Book Description
Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS continues to blend the best of its proven coverage with new innovations. While retaining the straightforward presentation and traditional outline for descriptive and inferential statistics, the Twelfth Edition incorporates exciting new learning aids like MyPersonal Trainer, MyApplet, and MyTip to ensure that students learn and understand the relevance of the material. The book takes advantage of modern technology, including computational software and interactive visual tools, to facilitate statistical reasoning as well as the understanding and interpretation of statistical results. In addition to showing how to apply statistical procedures, the authors explain how to meaningfully describe real sets of data, what the statistical tests mean in terms of their practical applications, how to evaluate the validity of the assumptions behind statistical tests, and what to do when statistical assumptions have been violated. This new edition retains the statistical integrity, examples, exercises and exposition that have made it a market leader, and builds upon this tradition of excellence with new technology integration.
Customer Reviews:
Unfortunately Book Required By Professor!.......2007-09-09
I purchased textbook because it was required by my Biostatistics professor in my graduate program. Personally, I do not like the book. It makes problems more complicated than they need to be. I feel a good textbook is one in which you can read on your own and basically understand it without a whole lot of instruction and review by your professor. It would be very difficult to just read this textbook and then take an exam. I have only had the book for several weeks and I think it makes Biostats more complicated. I did purchase the supplement that goes with it, which is good for practice and the CD allows you to take self-test. If you are not savvy in stats, purchasing the supplemental practice book may be the thing for you to do if your professor requires use of the textbook.
Poorly written freshman level probability and statistics book.......2007-07-19
First, I cant believe that people actually used this book in a graduate class. I taught out of this book to freshmen.
A lot of the notation in this book is horrible and I feel this makes it harder for people new to the subject to read. Also there are very few exercises for the students to practice. In addition, too many of the answers in the back of the book are incorrect (this really confuses students).
I will not be teaching out of this book again.
Very poorly written........2004-03-15
I had to buy this book for an introductory graduate stats class. This book assumes you have some knowledge of stats and so provides very brief explanations for most concepts. This is a big problem for students with little or no stats background.
Another problem is that there are too few examples. Considering their meager explanations, one would hope they would at least provide enough examples to help students understand the concepts. But they usually provide only one or two problems, which are woefully inadequate.
Also, the CD is totally useless. Most of the practice is multiple choice, which I think is pretty silly for a stats class. In addition, there is no explanation for how they got to the answer, so if you can't figure it out and choose the wrong answer, you're out of luck for any explanation.
I stopped using this book for my course and instead began using Elementary Statistics, A Step by Step Approach by Bluman. This book is excellent; it explains everything from step 1. There are also many, many examples and lots of pictures to help you further understand stats. Also, they explain very clearly when you should use the different formulas, which I found extremely helpful in bringing all the concepts together.
Disappointing.......2004-01-16
The text we used for our undergrad Stats class covered the exact same material as this text, which we used for a graduate level class and which cost about 60 bucks more, but the undergrad text was written more clearly, concisely and logically. We even found a mistake in one of the tables in the back of this book.
An "easy" introduction but lacks content.......2003-09-18
Author: Computer Science/Mathematics Undergraduate at Cameron University
This book was required for an introductory non-calculus based statistics course at my school and it turned out to be a mixed bag. The theories are explained well in most cases but the book doesn't have enough examples for all of the theorems. Many times only one case is explained in dynamic situations leaving this reader more than a little lost. Usually the theorems are explained well enough that this is not a big deal, but not so in every case. So there tends to be those points where the student may get a little stuck without assistance from their professor.
Another problem I found was that the book was a little bit dumbed down in many areas. This book uses no calculus, so the theories are presented often without the mathematical rigor required to properly formulate accurate results. The book still presents the theorems and formulas in a way where the student can get something out of this without calculus, but it becomes a problem later in the book in the sections on regression. For a non-calculus based class like the one I took, this is all unavoidable, so the book handled the situation well considering the constraints.
This book presents a very light introduction to statistics and is good prep for more advanced statistics courses, but as a stand-alone only the most basic material is presented since it is non-calculus based and the material is spread thin between combinatorics, probability, binomial distributions, normal distributions, t distributions, ANOVA tests, regression, non-parametric statistics, etc... To attain a significant amount of useful knowledge you really need to buy separate books tackling each of these subjects independantly, so this book is really unneccessary even for an introductory text but might serve well the student who needs to be eased into statistics lightly or just wants a brief overview of the subject.
Book Description
Many statistics books lack well-defined connections among materials presented, as if the different topics were disjointed. In this new book, George Woodbury successfully illustrates the natural connections between probability and inferential statistics and between confidence intervals and hypothesis testing, for example. Throughout the book, the author provides explanations that are easy to follow and examples that are concept-based.
Book Description
This brief version of the authors' classic book retains the traditional outline for the coverage of descriptive and inferential statistics. The user-friendly presentation includes features such as Key Concepts and Formulas, and helps readers grasp the material while not sacrificing the statistical integrity of the subject. MINITAB™ (Versions 12 and 13) is used exclusively as the computer package for statistical analysis in this book.
Book Description
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The text avoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.
Customer Reviews:
Clear, rigorous, fascinating.......2007-01-20
I'm a Ph.D. student in biophysics. This is the best treatment of systems biology that I've encountered. It treats both the math and the biology with clarity, rigor, and respect. It simplifies without dumbing down. It's beautifully written. If you doubt that systems biology is a real scientific discipline, this book will change your mind.
Building Mathematical Models of Cells.......2006-09-25
The history of science over the past few centuries is to become ever more specialized. The physicists, becomming ever more concerned with the very large (stars, galaxies, the cosmos) or the very tiny (first atoms, then atomic components, now sub-components. The biologists on the other hand were studying much larger things, such as the cells that make up life. Both sciences developed techniques to facilitate their study.
In recent years, researchers have discovered that sometimes these specialized techniques can be used to develop greater insight into what is happening in other sciences.
In this book, Dr. Alon uses his training in physics to examine certain aspects of biology and to use the terminology and mathematics to describe the way these biological networks work.
The goal of the book is to begin the formulation of general laws that apply to biological networks. This is done by providing a mathematical framework in which some of the design principles of biological systems can help to understand biological networks. In looking at the results, an underlying simplicity not seen before appears in biological systems.
Great Job.......2006-09-09
A superb intro to the field. The math is moderate and helpful. Network concepts and their ties to examples and theory are clearly and succinctly presented. This is a textbook but reads easily like a book. Covers key elements while connecting them by at least mention to up-to-date further research. The basics and the grandeur of systems biology. I am trying to remember now anything on the negative side and cannot.
Product Description
An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields. This is the currently used textbook for "Probabilistic Systems Analysis," an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains, a number of more advanced topics, from which an instructor can choose to match the goals of a particular course. These topics include transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis has been just intuitively explained in the text, but is developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems. The book has been widely adopted for classroom use in introductory probability courses within the USA and abroad.
Customer Reviews:
Recommended.......2007-09-24
The shipping was very fast and the book was just as described. I would recommend this seller without hesitation!
Sheds Light.......2007-08-11
Bertsekas has truly been a savior in helping me integrate the concepts of probability. I tried most of the standard intro books before finally settling in with this comforting and rewarding book. The list included: Pittman, Ross, and Hoel. None of these books were effective in solidifying the concepts in my opinion. I think Bertsekas is also an excellent choice for brushing up for an actuary exam or self-study.
A good introduction!.......2007-02-20
First all, everyone wishing to learn probability comes from different background, math level, and motivation. There is no book that suits all. Recently I needed to know something about moment generating functions. With all my advanced engineering background though, I find it difficult to get into probability.
So I bought the following supposedly introductory texts: Ross, DeGroot, Stirzaker, Bersekas & Tsitsiklis. To me, Ross seems like a review lesson to cram for finals; it's choke full of examples but fairly spare in exposition. DeGroot is the opposite, long on descriptions but short on examples; by the time it finishes describing the problem, you have forgotten how to solve it. Probability is set up more as a prelude to statistics in the second half of the book. Stirzaker calls his book "elementary" the way Sherlock Holmes dismissed a case after slogging all night through the English bogs. It is more for the well-drilled boys from elite British "public" (private actually) schools. Bersekas comes closest to what I look for in a text, straightforward in prose with a judicious selection of examples to explain theory.
For beginners, the best approach I found, in the end, was to go the local community college and buy the text used for Finite Math. Usually, there are 3 to 4 chapters that introduce probability.
Such a text is aimed an audience from wider academic and language backgrounds, as community colleges are mandated to do. Therefore, probability is taught in simple, plain-spoken language crafted through multiple editions. One such is Finite Math, by Karl J. Smith; however, many others like it will do. For self-study, one might start in the chapter on probability to understand the author's approach, then go back a chapter or two to pick up the permutation and combinatorial math needed to calculate probability. Another alternative is just to enroll in a Finite Math course at a community college. Generally, such a course stops at Markov's chain which is enough to get you jump started in probability.
In any case, a good Finite Math text gives plenty of examples with clear, succinct, and layman-like explanation to help you tackle Ross' book or supplement any other at a higher level. If you plan to apply probability to your work, then shop around for another text after you get the basics. The thicker tomes delve more into theory which is good because real life problems are seldom like the examples given. However you can't go wrong by planting your feet solidly on a good Finite Math text first.
Excellent.......2006-07-15
I found this book a very readable, concise and useful introduction to probability.
Designed with application in mind, it emphasizes intuitive understanding and doesn't contain any boring formalism.
The only regret that I have is that avoidance of matrix calculus leads to lack of some
results, notably in markov chains (anyway this subject is well covered).
I strongly recommend this book to anyone looking for a fundamental text on applied probability.
Great Intro to Probability.......2006-03-18
I am a university student taking a probability course and found this book to be invaluable.
The book actually assigned to our class was Sheldon Ross' A First Course in Probability. I found Ross' book unreadable so I began looking for another text in order to help myself pass the class.
After reading numerous reviews I decided on an Introduction to Probability. The book is well written and easy to understand. The main points are highlighted and made extremely obvious. In addition they are backed by step by step easy to understand examples. Another feature I found very helpful was the use of graphical examples to reinforce the points being made.
In short I would recommend this book highly to anyone looking for an introduction to probability.
Update: I finished my probability course in May with an A. I completely stopped using Ross' book around the time of this review. This book was by far the most useful tool I had. I strongly back my original recommendation. I will be graduating this fall, and this book has turned out to be one of the best mathematic books I have encountered thus far.
I say this for the following reasons. First, the layout of the book, and the order it presented material is very intuitive and helpful. Second is how well the book reads. My experience with quite a few mathematics books has been the following. The math books are written by mathematicians. While being a mathematician may qualify you to teach a subject, it does not generally translate into an ability to put your ideas into written form. The result is a book that is not read by the students, but instead only consulted when all other methods of information retrieval fail. Introduction to Probability does not share this fate. The writing style of the book is very straight forward and easy to understand. While this may sound redundant, I personally think this is one of the best reasons to buy this book.
Book Description
This book is about the use of modern statistical methods for quality control and improvement. It provides comprehensive coverage of the subject from basic principles to state-of-art concepts and applications. The objective is to give the reader a sound understanding of the principles and the basis for applying them in a variety of both product and nonproduct situations. While statistical techniques are emphasized throughout, the book has a strong engineering and management orientation. Guidelines are given throughout the book for selecting the proper type of statistical technique to use in a wide variety of product and nonproduct situations. By presenting theory, and supporting the theory with clear and relevant examples, Montgomery helps the reader to understand the big picture of important concepts. Updated to reflect contemporary practice and provide more information on management aspects of quality improvement.
Customer Reviews:
Do not buy this CRAM book........2007-01-22
If you want to understand and pass a subject, you have to read the original book (here Introduction to Statistical Quality Control by Montgomery) and try to understand the examples and the concepts in the book. In addition you have to do several exercies in this book to reinforce this understanding. Studying some outlines, highlights and notes prepared by other people won't help you much.
Sacred Book on SQC.......2007-01-12
If you are looking to be well versed on the principle of Statistical Quality Control, then you need this book.
Great SPC book.......2004-08-14
Used this book in a graduate level course on SPC. The book and the excercises were interesting and highly informative, as are all of Dr. Montgomery's numerous texts. Most concepts are backed up with liberal examples to help understand the theory and cement the concept and their practical applications, and run the whole gamut from management to electrical engineering problems. Many of the tables in the back of the book, such as the random number table, are outdated due to computers, however these may have been dropped in the new version of the text.
good book worst service.......2004-06-30
the book is very good ..no doubt but the service is aweful.
1. on the website they show it is a hardcover book and so i ordered for it but got a soft cover book ...now i have to worry about return or refunds etc...
2. had to wait for 3 weeks to get the book.
3. print quality aweful ...the original book has good color print...the one i received for the same price has a black and white print with very thin see-through pages...
my advice would be to avoid abebooks.com through amazon if possible because the same book is listed for $ 33 on their own website and here they sell it for $ 41 ...so waste ur money if u want.
Everything You Ever Wanted to Know about SPC.......2003-09-12
As the developer of the QI Macros SPC Software for Excel, customers often call with exotic questions about statistical methods for quality control.
Montgomery's book, more often than not, is the one I turn to for answers that I can't seem to find anywhere else. Even if I do find the answer in another book, it's always easier to understand in Montgomery's. The book is written in a way that makes seemingly incomprehensible statistics understandable. And there are plenty of examples.
If you're looking for a book to help you implement quality control in a small business, Montgomery's book is a bit too much, so you might consider my book on the Small Business Guerrilla Guide to Six Sigma or Six Sigma Simplified.
Book Description
This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.
Customer Reviews:
A best book on Statistical Pattern Recognition.......2005-09-13
Multivariate analysis is borrowed to name a NEW subject, Statistical Pattern Recognition (SPR). Many statisticians think it unfair or a shame. In spite of these, it is a good reference book of SPR. :-)
[1] Many contents of this book can be found in any graduate textbook of Multivariate Analysis, for instance, Fisher's linear disciminant, etc.
[2] The book is badly printed. Why not using LaTeX?
[3] Guassian distribution is assumed here and there.
[4] It may be good as a reference book, but definitely not as a textbook.
Standard reference and a classic text but with flaws.......2004-01-20
I do not like to consult this book for the following, quite superficial reason. The book is sloppily produced and proofread
(and the fault is [probably] mainly the publisher's instead of the author's). This manifests itself, e.g., as follows
(1) the typography is flawed (the equations hurt at least my eyes);
(2) at its each appearance, the all-important >
< -sign goes the wrong way.
good coverage for engineers.......2000-08-04
Fukunaga is a standard source for pattern recognition methods often cited in the engineering literature. Covers parametric (particularly linear and quadratic discriminant algorithms) and nonparametric methods (density estimation). It is designed for and popular with engineers. When I was working at Nichols Research Corporation Fukunaga's papers and this book (earlier edition) were often cited as sources to justify the algorithms we used for discrimination problems. In fact Fukunaga had been a consultant to the company (used primarily by the Boston branch of the company where the KENN algorithms were developed). It is a reputable source. I still like Duda and Hart (1972) for good explanations of the fundamental concepts. For statisticians McLachlan's book is now far and away the best source.
Standard Reference in the Field.......2000-04-06
If you are writing a machine learning paper, and need to cite something to support an argument, you can almost always cite Fukunaga. This work is a standard reference in the field. The presentation of most material is very terse, but that is great if you already have a good feel for the material and need to look up some details about some algorithm or technique. There isn't much about neural networks here, but for the rest of the pattern recognition techniques, this is almost always the first place to start. Another strong point for this book is the use of realistic examples, which illustrate many of the statistical techniques.
Customer Reviews:
Overall Best Work for Study of Educational Research Methods.......2006-07-07
As a university instructor who has used this text, I would recommend it for its thoroughness and attention to detail in the teaching of educational research methods. Most students are intimidated by research courses. However, this book lays out the reasons for research and the ways of approaching research problems in a step-by-step fashion that is both scholarly and common sense. It is also a great resource to have on one's library shelf. I highly recommend it it for graduate research courses.
Useful.......2005-04-03
If a person is doing a thesis, or disertation, then this book will answer questions about each of the 5 chapters and all those little details that a not taught but are required by your committee.
Book Description
This non-technical, hands-on introductory text is supported by up-to-date technology to augment students' comprehension and interpretation of both qualitative and quantitative techniques in educational research methods. This non-technical, hands-on introductory text helps students clearly understand and apply research concepts. This text helps readers learn how to prepare a research plan, gather and analyze data, address research questions and hypotheses, and organize a report of their projects. Pre-service educators or anyone interested in learning more about educational research.
Customer Reviews:
An excellent, clearly-written book.......2007-07-24
I think this book is a gem! It's clearly written in a step-by-step way that is extremely helpful in this course. I really appreciate the sample research proposals and the examples. This book helped me prepare for my own research project.
Statistics a Pre-Requisite.......2004-06-01
As a graduate student with no formal training in statistics, the authors jump head-long into discussions of educational statistics beyond the pervue of the course for which this book was intended. Some good descriptions, but other texts are more appropriate.
Errors abound.......2002-09-20
I was very disappointed with this textbook. The opening chapter is misleading as it only presents the quantitative view of research (even though the book does include a later chapter on ethnography). And too many errors! The statistics sections are unreliable and not useful to students; the appendix, in particular, contains errors and misleading information.
In my personal opinion, I caution people from relying on the information in the textbook.
An excellent text.......2001-05-11
I have used this book for three years to instruct individuals in a masters degree program. The book is clear, easy to read, and easy to understand - quite a feat for a book about research and statistics! Most educators are intimidated by texts on educational research, but this book is readable and makes sense!
Book Description
Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
Customer Reviews:
It is a good introduction book.......2007-05-22
This book is designed for people who do not have have background in bootstrap. I found that it is easy to read and understand. You could follow the examples of this book and directly to the "R". Reader should read this book before going to read the "Bootstrap Methods and Their Application".
Dirty your hands and you will get a lot from this book.
introduction to bootstrap.......2006-03-24
As a physician I was looking for an introductory text on bootstrapping and comparative methods. This book was useful to me to get an impression. Some mathematical background is needed.
A great book to learn the Bootstrap method from.......2004-02-05
This is the best book to learn about the bootstrap. Clear style, no empty verbiage, good problems, excellent examples are some of the qualities that make this exposition of Bootstrap great. The math level is minimal - some basic statistics (perhaps at the level of Wackerly et al's book) - is all that's required.
Not for Engineers.......2002-08-07
This book provides a good coverage of the very useful bootstrap method. However, post-graduation as an engineer, I find that the method is neither well known nor happily accepted by engineers outside of academia. In the corporate world, bootstrapping is left up to degreed statisticians, as this is what management trusts. As a mechanical engineer, I find that simpler statistical techniques, even if they include broad assumptions, are much more widely accepted. If you are an engineer, leave this up to the statisticians. If you are a statistician, this book is an acceptable source for learning bootstrap.
Great introduction by the originator of the bootstrap.......1998-07-16
Brad Efron wrote the key paper rediscovering the bootstrap and putting it in its proper place with other resampling techniques in his famous 1979 paper in the Annals of Statistics. His work was a breakthrough that has now led to hundreds of other publications and several books on the bootstrap and more general resampling procedures by himself, his students and many other statisticians. In fact I am working on a book with goals similar to what he and Rob Tibshirani achieve in this monograph. It is a concise and accurate presentation of the bootstrap and its wide variety of applications and is very much up to the state-of-the-art in this rapidly growing area of statistics. It is written in an intuitive fashion and avoids much of the mathematics (Edgeworth expansions etc.) which are needed to provide formal proof that the bootstrap does what it is intended to do. Provides most of the important references up through 1993. For a similar treatment that is more current, see Davison and Hinkley (1997). Bootstrap Methods and their Application. Those interested in the theory and formal mathematics should consult Hall (1992). The Bootstrap and Edgeworth Expansion.
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General
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Student Solutions Manual for Mendenhall/Beaver/Beaver's Introduction to Probability and Statistics, 12th
Data Analysis with Microsoft Excel: Updated for Office XP (with CD-ROM)
Human Resource Strategy: A Behavioral Perspective for the General Manager
Managerial Accounting: Creating Value in a Dynamic Business Environment w/PowerWeb/OLC
Mathematics: A Concise History and Philosophy (Undergraduate Texts in Mathematics / Readings in Mathematics)
iLrn? Student Homework for Mendenhall/Beaver/Beaver's Introduction to Probability and Statistics, 12th
