Probability books reddit. Bishop's section on probability is rather good.

Probability books reddit I used coaching actuaries for P then used Lay for my probability theory course and pretty much coasted through on my knowledge from CA and didn’t really try that hard since it was my last math class of college Problems in Probability by T. Yeah most of the books are good for the most part. One book I really enjoyed when learning statistics at uni was Grimmett and Stirzaker’s “probability and random processes”. I think Blitzstein and Hwang (suggested by another poster) is probably the most comprehensive not measure theoretic probability book. As one of my undergrad profs said, never learn probability from a statistics book (e. I find it fascinating but some of the terms and equations I find in books and articles are just unintelligible to me, and I need some advice on where to start with brushing up on statistical methods and concepts that will help me go further in machine learning. Probability theory is the soul of statistics. Posted by u/Individual_Ad_1214 - 1 vote and 2 comments /r/Statistics is going dark from June 12-14th as an act of protest against Reddit's treatment of 3rd party app developers. It's available online. There are many possible books, but the main issue is that books tend to have their own notation and that's going to be different from the notation your professor is going to use. For basic forecasting, Hyndman's fpp 3 is one possibility, though you might prefer something like Shumway & Stoffer perhaps. Durrett’s Probability: Theory and Examples seems to be a canonical text. If you don't, then get your calc in order first, then come back and try again. A while back I asked this subreddit about good books on probability theory. Given the units on the syllabus, you'd need to look into a Probability book, or Probability and Statistics book. The best one if you have time to go through the problem sets. I was interested in a book in probabability theory which is structured such that it contains introductory material, ie. Springer Undergraduate books are always good - the Probability one is Probability Models by John Haigh. In terms of topics, We are currently on cdfs and special cont distribution types (gamma, weibull etc. The early undergrad probability courses are mostly combinatorial in nature. I'm looking for a good introductory Statistics (and Probability) textbook that preferably uses R to provide some practical examples. Oct 19, 2024 · I have no clear background when it comes to stats & probability, but I have learned something similar from highschool. I think you should find out what kind of probability knowledge you need for the area of machine learning you're interested in. Sheldon Ross has a book on measure theoretic probability. You don't need any stat book to learn it. Varadhan gives proofs of many of the necessary measure-theoretic theorems and references for I would consider the Art of Problem Solving series; they have introduction and intermediate books in counting and probability, as well as number theory. in underlies all the machinery you use in inference. A good series of books for this are Tao’s Analysis 1 and Analysis 2. T jaynes's approach - for someone without advanced math background - i know calculus (1 - 3 ) and linear algebra at axler's LADR book level , i tried wackerley's book but i didn't like his way which is look like high school stat books . Mills Probability Through Problems by Capinski and Zastawniak These last two are Olympic Caliber and have problems that could take lifetimes to solve or think about: "Mathematical Mind-Benders" and "Mathematical Puzzles (A Connoisseur's Collection)" by Peter Winkler; these are two separate books. A probability book cannot be pro/anti bayesian. For intro probability, try: Introduction to probability by Blitzstein and Hwang, or A First Course in Probability by Ross. The book you already have will probably suffice. g. But as your first goal was to go deeper into probability I’ll throw in another book Achim Klenke: “Probability Theory” I like the original German version, I don’t know how the translation turned out. also for people who have gone through trading interviews any topics to highlight So far I am enjoying Rosenthal's book, "A First Look at Rigorous Probability Theory". al. It won't be your last book, but it'll be your next book at least. I hope I can find something akin to that about mathematical statistics. Irrespective of what you pick up, solve a lot of problems, and/or play For a solid background in stats, I would recommend the Wasserman books: "All of Statistics" and "All of Nonparametric Statistics". I also recommend the Bona book. I haven't been an academic for almost 20 years and there may well have been some good probability books published recently, but Probability and Measure by Billingsley is a classic for a reason and quite approachable for self-learning. Just pick a book. a first course in Probability, Ross. It gives step-by-step solutions for the self-test problems, and gives answers for a subset of the others (but it doesn't work through them - though with the theoretical problems, there's not a work-up to the answer). R. Does anyone know of any such books? Please recommend! Is there a book that starts at the elementary level and preferably has some exercises (with their solution) so I can practice my way through them? The "Probability theory and stochastic processes" by Peter Bremaud is the most relatable one I've found, but it doesn't have a manual for its exercises. It’ll give you a quick introduction to probability theory too but you should consider another book that principally focus in probability theory. David Williams’ Probability with Martingales is good. But we only went up to joint probability distributions. For those of you familiar with the book, this means the equivalent of most of Rudin’s Principles of Mathematical Analysis, or popularly known as Baby Rudin. Apr 9, 2011 · Grinstead & Snell's Introduction to Probability is a good comprehensive introduction, and after that Feller's Introduction to Probability Theory and its applications is a very good serious treatment after introductory probability. The standard problem books that people recommend are great, but I would personally disregard sections pertaining to logic puzzles, stochastic calculus/options pricing, and behavioral (disclaimer: as mentioned, I have no experience with quant roles at banks). Additionally; they have a 'practice' section of the site which allows you to drill down specific subtopics (combinatorial analysis, conditional probability, etc). My suggested path to probability for any beginner would be this. Bishop's section on probability is rather good. _ Yeah I've always thought that book is a good bridge between intro probability books (e. Ross, Hoel/Port/Stone) and more advanced/abstract books (e. It's definitely rigorous without really requiring any background in other theoretical math, and I remember it being pretty clear and well The first was real in one variable with the first 9 chapters of Bartle, and the second was multi-dim with Spivak's little white book. Otherwise a standard statistics book is Shao's Mathematical Statistics. Once you understand probability and estimation theory, then you can start with ESL or any other topic (like sampling or survival analysis, time series, linear models, GLM, etc. Here a few of the standard texts to get you started. Or you might want something with a bit of time series, maybe even Harvey's book Forecasting, Structural Time Series Models and the Kalman Filter, though you may prefer a more traditional book first. If you have the math chops for it, Wasserman's is my suggestion. Allan Gut, Probability, a Graduate Course. A fairly readable measure theoretic probability book is Resnick's "A Probability Path. I've been studying computer science for a few years now and am finally wandering into the world of machine learning. I look forward to his his book tour in a few decades: “Classic Probability Machine Learning: the Retirement Tour!” 😂 Reply reply More replies More replies More replies [deleted] I think that you might find useful this book: "Probability, Statistics and Random Procesess for Electrical Engineering" 3 Ed by Alberto Leon Garcia. 'At a used book sale, there are six novels and four biographies. I would suggest "Introduction to Statistics and Data Analysis With Exercises, Solutions and Applications in R" by Christian Heumann & Michael SchomakerShalabh, which offers comprehensive solutions after each chapter. I love Williams (the book) because you can really feel that Williams (the man) has a particular perspective that he wants the reader/student to experience. For those not familiar with Blitzstein's book, the contents are as follows: Probability and counting Conditional probability Random variables and their distributions I call ross as a puzzle probability book in contrast to measure theoretic probability. Starts with very basic probability- stuff you would have probably covered pre-uni/1st year of uni (conditional probability, independence etc. Hoel/Port/Stone also have a good and concise book on stochastic processes. It’s a good mix of applications and theory and he covers a lot of topics, you won’t get bored with this book for quite some time. [E] Is "Probability and Statistics - by DeGroot and Morris" a good text book to learn statistical theory from? Education Coming from a background in Psychology and Molecular Biology, I've learned about how to use off the shelf statistical tests - in SPSS; and to an extent - building my own models in R. For intro statistics, try Statistical Inference by Casella and Berger. It really depends on the book; A good understanding of linear algebra, probabilities, and calculus, and a combination of all three It's meant to give the reader an holistic view on the components of a quantitative investment/trading system. That would be statistics. ) and goes through distribution theory, convergence theorems, all the way to Studying for interviews, one thing I was really having trouble finding was a large group of practice problems for probability. Do you have any favorite books or resources on these subjects? My god, the responses here seem to be testament about the level of real helpful advice. Quiz solutions are available on the book's website. Loeve). Hi everyone, I asked about a good probability theory book and got a suggestion for "basic probability theory" by Robert Ash, which is a great book. Prerequisite for into statistics is intro probability. With that being said I don’t have a great judgement on probability theory books. You've probably come across things like conditional probability, Bayes' theorem, the central limit theorem and laws of large numbers, random variables, expectation, variance, pdfs, cdfs, moment generating functions, and some of the more common probability I have no idea about this book but there's a weird tendency in math to name books opposite to their actual difficulty. The cheapness of Dover books means they are pretty non-impactful as impulse buys, and it doesn't seem like they issue truly crap books (from a material standpoint). Then there is Folland, which is feel is significantly harder going, and definitely requires you to know a bunch of measure theory first. I'm also going through the probability section of the green bo Thanks, I will look into it. Or Pollards "User's guide to measure-theoretic probability" is a bit more formal. Introduction to Probability and Mathematical Statistics This is another senior level math book, but can be used as a first year intro grad level book. Williams' book is really, really beautiful. I need one for Statistics, the semester course consists of: Statistical structure. The book is made for people with a formal training in statistics and the authors (all famous statisticians) are the inventors of many of the methods presented in the book. I stumbled upon a GMAT probability practice question forum, and it has a TON of probability questions labeled easy/medium/hard. I also recommend One Thousand Exercises in Probability, by Grimmett and Stirzaker. Sample moments and sample distribution function. It becomes fun once you bring in stuff like calculus and (later) measure theory. shiryaev, probability. If you don't know how to calculate the probabilities of hands in, say, Poker, this is your starting point. So I'm looking for a measure theory book that will treat probability as well ( would be a + but not required ). the english translation is in the 2nd edition while the russian book has two volumes and is the 4th edition. I think this book by Ross is the standard advanced undergraduate text that gives a nice introduction to the subject. Probability Theory: a comprehensive course (Achim Klenke), much better than classical textbook such as probability path/probability with examples. It seems people either love it or hate it. I'm still early in my journey, going through calculus using Prof. I second "Probability: A Concise Course. I was wondering if anyone here could recommend a good book that covers probability theory at a similar level to Blitzstein & Hwang, or at a slightly more advanced level. In my opinion, the text seems to be lacking a bit but it's still worth taking a look at. If you're concerned about cost check out your school's library first. Wᴇʟᴄᴏᴍᴇ ᴛᴏ ʀ/SGExᴀᴍs – the largest community on reddit discussing education and student life in Singapore! SGExams is also more than a subreddit - we're a registered nonprofit that organises initiatives supporting students' academics, career guidance, mental health and holistic development, such as webinars and mentorship programmes. a) It's illegal! b) Authors deserve your support! c) If you can't afford a book, you can't afford to trade! Happy reading! Great book on stats, starts from the basics and builds the foundation for other several advanced topics. Statistical Inference, Casella and Berger. I was recommended an amazing book by Joseph K Blitzstein and Jessica Hwang "Introduction to probability". Ross. Nothing hurt me more than theorems with no proofs or formula coming It really depends if you want measure-theoretic probability or not. If anyone can suggest a better book (or better books) that don't cost a hundred dollars, I'd really appreciate it. The teacher will loosely follow "Introduction to Probability and Statistics for Engineers and Scientists" by Sheldon Ross; it is a very expensive book and the reviews from other students and from Amazon are mostly negative. That being said, if you're fine with probability, I quite like "Signals, Systems, and Inference" by Alan Oppenheim and George Verghese. With your math background, I think the better suggestion I have is Blitzstein & Hwang Introduction to Probability along with his Harvard Stat 110 vídeos. For topics related to the design of games for interactive entertainment systems - video games, board games, tabletop RPGs, or any other type. A little of context: In 2012, I published a 1200-page book called “Machine learning: a probabilistic perspective”, which provided a fairly comprehensive coverage of the field of machine learning (ML) at that time, under the unifying lens of probabilistic modeling. Probability textbook recommendations - Nov 2021 (reviewed June 2022) What books serve as a good introduction to some of the core concepts of quantitative finance? - Oct 2021. What books have helped you find probability and statistics more intuitive? - Oct 2021. I have read some books (Karlin & Taylor Stochastic processes) but it feels like i am missing something. from what you say, it sounds like you want an introductory statistics textbook (not just a probability textbook), since these usually begin with covering probability basics (usually around the first third to half is probability and remainder statistics). My background is in Linguistics, so I'm interested in something that really starts from the basics like Introduction to Probability and Statistics for Engineers and Scientists by Sheldon M. Introduction to Mathematical Statistics - Robert Hogg Any good beginner probability books for idiots? I am a highschool student and I recently started learning probability, the school math textbook left me very confused because I am too stupid to comprehend this subject, I could partially understand some concepts by looking at visual representations but I could not understand how the equations are Probability and Statistics books Hey /r math, I've been wanting to read up on statistics and probability theory because I'm interested in their use in AI and decision-making. A bit of linear algebra, matrices, vectors, but really just the basics. It helped me immensely throughout my course in University but alas, it's not enough now. Probability and Statistical Inference by Hogg, Tanis and Zimmerman Mathematical Statistics with Applications by Wackerly /r/Statistics is going dark from June 12-14th as an act of protest against Reddit's treatment of 3rd party app developers. the space of all (continuous) functions and the Wiener measure, and the two books explain it regorously. My other alternative is Bertsekas and Tsitsiklis Introduction to Probability coupled with the MIT 6. Now, this time there are several good online courses and books are available for learning probability and statistics. Specifically, I will use the setup of most introductory textbooks where probability spaces are point spaces and random variables are pointwise defined functions (using parentheticals to indicate how we understand them in the purely measurable setup). 2 is a good starter. IMO, they're akin to Apostol's calculus volumes. The problem used to be international editions because the publishers would sell the books in India cheap and they would bring the books they bought for $5 to the US and sell for $100. chung, a course in probability theory Bauer also has a really good book on probability theory, but it does assume that you've read his measure theory book. TR Jaynes, Probability Theory: The Logic of Science Ultimately, statistics is a large enterprise, no one book contains it all, and all the books I listed above doesn't encompass it either. Tsitsiklis, Bertsekas, "Introduction to Probability, 2nd Edition" - fantastic book intuitively speaking, not so great in terms of rigour and formality. As of the current moment, I have found a book named Introduction to Probability, Statistics, and Random Processes by Hossein Pishro-Nik. Books I've started looking at: Option Volatility and Pricing, Natenberg Python for Data Analysis, McKinney Frequently Asked Questions in Quantitative Finance, Wilmott Introduction to Probability, Blitzstein (for a recap of fundamentals) Any other recommendations or suggestions very much welcome. Do anyone have a book/blog/youtube series they're recommend to learn about the history of probability and statistics? I have sufficient intuitive understanding of Probability Theory when it is applied in RL, I can understand the maths, but these don't come that easy, and I lack a lot of problem practice which may help me develop a better understanding of concepts, for now I can understand maths, but I wont be able to rederive or prove those bounds or lemmas by myself, so if you have any suggestions for books Sheldon Axler has a nice book on the basics of measure theory and some other analysis topics. For book recommendations please check out our Book Wiki here for some of the most commonly recommend books in a variety of categories. And it's Shiryaev, not Shiryaen. Probability and Statistics for Data Science - amazing free book (not the buzz book you imagine) Everyone knows what probability is, and we all understand how a coin flip works, but not everyone can explain the optimal betting strategies for a roulette table. If you need a little encouragement I hadn't touched stats before 14 months ago, even in highschool. my personal recommendation is statistical inference by casella and berger. Sample. Introduction to Probability by Ross is pretty standard. If FE or Economics is where you get into, Jacob and Protter’s Probability Essential or even the first two chapters of Shreve’s Vol. I am a 4th year maths-physics teacher now taking stochastic processes but i have never learnt any measure theory. Reading even minimally advanced texts requires probability theory. To understand the concept of stochastic processes, need to know the canonical Wiener space, i. Let me add that, in my experience at least, Sheldon Ross's books are much easier to self-study. Builds from the ground up in an easy to follow manner. if you're looking for one I think you should start with basic probability theory. They aim at students who are interested in math contests and are pretty bright, so they pull from a lot of contest-level ideas and problems. It's very common to see PhD level books with titles like "An introduction to the Langlands program", "A first course in modular forms" or "Derived algebraic geometry for dummies" which are likely much more demanding than "Advanced calculus" or "A second course in linear algebra". In my school it was the text used for a probability 2 course, and is also pretty well known around actuary circles. Loehr (2nd edition, 2017). But if you put your mind to it, build a strong foundation, you can keep learning and building and applying. Beginners level: An introduction to probability by bertsekas/ Feller vol 1. You can learn it from Casella and Berger, where the first 4 chapters are devoted to it, and then the book goes into statistics. " This is also a place to talk about your own psychology research, methods, and career in order to gain input from our vast psychology community. _ I don't think this is typically an introductory book, but I used the book Probability and Random Processes by Grimmett and Stirzaker for my first probability theory course and I thought it was really good. If you have done statistical mechanics, you likely have a decent understanding of a lot of the basic ideas in classical probability theory. They look like they do a great job bridging measure theory and probability theory. The book not only teaches you the theory behind statistical methods, but also demonstrates their The book covers all the probability notions you will need and provides intuitive explanations of all presented concepts. My undergraduate text was Fundamentals of Probability, Ghahramani. Tons of examples covering every topic discussed. Here's a list of books that I've had a look at so far. It was okay. In my experience practical understanding of information theory boils down to developing an intuition for it in terms of counting shared bits (in the 0,1 technical sense) of information and then realizing applying it to the continuous case requires probability distribution estimates which is hard. The best book I have used so far is "Probability and Statistical Inference". Varadhan's book Probability Theory is an excellent grad-level text which deals with the basics of probability theory. is there any probability books similar to - E. Thanks. Hi, I am a Master’s student in Astrophysics. i have taken probability and stochastic processes, however i was wondering if someone can guide me to another book in stats thats good. This book is considered a good comprehensive statistics book, that contains exercises and solutions for self-study. Thanks in advance Maybe combine with a 'popular science' probability book like the ones written by Haigh or Rosenthal for 'fun' brain teaser style problems. Maybe rigorous was a better term. I've gone through the sub's wiki and read Berteskas & Tsitsiklis-- I understood most of it but found that it didn't really help me solve interview-type questions. M. It's pretty thorough and contains most of the material I would expect your course to cover. I will recommend Klenke’s Probability Theory or Billingsley’s Probability and Measure. We learned about the definition of probability, Bayes theorem and practised with this for a while, and then the course skipped to stats and we learned about distributions (3-4 most common ones, binomial, poisson, normal) with the focus on gaussian/normal distribution. High Dimensional Probability (Vershynin) A natural introduction to Probability theory by Ronald Meester, by far the best book on Probability (without measure theory) out there, he uses no measure theory and derives everything from basic notions and calculus, the book gives great intuition for many of the facts and the book is on archive so you can read it (and I believe donwload it) for free, very fun book. Bertsekas' book is also rather good if you want to learn good proof based-measure theory probability I want to study AI and Data science in the future, and currently I sometimes run into statistics when i read some book for example i was reading a database concepts books and in the Big Data chapter I saw statistics used, another day I saw statistics in computer architecture (or Operating system) books for performance and I have to skip those chapters because of my lack of understanding For someone with a good understanding of single variable calculus, as well as introductory classes in linear algebra and proofs (but no real previous probability/stats experience), what would be a good intro to probability and statistics book that focuses more on the actual math and understanding rather than applied stuff? Thanks in advance. Please do not share free links to copywritten books! This will earn you a permament ban. If, however, you would want to delve slightly deeper into statistics, this is a good book: All of Statistics, by Larry Wasserman. The intro combinatorics book I used in undergrad. Then, for a book that goes deeper into the theory (and proves theorems in full rigor), I recommend Probability (Theory and Examples) by Durrett. Absolutely loved this book. I will deliberately work in the naive concrete setup as probability is usually first presented. Posted by u/mezo_1 - 4 votes and 1 comment TR Jaynes, Probability Theory: The Logic of Science Ultimately, statistics is a large enterprise, no one book contains it all, and all the books I listed above doesn't encompass it either. By probability, I mean covering topics from basic counting principles to going up to the chi-square test and all the distributions. I am trying to improve my understanding of probability and statistics. They are really easy to find for free online. Wackerly, Larsen and Marx, Rice). It's super easy to learn. 431x lectures. " A lot of new books have been released in the past few years, so my list may be very different from everyone else's. probability and statistics are two different subjects. I'd highly recommend Jaynes' book as an antidote to these early treatments which feel like "puzzles" more than anything else. /r/GameDesign is not a subreddit about general game development, nor is it a programming subreddit. I have been going through this problem from a text book on Probability for revision. This was the book for The bachelor In Electronics and Telecommunications for the Probability and Stochastic Procesess at my College back in 2012. I have spent a considerable amount of time looking for the specific topics that I should learn in statistics and probability but the majority of the answers are far away form the topic or just recommend you books that are most of the time not suitable for beginers and are more general and have a lot of unnecessary information. Be wary of the Volume 1 and Volume 2 books as those are very focused on competition tricks and techniques. Brualdi. I'm looking for a rigorous book. i know its mentioned here in the faq, however its not mentioned the books after learning probability. S. For an easier intro, I like to recommend A First Course in Probability by Sheldon Ross or Probability and Statistics by DeGroot and Schervish. Circumstances are a little weird. _This community will not grant access requests during the protest. I thought the main textbook did a great job explaining things however. The discussions in this reddit should be of an academic nature, and should avoid "pop psychology. That's good enough. The benchmark book for that subject is the book by Casella and Berger or maybe the book by Hogg and Craig. /r/Statistics is going dark from June 12-14th as an act of protest against Reddit's treatment of 3rd party app developers. Laurie Snell. _ Basically I've been studying probability books ( frequentist / bayesian approach ) and decided to stop and build on the foundations. I sell used books and don't worry about it in the used market at all. Os a good book for multivariabke statistics, quite useful for future econometricians. Probability is hard as you can not simply memorizing formula and just plug it in, my friends can solve complicated multivariable calculus or differential stuff cannot solve basic probability problem, when you have problem distributions, you should always go back to simply basics, the most amazing feelings when I learned it is deriving all the Kevin Murphy's ML book is specially focused on a probabilistic approach to ML and aimed to be more accessible to undergrads. Variational series. , and Capinski and Copp. Lots of examples, exercises, and really nice geometric view of conditional expectation via Hilbert spaces. Wasserman is to short, it rushes through every topic. What books would you recommend? Any suggestions on question banks for probability, statistics, combinatorics would be appreciated as well. If a person selects four books at random, what is the probability that the person selects three novels and one biography? I way I tackled this questions is: there is a total of 10 books and 4 Statistics and probability theory are really hard, not only from the various areas of pure math it draws from but statistics has a intuition that is a lot different from traditional math and can take time especially the more advanced topics. Anyway, what do you consider advanced probabilty? I was considering doing a master in probability so I am curious Please suggest me some good books/resources that can provide me with lots and lots of questions on probability and stats. all of What textbook did you use in your class and how much of the book did you cover? Which topics did you cover? I recommend Introduction to Probability by Blitzstein and Hwang [Link to PDF]. Please do not message asking to be added to the subreddit. e. ISLR book is too basic. May these books help you understand! Probability is not merely a branch of analysis, even though the Kolmogorov approach uses measure theory. If you have actually read the book you should know that it was written by statisticians and uses mathematical statistics to demonstrate how and why "supervised learning" works. David McKay's book is great in theory and includes lots of exercises And of course there are the other classics: ESL, PRML, and Tom Mitchell's ML book, which while outdated is quite nice on intuition and basics of 'learning I was looking to do the same for probability theory but most history of mathematics books I've found focused more on the development of analysis/calculus. If you are sourcing new books from a supplier, you'd better pay attention to it. Hi, would love to read some great probability and stochastic processes textbooks. The books you mentioned cover a wide array of topics, which have books to cover each. Of course the books are aimed at preparing middle and high schoolers for competitions but, nevertheless, they do have good content. Casella and Berger's book also has a treatment of probability, but I haven't read it. It is an open source book with a solutions manual. The Ross book is an intro probability text - if i remember correctly DeGroot and Schervish covers more material. ). I think a textbook in mathematical statistics like the one by Mood Graybill and Boes might be more relevant to machine learning than a book in probability like Sheldon Ross's. Or Billingsley's book, which is a bit less fun, but still good. Leonards videos while working through a Linear Algebra book all in prep for tackling a stats book. " Shlomo Sternberg's "Dynamical Systems" I also find to not be a bad supplement to existing dynamical systems' texts. But if you really want a good mathematical ststistics book, then go for Dennis D Wakerley Mathematical Statistics with Applications. In terms of books/supplemental resources, this is only a first course in introductory probability, so I’m open to any suggestion that would be rather intuitive (with/without measure theory). Billingsley is also great but I would say more standard. It's its own subject. Most well-known of course is the undergrad book A First Course in Probability, but he has several others and of the ones I have read, are very good. But I don’t think this is the best book to learn from, especially if you’re learning for the first time. Here is a list of great books in probability, found in this blog: The Probability Tutoring Book: An Intuitive Course for Engineers and Scientists (and Everyone Else!) An Introduction to Probability Theory and Its Applications, Vol. Definitions. Plenty of examples and questions, no measure theory but covers a lot of probability. Thanks! 🤝 In fact, just by working through all the probability and statistics courses you will be well on your way to being able to answser most of the questions in the interview books. Once upon a time, they might have been excellent introductory texts for students of a high caliber with the right background and teacher, but mathematics education between now and when those books were written has apparently changed quite drastically. I had calculus, but not multivariable calculus. 1, 3rd Edition; Discovering Statistics Using R; Fifty Challenging Problems in Probability with Solutions May 1, 2011 · A really comprehensive, easy to read book would be "An Introduction to measure and probability" by J. this book goes from elementary probability to advanced probability, with a self-contained introduction to measure theory that is needed for advanced probability. Its not a bad read for self study and I think the material is decent. It is not very deep into probability since it does not mention sigma algebras. We don’t study probability to understand the likelihood of events. no single book can cover everything but could you recommend anything that has helped you, be it textbooks or popular books on probability, Blitzstein/Hwang's book is used for the flagship probability class at Harvard and has received very good reviews from friends. Beyond this, if you would like to read about probability Models, the book: Introduction to Probability Models, by the same author is quite good. If you already know the basics of probability and want to go further into measure-theoretic probability, then Williams "Probability with martingales" is pretty nice. Wackerly covers probability and statistical inference, but it has a very poor selection of exercises and examples. I think the main difference between probability 101 is the connection to measure theory, hence advanced. As the authors themselves admit in the preface, this book is intended to serve as an intro to probability for a wider audience, not mathematicians per se. As for ML, my favourite by far is "Introduction to Statistical Learning" and then maybe Murphy's book "Machine Learning: a Probabilistic Perspective". I'd say they're great books, but maybe not as your first introduction to probability. The book is free as well on the website. I had a friend take a stats for engineers course at the same time I was using this book and he would often use it when his book didn't explain the material well enough. Focused on stats but with a (quick) intro to probability. Tons of MATLAB code available on the book's website. The solution manual doesn't tell you all the steps most of the time though but there are some on GitHub. The books I have listed are pretty common, they should have them. Statistics. Casella and Berger is a fantastic book, but depending on your level it can be a little tough. S. Straight forward, no bullshit run through of probability. Slow, Great Depth/Heavy Theory (I don't quite have the Statistics and Probability books nailed down yet, but the rest of the list is pretty solid): Understanding Numbers in Elementary School Mathematics - Wu - [Free, Legal, Link: https://math. I am planning to break into Quants, I have a fairly good knowledge of statistics but I want to level up my probability. Ron Mittelhammer, Mathematical Statistics for Economics and Business. But I personally read this book "The Art of Statistics: Learning from Data" by David Spiegelhalter, this book helps me a lot. _ A place to share and discuss articles/issues related to all fields of psychology. . Another popular textbook is "An Introduction to Statistical Learning: with Applications in R" by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. Counting principles, sample spaces all the way up to stochastic processes. I haven't read it, but it might be worth a look, since his undergraduate introduction to probability books are fairly readable. I am just now finishing courses in measure theory and functional analysis (using Royden's book). Knowing the odds an introduction to probability by john walsh Probably by grimmett and stirzaker Looking to apply for quant trading internships for next summer, and probability is by far my weakest point. If you are looking for a probability book, then Durrett's probability theory and examples is a standard text. I'm learning quite a bit by writing them in R and Python. Somewhere in between is the smallest probability you'd still say "that's not all that weird under H0", which is what you should have as your significance level. We study probability to understand the expected outcomes of business processes that depend on those events. The Bertsekas book is a good book for first exposure to probability theory. I'm working through the free intro to probability book mentioned here. Avoid that book if you are still a beginner, that book is more suitable for Advanced learners. I have heard good things about "A Second Course in Probability" by Ross, but I haven't read it, but the two latter books develop Probability without assuming a course in measure theory, which I think is nice. Introductory Combinatorics by Richard A. If you want more math heavy, then go for Casella and Berger. C Taylor . Also, u/DaKing410 a few more recent books (listed in order of my (personal) opinion of whether they're good books or not): Combinatorics by N. We used wackerley and mendenhall as our book. In the next year I intend to take what I've learned and apply it to probability theory, by reading books by Leadbetter et. It depends what you mean by "progressing" into machine learning. This for if you want to learn measure theoretic probability. The course is called "advanced probability theory". For probability: Try the probability book Introduction to Probability by Grinstead and J. Very accessible. Ordinal statistics. It's intended more for a second undergraduate signals course, but is fully self-contained (if I remember correctly), and adds in some rudimentary random process tools. Book request: building mathematical models of real world events - Oct 2021 The way the book is laid out, it has different types of question sets: practice, theoretical, and self-test problems. I can never seem to find questions in probability textbooks I've used (Introduction to Probability by Blitzstein and Hwang, A First Course in Probability by Ross) that come close to matching the difficulty of the probability questions I've encountered on numerous OAs for quant trading positions on topics like EV, conditional probability, Markov etc. For something written by a computer scientist, Bishop has probability covered in his book, though from a mathematical perspective, it's really poorly written. If you had already had a course on measure theory, I would recommend that one. As measure theory books go it's pretty gentle - it spells things out carefully without leaving much for the reader to fill in - but this is probably not a bad thing if you're just looking for something for some self-study to get a taste of the topic. After that you should consider taking measure theory so that you can tackle some of the more difficult probability books. Anyhow, Grimmett and Stirzaker is quite good for a probability text. berkeley. What people won’t tell you, is that if you have a good math background, or are comfortable with math up to linear algebra and have a firm understanding of probability theory, read BDA3 (Bayesian Data Analysis 3rd edition) by Andrew Gelman. Similarly, Larsen and Marx's math stat book is something you can read with minimum training - (it's why I recommended it as well). The first chapter is great for a CS person because it's all about running simulations to approximate the real probability. edu/~wu/ ] /r/Statistics is going dark from June 12-14th as an act of protest against Reddit's treatment of 3rd party app developers. slo ojgnzg ldb ostxr tcee ycbjv irelrzso joblwx uqe eals