... (read more)
Related: The Best Intro Book for Any Topic.
I would like to request a book on Game Theory. I went to my school's library and grabbed every book I could find, and so I have Introduction to Game Theory by Peter Morris, Game Theory 2nd Edition by Guillermo Owen, Game Theory and Strategy by Philip Straffin, Game Theory and Politics by Steven Brams, Handbook of Game Theory with Economic Applications edited by Aumann and Hart, Game Theory and Economic Modeling by David Kreps, and Gaming the Vote by William Poundstone because I also like voting theory.
My brief glances make Game Theory and Strategy look lik... (read more)
Machine learning: Pattern Recognition and Machine Learning by Chris Bishop
Good Bayesian basis, clear exposition (though sometimes quite terse), very good coverage of the most modern techniques. Also thorough and precise, while covering a huge amount of material. Compared to AI: A modern approach it is much more clearly based in Bayesian statistics, and compared to Probabilistic robotics it's much more modern.
Bishop, vs Russell & Norvig, are not in the same category. There's only two chapters in R&N that overlap with Bishop.
Within the category of planning, symbolic AI, and agent-based AI, I recommend Russell & Norvig, "Artificial Ingelligence: A Modern Approach", or Luger & Stubblefield, "Artificial Intelligence". They are aware of non-symbolic approaches and some of the tradeoffs involved. I do not recommend Charniak & McDermott, "An intro to artificial intelligence", or Nilsson, "Principles of artificial intelligence", or Winston, "Artificial Intelligence", as they go into too much detail about symbolic techniques that you'll probably never use, like alpha-beta pruning, and say nothing about non-symbolic techniques. A more complete treatement of symbolic AI is Barr & Feigenbaum, "The Handbook of Artificial Intelligence", but that's a reference work, and I'm recommending textbooks. I do recommend a symbolic AI reference work, Shapiro, "Encyclopedia of Artificial Intelligence", because the essays are reasonably short and easy to read.
Within machine learning, data mining, and pattern recogn... (read more)
For elementary economics: "Macroeconomics" by Mankiw, is without a doubt the best on the market. It is incredibly well written, and it's so good once you've read the book it fools you into thinking you understand absolutely everything on the topic! "Intermediate Microeconomics" by Varian, is arguably the one to get. It can be a tad dry, and he uses lots of maths. If you don't like the idea of that then "Microeconomics" by Katz and Rosen is a very readable and less mathematical, though not quite as comprehensive as Varian.
That's a weird feature to claim for a book you say is both good and only covers elementary knowledge.
Any recommendations for Mechanism Design textbooks?
In Introduction to Mechanism Design Badger recommended A Toolbox for Economic Design (2009) and An Introduction to the Theory of Mechanism Design (2015).
In the the preface to the latter, the author mentions a few other books too:
... (read more)
- Designing Economic Mechanisms (2006) by Leonid Hurwicz and Stanley Reiter. "The focus of this text is on informational efficiency and privacy preservation in mechanisms. Incentive aspects play a much smaller role than they do in this book."
- Communication in Mechanism Design: A Diffe
For category theory, I would recommend Category Theory by Awodey instead of Category Theory for the Working Mathematician by Maclane. Awodey gives a lot of intuition, and explain through examples many of the subtleties, while still being formal. Maclane is a great reference book, but it is to terse for first learning the field, in my opinion.
Is this list still being maintained and/or discussed over ?
I feel like the ML text-book being recommended *could* at least use an alternative in the form of: http://www.deeplearningbook.org/ , it takes a purely frequentist perspective (but consider that's basically the "practical" perspective at the moment, with even the bayesianNN work being... not so Bayesian), but it's much more concise, does a good job at explaining the math and skips over historical stuff that people either know of already (e.g DT) or that is essentially useless ou... (read more)
Question: what are the recommended books on the following topics?
*Inspiration (how to get inspiration for yourself and for others)
*Social Science research methods
This guy reviewed 5 freely available calculus textbooks and chose Elementary Calculus: An Approach Using Infinitesimals by Jerome H. Keisler as his favorite. Note that the book uses a nonstandard approach.
Here are some physics and quantum mechanics recommendations that may not meet the "read three books" requirement.
Another strategy for finding good textbooks is to surf around Amazon and see what seems to have good reviews.
Special relativity: Spacetime Physics by Taylor and Wheeler is excellent. It reminds me of the general style of the Feynman lectures, but is in depth and has good problem sets. Like the Feynman lectures it is based on developing intuition, which is important for relativity because, like QM, every single human is born with the wrong intuition. It takes time and practice to develop. Also like Feynman, the writing style isn't akin to a barren wasteland like most textbooks. It is written to teach, not as an accompaniment to a university course. Finally, the pr... (read more)
I'd like to request Best Textbook suggestions for: climate science and/or climate policy.
Recommended for LINGUISTICS: "Contemporary Linguistics", by William O'Grady, John Archibald, Mark Aronoff, & Janie Rees-Miller. Truly comprehensive, addressing ALL the areas of interesting work in linguistics -- phonetics, phonology, morphology, syntax, semantics, historical linguistics, comparative linguistics & language universals, sign languages, language acquisition and development, second language acquisition, psycholinguistics, neurolinguistics, sociolinguistics & discourse analysis, written vs spoken language, animal communicat... (read more)
In the wake of publishing Scientific Self-Help: The State of Our Knowledge, I realized there is another subject on which I have read at least three textbooks: self-help!
Recommendation: Psychology Applied to Modern Life by Weiten, Dunn, and Hammer
Reason: Tucker-Ladd's Psychological Self-Help is a 2,000 page behemoth of references from a passionate, life-long researcher in self-help. It was a work-in-progress for 20 years, and never mass-published. It's an excellent research resource, though it's now out-of-date. John Santrock's Human Adjus... (read more)
Software engineering: everything by Andrew Tanenbaum. The standard texts in the field for good reason.
the absolutely wonderful thing about textbooks is that you can often pick up older editions for the price of a paperback novel.
Sometimes two textbooks on the exact same topic serve completely different purposes. There are "I want to learn this thing I don't know" textbooks, and there are "I am an expert but I still want this book on hand as a tool to help me with my experting". Below I describe the most extreme examples I am aware of, which are unfortunately on different topics:
Nonlinear Dynamics and Chaos by Strogatz is incredibly readable. You can sit with it on a train and read non-stop without needing to look anything up and you will keep wanting to relate the next amazi... (read more)
Personality Psychology: Domains of Knowledge about Human Nature by Randy J. Larsen, David M. Buss
I have looked into maybe 40 general psychology textbooks. Not read them all though, but read quite a few. This one is still by far the best intro to general psychology. But you may put it under personality psychology even though that's basically all of psychology minus the philosophical and political part. I try to read many more textbooks to review them. I'll inform people if I find something on this level again. The problem is that it very fast gets... (read more)
For Functional Analysis, I'd recommend Functional Analysis, Sobolev Spaces and Partial Differential Equations by Haim Brezis. Some alternatives often suggested are the books by Kreyszig or Lax. Where they fall short depends on what your purpose of study is. To me, most students are learning functional analysis as a tool, usually for PDEs at the level of Evans or John and Brezis is the most versatile book for this or other purposes. It's exposition is lucid and the exercises come with partial solutions. Kreyszig has a lot of overlap but it's ... (read more)
Does anyone have a recommendation for a comprehensive history textbook, covering ancient as well as modern history, and several geographical regions? Just something to teach me about major events and dates, wars, rulers & dynasties, interactions between civilisations, etc., without neglecting the non-geopolitical aspects of history. College-level, please. (A dumbed-down alternative to what I'm asking would be to start looking for my old high school textbooks, but obviously that wouldn't be very satisfactory.) Comprehensive accounts of single civilisati... (read more)
On philosophy, I think it's important to realize that most university philosophy classes don't assign textbooks in the traditional sense. They assign anthologies. So rather than read Russell's History of Western Philosophy or The Great Conversation (both of which I've read), I'd recommend something like The Norton Introduction to Philosophy.
Just so you know, the title of Spivak's book has been misspelled as 'Caclulus.'
Subject: Animal Behavior (Ethology)
Recommendation: Animal Behavior: An Evolutionary Approach (6th Edition, 1997) Author: John Alcock
This is an excellent, well organized, engagingly written textbook. It may be a tiny bit denser than the comparison texts I give below, but I found it to be far and away the most rewarding of the three (I've just read the three). The natural examples he gives to illustrate the many behaviors are perfectly curated for the book. Also, he uses Tinbergen's four questions to frame these discussions, which ensured a rich description ... (read more)
For someone who currently has a teacher's-password understanding of physics and would like a more intuitive understanding, without desiring to put in the work to obtain a technical understanding (i.e. learning the math), I would recommend Brian Green's Fabric of the Cosmos, which I feel does for physics (and the history of physics) what An Intuitive Explanation of Bayes Law does for Bayesian probability. It goes through history, starting with Newton and ending with modern day, explaining how the various Big Names came up with their ideas, demonstrates how ... (read more)
For organic chemistry, all the textbooks have more or less the name "Organic Chemistry", The best, if most rigorous, is by Clayden, Greeves, Stuart Warren (main author) and Wothers. Much less rigorous are the books by McMurray, or Jan Smith or many others. I find the Wm. Brown book well written but rather similar to all the rest. The market requires that the book prepare one for the MCATs which means all chemistry discovered after about 1980 is omitted. Perhaps that is why Clayden is good, it is English. Modesty prevents me from naming the one I wrote, but I would suggest that if you want to organize your thoughts, writing a textbook is not a bad way to do it.
Subject: Criminal Justice Recommendation: Criminal Justice: Mainstream and Crosscurrents/John R. Fuller
Reason: The other intro texts on the subject are somewhat dry and tend to be just recitations of the Uniform Crime Reports and other government documents, with little interpretation. There are books by several authors (Neubauer and Albanese are two), but Fuller's book takes a critical view of the system without demonizing the system or those who work in it. Fuller's writing is also better, making reading a pleasure, which is an unusual trait for textbook.... (read more)
This article showed up on the front page of HackerNews and on the front page of metafilter today.
Recommendation requests: Intro to calculus. I know about derivatives and I can use them and I sort of understand integrals but my knowledge is very fragmented. For instance, I don't know what half of the notation is supposed to actually represent. Also, I want strategies for solving problems rather than being given a bunch of (apparently) unrelated tools and told to just figure it out.... yea, I didn't have a good math teacher
Set theory and other discrete mathematics.
Something or other on the scientific method (how to design experiments)
Biology... (read more)
Recommendation: Miller, An Introduction to Contemporary MetaEthics
Reason: Jacobs' The Dimensions of Moral Theory is shorter and easier, for beginners, but it doesn't explain contemporary debates hardly at all. Miller's books is more comprehensive, precise, and contemporary, and even includes some original arguments (the section on Railton is particularly good). I'd like to see an updated third edition, but the 2nd edition from 2003 is still the best thing out there for an overview of meta-ethics. Smith's Ethics and the A Priori is prett... (read more)
I would like to request a recommendation for a text that provides a comprehensive introduction to Lisp, preferably one with high readability.
Thank you for this post. It is profoundly useful. I noted it when it first appeared and recently had the need for a textbook on a subject. Came over here and found a great one.
Added the recommendations by joshkaufman, realitygrill, and alexflint.
Thanks, gang! Keep 'em coming.
In college, I found most of the time that the professor's lecture notes contain almost everything of value that both the textbook and the lecture contains, but they contain ten times less text. This led me to believe that textbooks are a terribly inefficient way to convey facts, by comparison to the format of lecture notes. Books are words, words, words, flowery metaphors, digressions, etc. Hell, I don't know what they spend all those words on. But I know that, potentially, lecture notes are one fact after another.
I find all those extra words surrounding the bare facts in textbooks to be highly useful. That's what helps me not just memorize the teacher's password but really understand the material at a gut level.
What I have found to be the best textbooks for economic theory, and econometrics based on my experiences at econ grad school (graduate level, so more mathematical than suggestions above)
Microeconomic theory - individual decision making/production/general equilibrium - Kreps, Microeconomic Foundations 1: Choice and Competitive Markets. Better then Mas-Collel, Whinston and Green, Microeconomic Theory, and Varian, Microeconomic Analysis
Microeconomic theory - game theory - Osborne and Rubenstein, A Course in Game Theory. Better than Mas-Collel, Whinston ... (read more)
Recommendation: Mastering 'Metrics by Josh Angrist and J.S. Pischke
Reason: The book uniquely explains the intuitive ideas behind econometric methods. There is also a video series by MRU on the book. Other books that I have read on the subject:
- Mostly Harmless Econometrics, by the same authors. Kind of an earlier version of Mastering Metrics, more in depth, less fun and engaging.
- Introductory Econometrics A Modern Approach, by Wooldridge. Excellent for hands-on projects, very detailed, not as intuitive and easy to read as the others, ... (read more)
Is this list still being updated? Does anyone have any recommendations for linguistics, specifically the study of how languages change over time?
We should migrate this post to a Github Awesome list. That medium works best for this kind of semi-distributed curation.
Hi, I am currently building a website to find recommended textbooks for specific topics, because I personally wanted this tool and I thought it might help other students like me, and I just randomly found this webpage a few days ago. I was wondering if I could use some of the comments here for my website, I just want to share your recommendations with more people and I will obviously add links back to this webpage and include the acknowledgements . Would that be ok with you?
By the way, the website is: www.books2learn.com
I just started this project a few weeks ago, so if you have any ideas to make it better I'm open to suggestions.
Subject: Probability Theory
Recommendation: Feller's An Introduction to Probability Theory is better than Jaynes' Probability Theory: The Logic of Science and MIT OpenCourseware: Introduction to Probability and Statistics
Jaynes' book probably has more insight for someone who already knows probabili... (read more)
Recommendation: Spacetime and Geometry
Author: Sean Carroll
This is an expanded version of Carroll's lecture notes on relativity, which he has used to teach courses and which are available for free online (see the "Lecture Notes" tab on the page linked to above). I find it to be an excellent introduction to the subject, which covers the mathematical tools used, the basics of the theory, and the most common applications, all in a straightforward fashion. I have recommended this text (or its corresponding lecture notes) many times on Physic... (read more)
For Biology 101, Life by David Sadava is amazing. I wasn't even particularly interested in the subject and just needed the course credit, but it was a fascinating page turner and made everything so clear.
I don't know if this counts as a textbook, but Python for the Absolute Beginner is so good for beginning programming. Python is a great language to learn programming with. This book is just so perfectly paced. It's the exercises that make it work so well. It increments the difficulty jus... (read more)
On introductory non-standard analysis, Goldblatt's "Lectures on the hyperreals" from the Graduate Texts in Mathematics series. Goldblatt introduces the hyperreals using an ultrapower, then explores analysis and some rather complicated applications like Lebesgue measure.
Goldblatt is preferred to Robinson's "Non-standard analysis", which is highly in-depth about the specific logical constructions; Goldblatt doesn't waste too much time on that, but constructs a model, proves some stuff in it, then generalises quite early. Also preferred to... (read more)
Subject: Written style and composition
Recommendation: Rhetorical Grammar: Grammatical Choices, Rhetorical Effects, by Martha Kolln and Loretta Gray
Reason: After reading Pinker's The Sense of Style, I wanted a meatier syllabus in the mechanics of writing well. My follow-up reading was Rhetorical Grammar and Joseph Williams' Style: Ten Lessons in Clarity and Grace.
I would actually recommend reading all three. Rhetorical Grammar is the most textbook-y of the recommendations, and The Sense of Style is more like a weighty, popular book on the subject, with Ten ... (read more)
As opposed to not elevating any particular hypothesis out of the hypothesis-space before there is enough evidence to discern it as a possibility. Privileging the Hypothesis and all that.
There is a thread on calculus textbook recommendations here. And here are some useful textbook recommendations on mathematical logic, math foundations and computability theory, courtesy of Vladimir_M.
On the basics of (normative) decision theory, I recommend Peterson's An Introduction to Decision Theory over Resnik's Choices: An Introduction to Decision Theory and Luce & Raiffa's Games and Decisions. Peterson's book has clearer explanations and is more up to date than these others. It's main failing is to ignore the work on decision theory in computer science and in Bayesian statistics, but the other two standard decision theory textbooks (Resnik; Luce & Raiffa) skip those subjects, too.
In statistical decision theory you've got Chernoff & M... (read more)
For transport phenomena (momentum, mass, heat) I recommend Bird, Stewart, Lightfoot over Welty, Wicks, Wilson, Rohrer or Deen. WWWR is good if you need a quick reference and Deen is great for mathematical treatments, but nothing beats BSL if you are trying to actually learn transport phenomena.
For Physical Chemistry, McQuarrie and Simon is better than Atkins.
For basic Calculus, James Stewart has the best treatment.
Enderton, "A mathematical introduction to logic" then Shoenfield's classic "Mathematical logic"
Cori and Lascar, "Mathematical logic: a course with exercise" for exercises for self-study
Manin, "A course in mathematical logic" for additional enrichment
Van Dalen's "Logic and Structure" and then Fitting, "First Order Logic and Automated theorem proving" to fill in the gaps
From Frege to Goedel: a sourcebook in mathematical logic
additional works by Fr... (read more)
These two books are great for those who want to study Computer Sciense in a breadth-first manner. While each topic is not discussed in great details, the number of covered topics is mind-boggling. From trivial ones such as Sorting and Searching to more esoteric matter like Pricing Algorithms for Financial Derivatives, etc.
Subject: Automated Theorem Proving
Recommendation: Harrison, Handbook of Practical Logic and Automated Reasoning
Reason: Afraid I'm going to break the rules here, I haven't read any other books on the subject but as there's nothing posted here on ATPs I thought this might be useful to someone. The book is an excellent introductory text for someone who has a CS background but not in logic, and who wants to learn about theorem provers for from a practical perspective.
Updated again. Thanks, people! Keep 'em coming!
I would like to request a book recommendation on probability theory.
Following the rules if possible.
On systems theory, I'll recommend "Thinking in Systems: A Primer" is a great general audiences book, with a great nontechnical approach.If you are looking for something more mathematical, you'll need to ask someone else; I'm just not well read enough. (Despite being a math major back in school.)
"The Fifth Discipline: The Art & Practice of The Learning Organization" is a great book, but not as useful for systems theory in general, it's a more domain specific book. (I would recommend it, but not as the best book on the subject general... (read more)
I would like to request a recommendation for a text that introduces one to Utilitarianism.
But what exactly do you want to learn? If you study widely, surely you are trying to learn something different from what specialists in their respective fields try to learn. They might for example forgo a general understanding for specialist knowledge, because that is how they could best hope to contribute something unique to their field and hence reap the rewards of status. They might overemphasize certain methods of their fields since only discoveries through the use of such methods can hope to contribute results to their field.
An example:... (read more)
Maybe not terribly relevant to LessWrong, and is not really a textbook per se, but considering that a lot of Yous are aspiring authors:
How to NOT write a novel by Mittelmark and Newman
What I also read:
Writing a Novel in 30 days
Writing the Novel from Plot to Print
On Becoming a Novelist - Gardner, John
Why? HtNWaN condenses all the good advice similar books have into extremely memorable snippets that stay with you. It will not make you a great writer, but it prevents you from being a terrible one, by instilling in you certain useful "taboos" against typ... (read more)
What astrophysics textbook would y'all suggest?
On storytelling (developing a movie script in particular).
John Truby, The Anatomy of Story. 22 Steps to Becoming a Master Storyteller
I haven't actually read other books on movie scripts, but I have read a number of comparision reviews that overwhelmingly recommend this one. I have also read Joe Vitale's books, Springboard by Demming, a number of books on Seth Godin and Made to Stick and other books by Heath brothers. Truby's book excels as a textbook. He also taught tens of thousands of people.
About solid rocket engine principle: recommend Tang Jinlan's solid rocket engine principle (it's a Chinese book)
Subject: phonological theories
Recommendation: Routledge's Handbook on Phonological Theory
Strengthes: each chapter on an approach is written by a specialist in that approach, clearly explaining what the ideas are.
Alternatives: the relevant section of Kodzasov & Krivnova's "Obshchaya fonetika" (short and obscuring some very important points, as well as leaving out some approaches); Philip Carr's "Phonology" (somewhat outdated - 1993 - and makes that unpleasant trick with "this is our current theory... now let's look how it's wrong and adopt a better theory... and again... and again" - while this is akin to how scientific thought goes it doesn't necessarily do justice to the theories in question).
Does someone have a suggestion for an anthropology book?
Subject: History of Economics
Recommendation: Economics Evolving, by Agnar Sandmo
Reason: A superbly clear overview of the history of economics, from Adam Smith until the 1970s. Each chapter provides a guide to further reading. I found this book much better than the alternatives in the genre that I consulted, including Lionel Robbins' opinionated A History of Economic Thought and Joseph Schumpeter's chaotic History of Economic Analysis.
As a companion, I recommend Keynes' Essays in Biography, a collection of wonderfully written (and astonishingly well-resear... (read more)
Regarding the McAfee economics book, the link appears to have changed. I believe this link directs to the appropriate text
Another attempt to do something like this thread: Viva la Books.
Does anyone know some good textbooks for animal anatomy and ecology? I haven't found any good ones so far...
I'd like some recommendations for precalculus textbooks. I'll be starting university in the fall and I'll taking calculus I honors, as well as other math courses. I'll likely be doing a math major. But I'm not confident in my knowledge/ability to do rigorous math, so am spending the summer reviewing past material. I'd like to make sure that I master the basics before moving on, so to speak. I already know a bit of calculus, and I know from that studying that two of my weaknesses are with logarithms and trigonometry,
For Introduction to Computational Fluid Dynamics, the book I would recommend is "Numerical Heat Transfer and Fluid Flow" by S. V. Patankar.
Most common Finite Volume codes used for incompressible flows are based on a method (SIMPLE) originally created/invented by the author, Patankar and this book has a from-the-horse's-mouth appeal and doesn't disappoint. The book is somewhat limited because everything builds up to explain the SIMPLE algorithm and the focus is narrow. However it does this very well. Another limitation is that it is short on work... (read more)
I'd like to request a book on Mathematical Economics that teaches you the basics of building and solving utility based microeconomic models (without strategic behavior).
Can anyone think of a good textbook on research in nursing? The one I have is abysmal and I literally cannot read it, thus I have a C in the class. Something in English might help. (I'm taking the class in French and although I'm almost equally fluent in both, I do find it harder work to read in French.)
Any recommendations for a textbook on cryptography?
I haven't had much success with textbooks. I have found them to be mostly boring and riddled with errors. I interpret boredom to mean that I'm not learning anything.
Here's a possible explanation for the boringness. Are you familiar with the experience of not being able to understand how you didn't get something, right after you've got it? The same presumably applies in the minds of professors.
It's hard for them to imagine not understanding the ideas. One can't know what the reader knows and doesn't know and what his misconceptions are. Teaching generation... (read more)
Subjects: algorithms, computation, physics, Bayesian probability, programming
Introduction to Algorithms (Cormen, Rivest) is good enough that I read it completely in college. The exercises are nice (they're reasonably challenging and build up to useful little results I've recalled over my programming career). I think it's fine for self-study; I prefer it to the undergrad intro level or language-specific books. Obviously the interesting part about an algorithm is not the Java/Python/whatever language rendering of it. I also prefer it to Knuth's tomes (which ... (read more)
Macroeconomics: Olivier Blanchards Macroeconomics is a concise, yet in-depth tour of standard macroeconomic theory. I recommend it as a starting point for studying topics such as monetary policy and international trade.
Subject: Introductory Real (Mathematical) Analysis:
Recommendation: Real Mathematical Analysis by Charles Pugh
The three introductory Analysis books I've read cover
Okay, I'm going to take your word for it! So I just got The Great Conversation, Sixth Edition in the mail and it looks very good. But if I want to know more about Gottlob Frege or the philosophy of language or analysis, and I'm a layperson who needs something accessible, where should I go for that? Should I just get Meaning and Argument?
There's a brand new edition of Meaning and Argument. I'm gonna get it.
I do not have the expertise to review all the books, but this is a reddit/r/compsci produced list canonical introductory textbooks covering the major branches of computer science.
I should mention that on "machine ethics", "Moral Machines" is not exactly a textbook but it is currently the best source for a view of the entire field. I do not have other books to compare it to because at the moment they do not exist.
CORRECTION: The Andersons' Machine Ethics has been released, so I'll review that and update this.
What a wondrous idea! And, the contributions to date are outstanding. Thank you!
(This title already mentioned, but not as a top-level comment) For general Artificial Intelligence, Artificial Intelligence a Modern Approach by Russell and Norvig. It's very broad but still deep enough to get a feel for a lot of areas, with some advantages of scale due to certain exmples and consistent notation being used across many areas. It's also a much easier read than Bishop's ML book already mentioned for Machine Learning stuff, though Bishop's book is much more specialized.
To get an idea of the difference in scope AIMA covers planning algorithms, ... (read more)
Added the recommendations by Davidmanheim and Alex_Altair.
I'd personally appreciate a rule-following recommendation on A.I.
On Linear Algebra:
I was immensely impressed by the original ideas I hadn't seen elsewhere in the following books at the library. After my skim reading I'm gonna go back to borrow them and recommend them to ya'll. The marketing books are exceptions - the titles just look compelling, didn't flick through them. Hope I get time to get round to finding them again.
why it sells by 'danesh', critical marketing,
quantiative methods in marketing,
data driven business models,
aesthetics in marketing,
controversy in marketing theory.
Too lazy to get the links for the rest. They are: ps... (read more)
Recommendation: Introduction to Economic Analysis (www.introecon.com)
This is a very readable (and free) microecon book, and I recommend it for clarity and concision, analyzing interesting issues, and generally taking a more sophisticated approach - you know, when someone further ahead of you treats you as an intelligent but uninformed equal. It could easily carry someone through 75% of a typical bachelor's in economics. I've also read Case & Fair and Mankiw, which were fine but stolid, uninspiring texts.
I'd also recommend Wilkinson's ... (read more)