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Probability and Statistical Inference, Books a la Carte Edition (8th Edition) Loose Leaf – Jul 24 2009
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From the Back Cover
Written by two leading statisticians, this applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.
Probability; Discrete Distributions; Continuous Distributions; Bivariate Distributions; Distributions of Functions of Random Variables; Estimation; Tests of Statistical Hypotheses; Nonparametric Methods; Bayesian Methods; Some Theory; Quality Improvement Through Statistical Methods
For all readers interested in mathematical statistics.]]> --This text refers to the Hardcover edition.
About the Author
Robert V. Hogg, Professor Emeritus of Statistics at the University of Iowa since 2001, received his B.A. in mathematics at the University of Illinois and his M.S. and Ph.D. degrees in mathematics, specializing in actuarial sciences and statistics, from the University of Iowa. Known for his gift of humor and his passion for teaching, Hogg has had far-reaching influence in the field of statistics. Throughout his career, Hogg has played a major role in defining statistics as a unique academic field, and he almost literally "wrote the book" on the subject. He has written more than 70 research articles and co-authored four books including Introduction of Mathematical Statistics, 6th edition, with J. W. McKean and A.T. Craig, Applied Statistics for Engineers and Physical Scientists 3rd edtion with J. Ledolter and A Brief Course in Mathematical 1st edition with E.A. Tanis. His texts have become classroom standards used by hundreds of thousands of students
Among the many awards he has received for distinction in teaching, Hogg has been honored at the national level (the Mathematical Association of America Award for Distinguished Teaching), the state level (the Governor's Science Medal for Teaching), and the university level (Collegiate Teaching Award). His important contributions to statistical research have been acknowledged by his election to fellowship standing in the ASA and the Institute of Mathematical Statistics.
Elliot Tanis, Professor Emeritus of mathematics at Hope College, In addition to this text, received his M.S. and Ph.D. degrees from the University of Iowa. Tanis is the co-author of A Brief Course in Mathematical Statistics with R. Hogg and Probability and Statistics: Explorations with MAPLE 2nd edition with Z. Karian. He has authored over 30 publications on statistics and is a past chairman and governor of the Michigan MAA, which presented him with both its Distinguished Teaching and Distinguished Service Awards. He taught at Hope for 35 years and in 1989 received the HOPE Award (Hope's Outstanding Professor Educator) for his excellence in teaching. In addition to his academic interests, Dr. Tanis is also an avid tennis player and devoted Hope sports fan. --This text refers to the Hardcover edition.
Top Customer Reviews
So I really don't see what the problem with this textbook is. It definitely isn't worth it to buy it new, but if you can land a used copy, then it should suit any early-mid undergraduate student just fine. Maybe it isn't as useful for a course in Statistics, and this is what people don't like about it?
In general good Txt has a lot of examples and questions
Most Helpful Customer Reviews on Amazon.com (beta)
I rate the book a 4.5 stars. The 0.5 stars held back for lack of clear separation throughout the book between where examples end, and where the next topic starts. Plus Chapter 9 (Bayesian Statistics) was a bit wordy/difficult (could just be me).
Other than that, it's been a great book to follow for an Applied Statistics focus. It is not 100% suited for self study (I'd say more like 70% suited), because a Solutions Manual is not readily available. However, with the Home work problems from this book that my instructor assigned every week, and the worked out solutions he provided subsequently, this book was just "fantastic" in getting a good intuition about the subject matter. Especially if you give an honest effort to solving the problems yourself prior to looking at solutions. The homework problems cover many areas of interest, and you can clearly tell are not just made up - at the same time, serve to explain/drill concepts well, without overemphasis on the nonstatitical background of the problem.
Like another reviewer pointed out, this book's "elder sibling", the Hogg/Craig book (which I bought too), is more theoretical/dense/concise in explanations, and is the one probably better suited for a pure Statistics focus.
There might be other books that might be even better if your focus is only on certain areas: for example I really liked Jim Pitman's Probability book (which also I own), and this book could have been used as the text for the Probability portion of the syllabus (i.e., first sem of two semesters). However, there is something to be said about having the same book for 2 courses in 2 semesters, especially when you have to refer back to the earlier course for some concepts.
Another book that is similar to current book and merits a look I believe is Larsen's Introduction to Mathematical Statistics and Its Applications, though I am not a professor who can give you a more educated comparison of the two books based on a ton of experience.
For instance, there's this part on how to convert limits of integration from one double integral to appropriate ones for a related double integral. The book introduces this saying, "It is often [doing what I just described] which causes the biggest challenge. That is, in most cases, it is easy to [do the rest of the stuff with the double integrals]. However, [doing what I just described] can be more difficult." Okay, not a great start. Does it have an illustrative example? No, in the corresponding example the book just SAYS which limits map to what. Giving it credit, there is a related diagram. But it's somewhat unclear too.
So overall... It's hard to tell what's important, it's hard to tell when an example starts and stops, sometimes the authors go off on what seem like tangents to compute super difficult integrals for a page, sometimes variables are worked with for a minute before it's mentioned what they are. And I agree with another user that it can certainly be difficult to tell whether results are meant as a "this is always true" or "in this case, ...".
I mean, it's not dreadful. I can learn from it, but I have to put more work into it than usual. I would say it's subpar.
It focuses on some different areas than Wackerly's book, Mathematical Statistics with Applications, which is the best statistics textbook that I've seen. However, this book is shorter than Wackerly, a little cheaper, and covers some areas in slightly more depth. The big drawback is that there's no eBook version for the Kindle, as there is for Wackerly.
I wish that the Amazon listing had sample pages of the book so that people could see what they're thinking about buying. I took a chance on this book and am happy with it, but it was a risk to buy it sight unseen. I held off for a long time because of that.