It is rich in applications from accounting, finance, marketing, management and economics, covering data collection, tables and charts, probability, estimation, and more. This is one of the books that is used on the MSc in Economics econometrics course. Casella Berger is still good for an advanced undergraduate-first semester stats phd student but selection of topics is now a little dated. Full test bank for the textbook. Students: We have almost free, full-length certificate courses ready for you to take right now. File Name: probability and statistics degroot 3rd pdf.

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Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. That is a solid text, which is always to the point and rigorous. As long as you have a good instructor, that text works quite well, but is perhaps less helpful as a basis for self-study. It is far more "chatty" than the typical statistics textbook, introducing concepts with a verbal description of the goal and the underlying intuition before delving into the math.

As an example, I wanted to refresh my understanding of a sufficient statistic. Several math stat books I consulted introduced the concept with two sentences, and then delved right into equations. DeGroot on the other hand introduced the concept with two full pages of discussion and intuition pages before introducing a single equation.

After reading these two pages, I felt that I had a pretty thorough understanding of the meaning and usefulness of a sufficient statistic before I ever got to the factorization criterion which shows how to establish sufficiency mathematically. There are numerous other examples of such helpful discussion throughout the text, which make this book particularly well-suited for self-study.

There are also many examples drawn from the fields of economics and finance, which I personally find appealing.

Overall, a delightful discovery. By Panos Lambrianides on Jan 08, In the math world there are two general audiences: 1. Those that want an informal though rigorous example driven approach. This book attempts to do both. In doing so it has produced a monster of a volume that can be off-putting to both camps.

I am in the former camp and at first I was really disappointed with this book. The author is formal for the most part and does not try to introduce intuition into many places where it would be warranted, especially in the early "counting" and set chapters. This book is dry and uninspiring. What saves this book are the excellent examples and exercises that the author has accumulated over the years. In a sense your intuition is developed while doing the exercises and looking at the examples.

I really liked this book By L. I am now using this book for self-study to review, and I have to say I really enjoy reading this book. Outstanding By Cfs on Sep 23, This is an outstanding book for those with a strong math background some calculus might be enough to get by, but more is definitely better.

It covers everything that one would learn in a one-year statistics course and more, including lots of sections on Bayesian methods. I have compared this book to many others and again and again this one comes out best. Theory is rigorous, but there are lots of practical examples too. Answers to odd numbered exercises are supplied. You often have to go back and reread previous material to refresh your memory in order to understand a section or work on an exercise.

There will now be more proof than in earlier courses, yet the proofs here are delivered relatively informally. Episcopal with clear, crisp writing and abundant, well-stated exercises help you learn. It is true that there are some asides the beginner can ignore on first reading, for instance that a set union of uncountably many events may not be an event, and a proof that the reals are an uncountable set.

Joint distributions and Markov chains appear early, as soon as needed theorems have been stated. A few irritants: Failure to completely exploit the endpaper space, the traditional haunt for hints and reference formulas. The index gets short shrift, especially regarding ideas that occur only in the exercises.

To keep pp. No office complex draws million kWh per day--enough to power a big city--while using only 4, gallons of water daily, an amount 6 homes could easily dispose of. Their text will outlast the changes of instructional fad to become part of my library afterward. Awfully Structured By Mr. Smith on Nov 06, This book has far too many dependencies between chapters and sections. The authors keep making forward and backward references that make the book needlessly complicated.

The exercises should be designed more thoughtfully so they flow from easy to hard more naturally, rather than abruptly. Its chapters are very dense and difficult to understand and the examples skip a ton of steps and assume you, the reader, know how to do it. The chapters do not adequately prepare you for the questions at the end of the chapter and makes doing the problems next to impossible. Lots of Examples! They organized the text very well and gave really good examples. I felt like a learned a lot from this book.

Packwood on Apr 19, It has been some time since I read this in its entirety; however, I find myself referring to it so often I felt it was appropriate to write a review. My perspective is that of an investment professional who uses large sets of data to make investment decisions for my investment firm.

I have a bachelors degree in Economics and no graduate degrees. Despite my frequent use of statistics and probability, I felt that I was missing a lot of the underlying theory necessary to implement more sophisticated techniques--especially Bayesian ones.

So I decided to start back at the basics and refresh my knowledge from my college math classes. They then proceeded with the theory and more detailed examples. They often do this through end of section vignettes that illustrate these issues with real examples. You will still definitely learn frequentist theory in fact it always precedes the Bayesian discussions ; however, if you to build a solid base in Bayesian theory, this is a good start.

I have found no deficiencies in my foundation as I have progressed to actually implementing Bayesian techniques. In fairness, HMC do incorporate Bayesian theory as well, but I felt that based on my limited skimming of their book it was more like separate sections added it to be comprehensive and not something that was truly integrated throughout the book.

I do have one critique of the book and that is the lack of computer code for examples. I have studied it in college at the intro level, but wanted to refresh and deepen my knowledge to be well-prepared for some forays into more advanced topics.

This book had great reviews and I figured I should buy it. I was excited when the new, 4th ed, arrived in January. Then I started to read it. Nobody speaks or teaches this way in real life. People write like that when they are writing a proof at a test. I could understand the justification if author was providing a world with a tricky, long and novel proof to a hard problem. This totally breaks the flow, it fogs the concepts, and it helps to completely forget what you have just read about.

I would also be interested to learn how 3rd edition compares to 2nd and 4th. So if someone could comment on it, please, do. I would also appreciate comments from other readers as of which textbook they would recommend. I want to understand the subject at good enough debt to easily read more advanced texts. Worse than useless. By Miriam Alkon on Jan 13, Let me highlight just a few of the problems, since they have been referenced by others quite a bit: 1 Fundamentally very often unclear explanations 2 A disjuncture between the difficulty level of the examples and the problems - means working through and learning is impossible.

Maybe the positive reviews here already know the material, and are reviewing - as opposed to first-time learners. Statistics is a difficult subject for any learning By Mallory Keeler on Aug 02, My absolute favorite.

Statistics is a difficult subject for any learning level, I think, but atleast DeGroot and Schervish make it accessible while not dumbing it down. When I was working from it, there was also a pdf solution manual available with a quick google search.

Detailed stats book for mid or upper level students By Ruben Sifuentes on Sep 28, I think that the book is well focused on its main topics, and very detailed in the theorems and demonstrations.

I would say that such book is for students with background in Statistics, it might be a bit difficult dense in some theorical topics but I think that it is usual for the most part of Statistics book with depth and rigourousness in theory. All in all, I think the book is very complete and I endorse it. The material is accessible to students with calculus and linear algebra training as well as some mathematical maturity.

Examples and exercises really help improve learning. There are some minor ways the book can be improved. Maybe there is a way to reduce this on a case by case basis. The professors used the formulas from the text. I liked the text but when I worked out some formulas I did not get the same answers; I got a B in the class. Overall the writing is well-organized and the text is good; I did not work out too many of the problems; I will probably use this book again.

Very good books with a lot of examples By Luc M. Any beginner could learn rigourous probability and statistics theory from this. Overpriced, and difficult to use on Kindle By J.

Despite the outrageous price, the publisher limits you to only one Kindle device at a time, and this fact is not disclosed on this purchase page. You only find out when you try to read it on your PC after having previously downloaded it to your iPad or vice-versa. There are dozens of other good probability and statistics texts available on Amazon, and most of those other publishers are less stingy with their content.

Have to do previous exercises By Josh on Feb 26, Is the same version as the hardcover even though it is a different picture.

Great thank you very much By Elizabeth on Jan 04, Hi!! Great thank you very much! Sorry for the late return I forgot when this was due back!! Thanks again : Great Book! By Peter on Feb 21, Absolutely fantastic book. I recommend it for everyone!


Download: Probability And Statistics, 4th Edition, By Morris DeGroot.pdf

Examples and exercises really help improve learning. Page 1 of 1 Start over Page 1 of 1. Discover Prime Book Box for Kids. There are some minor ways the book can schevrish improved. The author has added special notes where it is useful to briefly summarize or make a connection to a point made elsewhere in the text. The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a new chapter on simulation including Markov chain Monte Carlo and the Bootstrapexpanded coverage of residual analysis in linear models, and more examples using real data. Introduction to Probability, Statistics, and Random Processes.


Probability and Statistics (4th Edition)

Would you like to tell us about a lower price? Examples and exercises really help improve learning. Username Password Forgot your username or password? The summaries list the most important ideas. Probability and Statistics, 2nd Edition. There are some minor ways the book can be improved.


Probability and Statistics, 3rd Edition



Probability and statistics degroot 3rd pdf


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