Probability (Springer Texts in Statistics) by Jim Pitman | (PDF) Free Download

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Ebook Info

  • Published: 1993
  • Number of pages: 576 pages
  • Format: PDF
  • File Size: 46.22 MB
  • Authors: Jim Pitman

Description

This is a text for a one-quarter or one-semester course in probability, aimed at students who have done a year of calculus. The book is organised so a student can learn the fundamental ideas of probability from the first three chapters without reliance on calculus. Later chapters develop these ideas further using calculus tools. The book contains more than the usual number of examples worked out in detail.The most valuable thing for students to learn from a course like this is how to pick up a probability problem in a new setting and relate it to the standard body of theory. The more they see this happen in class, and the more they do it themselves in exercises, the better. The style of the text is deliberately informal. My experience is that students learn more from intuitive explanations, diagrams, and examples than they do from theorems and proofs. So the emphasis is on problem solving rather than theory.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐I use the book for my interest. Probability is my interest.

⭐This book lacks rigor and clear explanations. If you manage to work through the problems, you may end up understanding (informal) probability much better than most students at the undergraduate level. If your teacher teaches from this book, you will be in for one of the most difficult times of your life.When I was first introduced to this book, I struggled very bad. I would be up late with very little progress to show for my work. However, this book slowly grew on me and I managed to break an 89.95 in my class (still got B because my professor did not round). Then I proceeded to put this book away and quickly forget about it until one of my friends explained what an actuary was. I quickly pulled this book out to study for the exam and a possible internship. Wow. Working through this book the second time, WITHOUT the pressures of school or homework, made me fall in love with the book. The problems are insanely hard compared to what my friend was studying for exam p with. Most problems really emphasized something that is not common in other introductory probability courses – learning to really read implicit questions. Unlike standard probability introductory books, the questions in Pitman’s book are not very explicit in what they are asking for and you really have to pay attention to the phrases used. It was no surprise that I passed exam p easily.However, I cannot recommend this book if you are a student with a full course load. When I took probability theory, I was also taking 4 other engineering courses along with it. I nearly jeopardized my other classes trying to master this book in one semester. Two of my friends got Cs, one got an A, and one friend failed the course because of this book. At the end of the course, most of us had come to the consensus that we hated the book (and the professor) because 15+ problems a week could easily take 10+ hours to solve and Pitman does not use rigorous arguments and definitions like the ones we learned in class.If your brave, get ready for a tough challenge. Make sure you repeat any problem you miss and DO NOT MEMORIZE. Prototype particular solutions, then proceed to generalize the results with proofs (usually induction) for sequential problems. Pay close attention to what the question is asking for. Be aware that some problems in this book assume that you have worked out previous problems in other sections. Your strongest weapons to finishing this book is gaining the ability to generalize problems along with learning the basic convergent series and every distribution from memory.

⭐The 5-star rating is for clarity and good compartmentalization of core topics for a survey course I took to augment my research. I was unable to finish a biostatistics graduate course in probability theory last fall when I had to submit an NIH grant halfway through the semester. An advisor recommended taking an introductory course in the statistics department for extra preparation, but that class filled in the spring semester, so I enrolled in the summer session. The pace was rapid since the regular 4-month course was compressed into daily 1-1/2 hour classes for one month. I haven’t had extra courses in calculus like the math majors, and it was difficult to finish the long 3-times-a-week homework assignments. A week into the course, I wasn’t sure I could keep up on top of my job duties.Thanks to a great professor and this book, I did keep up and passed the class. I doubt that I could have passed without this textbook. My previous course had used Ross’ “A First Course in Probability” with a few references to Casella and Berger. Those books assume prior knowledge of fundamental principles, and sometimes (esp. in Casella and Berger) mix topics together that are not self-evident the first time through. Pitman’s book takes a step-by-step approach that builds on prior sections so you don’t jump into topics like expectation and distributions without adequate preparation. Unlike Casella and Berger, Pitman’s book has a well-organized appendix so you can check other sections of the book for more background when needed.I agree with other reviewers that there are gaps in some parts of Pitman’s text, e.g. the sections on Poisson random variables and joint density. I could eventually solve problems on those topics only because my professor posted detailed solutions that filled in the gaps in the textbook. But because of Pitman’s clarity, I would choose his book over others for methodical coverage that allows non-math majors to understand.I rented Pitman’s book from Amazon initially, but after finishing the class decided to buy it. Now I will have a reliable reference when I repeat the biostatistics theory course this fall. If you are a brilliant math major, you can criticize this book, but for the rest of us it is a great help.

⭐I first encountered this book in the third semester of a masters-level statistics program. We nicknamed it “The Necronomicon,” due to the tome’s heft and sinister appearance. As time went on, the nickname felt more and more appropriate.This is not an easy book. As other reviewers have mentioned, some of its problems are virtually impossible to solve head-on. Its treatment of theory is somewhat shallow (mathematically speaking), and if you are using it for self-study in theory, be prepared to supplement your efforts with outside resources, particularly if you are interested in establishing proofs or working back to underlying principles. Its coverage of distributions and methods is also somewhat incomplete. For example, I seem to recall (though I may be wrong) that it is completely lacking in meaningful coverage of moments.With those caveats in mind, I have to say that I still love this book. Years after I used it as a student, it still occupies my bookshelf at work and I refer back to it often when I need to review properties of core distributions. As a textbook, it may be a little painful and chaotic (others have commented on the strange presentation order of concepts), but as a reference — not to mention as huge black and red devil-book you can use to scare undergrads — it serves admirably.

⭐As expected. Good quality, on time.

⭐If only I could give this textbook half a star, I definitely would. And that half a star is simply because it has SOMETHING to do with mathematics. This textbook is outdated, convoluted, and extremely unhelpful. As a third year mathematics student, I have seen my fair share of math textbooks and this one is the first one I have ever reviewed for being so incredibly horrible. I know almost every probability course uses this textbook and I only wish that a mathematician would publish another book in this field, because I think everyone would benefit from it.Ps. Of course the delivery/shipping of this item was fine, I am only dissatisfied with the quality of Pitman’s work.

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