Reviews (1)

Terrible book
This book is a farce! This book is terrible! The author doesn't go straight to the point when presenting his information, and the excersices he presents doesn't match the examples he provides(and the examples are far too few and his words are puff with little relevent content). I guess he wants the institution or individual to purchase the separate 'Solutions Manual' so he'll get bigger profits.

Maybe if you're an engineering student, this book will be a piece of cake since you already have a strong math background. But if you have to endure this book, make sure that your instructor knows how to teach, you know - really decipher the information and make it very deliverable to you as a student. If your instructor doesn't know how to do this and tries to teach it to you as if you had a degree in engineering, just withdraw from the class....you're instructor is a egotistical farce as well..

What ever happened to teachers who REALLY want to teach?

If you want to learn statistics on your own, buy the book "Statistics for the Utterly Confused" by Lloyd Jaisingh, Ph.D. He delivers the content fairly well. Also, go to tutoring if your campus provides it. ... Read more

Book Description

A best-selling introduction to statistical analysis in the social sciences written to be understandable to a broad range of readers, particularly those without a strong background in mathematics. This book provides the right balance of conceptual understanding and step-by-step computational techniques. It also offers clear, logical explanations for the rationale and use of statistical methods in social research. Designed for those entering a field of sociological study and wanting to learn statistical analysis. ... Read more

Reviews (2)

Best Basic Statistical Text for Social or Policy Sciences
Excellent description of the purpose and procedures of basic statistical techniques. Uses simplified formulas, and does not get lost in the math. Easy to read and understand. Good for social science and public policy courses, including public administration. Only drawback: does not effectively incorporate computer applications.

Jack Levin, Elementary statistics in Social research
One of the best statistics books I can think of for social scientists who are not well aquainted with statistical procedures. The book is structured in several chapters, each concentrating on one statistical problem. In the first part of each chapter the theoretical background is given, followed by examples. Then, other examples are given, so that it becomes easily understandable how to correctly use the formulas respectively when they can't be used. Finally, there is a part of exercises where the reader may apply his new knowledge, before proceeding to the next chapter. However, it is just an introduction, not dealing with more complex statistical problems. Very recommendable for anyone who needs a solid basic knowledge in statistic or who wants how to start processing existing data. ... Read more

Book Description

This brief version of Gravetter and Wallnau's proven best-seller offers the straightforward instruction, accuracy, built-in learning aids, and wealth of real-world examples that professors AND students have come to appreciate. The authors take time to explain statistical procedures so that students can go beyond memorizing formulas and gain a conceptual understanding of statistics.By integrating applications to ensure that even students with a weak background in mathematics can understand statistics, the authors skillfully demonstrate that having an understanding of statistical procedures help them comprehend published findings, and become savvy consumers of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support instructors with class preparation and testing. ... Read more

Reviews (2)

One of the Best Intro to Stats Texts
Having taken statistics before, I know a good book when I see one. This is hands down, one of the best intro to stats book. Unlike other stats textbooks, Essentials gives you the information in a concise manner accompanied by varied step-by-step examples towards understanding all the statistical tests. Psychology students have it lucky to have a book like this.

Understandable Statistics at Last!
This is the first statistics textbook that I have actually understood and enjoyed, and I have read many of them. The authors take students through the material step by step and do not make assumptions about prior knowledge. The charts and examples are very helpful and clearly presented. As textbooks go, this is the best! ... Read more

Book Description

This Seventh Edition maintains the all the winning qualities that have made A FIRST COURSE IN DIFFERENTIAL EQUATIONS WITH MODELING APPLICATIONS a best-seller over the years. Written in a straightforward, helpful, not-too-theoretical manner Zill's approach keeps students with differing levels firmly in mind.The new edition strikes a perfect balance between the teaching of traditional content and the incorporation of evolving technology. ... Read more

Reviews (15)

good for non-math people
Easy to follow examples. Great conceptual models. This book has plenty of useful applications in the real world: physics, biology, engineering, and chemistry. There is no math flood to drown non-math students. Great intro to Ordinary Diff. Eq.

decent
It's been a long time since I had this book for a course (so take this with a grain of salt...), & I had a pretty good instructor, but this book still helped reinforce the ideas. I don't think it makes a difference whether a book has a solution manual, just plug your solution into the equation to check your answer. A solution manual for a differential equations text is a bit superfluous, IMO, since solutions don't all look the same. Another good text is the one by Rainville/Bedient.

Lacking pedagogical stimuli or skill ?
Maybe this was an attempt to be unique in presentation of the subject ; yet , contorting paraphrased material into a potato - salad of words is an obvious sign of bad technical writing ; perhaps , poor confidence in subject , or who knows what ?!?! . The layout of this text is the worst I've seen in a mathematics text -- both , calculations and " explanations " are blobbed as run - on , rambling sentences contained into page - sized paragraphs ; unbearable amount of conceptual abstraction almost at every definition of critical importance . There lies a clue that descriptive terms were chosen by dictionary research of most subtle synonyms of such; moreover , an overuse of unnecessary adjectives , of same descent , to increment the confusing flush . This text is obviously designed to be NOT USER FRIENDLY on purpose !! .
To me , that defeats the whole goal of even attempting to write books for students . This one should , in its full definition , be banned from all pedagogical institutions -- those , where are those with a desire to learn . I personally did not encounter difficulty of solving this " book's " chapter problems ; however, due to the diffused presentation of theory , am still lacking satisfaction of conceptual clarity of such a rich subject .

An Enjoyable Book Overall
I enjoyed using this book in my DiffEq class. It gives lots of examples and a variety of homework problems. It proved to be very useful for me.

Do not recommend
I am using this book for my D.E. class. The solutions manual [is bad], solving only every third problem. I found the reading quite difficult to understand and the pages are boring and bland!!! ... Read more

Book Description

This work brings together, in a ready-access encyclopedic format, theories, methods, applications, and historical background in the statistical sciences. More than 4,000 entries by leading statisticians, mathematicians, educators, and major figures in the development of statistics cover all the principle subfields including probability theory, statistical distribution theory, computational methods, sampling survey methods, decision theory sequential analysis, and multivariable analysis. ... Read more

Book Description

If you have ever looked for P-values by shopping at P mart, tried to watch the Bernoulli Trails on "People's Court," or think that the standard deviation is a criminal offense in six states, then you need The Cartoon Guide to Statistics to put you on the road to statistical literacy.

The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trails, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more--all explained in simple, clear, and yes, funny illustrations. Never again will you order the Poisson Distribution in a French restaurant! ... Read more

Reviews (33)

I'm a Cartoon Guide Addict now...
Have you ever chuckled while reading your mathbook? Ever laughed out loud while crunching numbers? Don't worry--neither had I until I read this book. And any book that makes me smile when I'm doing math has got to be a winner.

Yes, Gonick has done it again. I bought the CG-genetics a while back, and loved it. So when I went hunting for a good 'refresher' stats book, I picked up this one.

I wasn't disappointed. Gonick (et al) has great talent for presenting information in a way that almost fools you into thinking you're not learning, but rather, having fun. And although this book wasn't as "easy" to get into as his Genetics book, I believe it's because I'm less familiar with this subject.

Careful though--as others have mentioned, you can't be fooled into thinking this book is THE way to learn statistics. You have to be pretty comfortable with algebra, and pretty determined to read through the book in order to take anything away from it. And don't try this book as a stand-alone or you'll end up with the same frustration you'd have with a college textbook.

A Good Introduction
"The Cartoon Guide to Statistics" by Larry Gonick and Woollcott Smith was published in 1993. This book is a good introductory level look at Statistics. The authors cover what Statistics is, what the history of the subject is, and a look at some theories, terms, and applications of the subject.

The weakness of the book is that there are a lot of formulas given, and not enough discussion of the formulas, so one would need to use other statistics texts to supplement the material, so this book cannot stand alone in that respect. On the other hand, if one is just trying to get an overview, there is a lot to skip over. The authors do make fun of the formulas, and the amount of math so those that are looking for an overview may enjoy the humorous presentation. There is also a lot to do with the subject that the book covers. It does cover probabilities, but when it comes to distributions it really focuses on Standard Normal distributions. I don't believe it ever mentions Uniform, Poisson, or other types of distributions which most statistic courses do cover.

The best part of the book is the examples, some of which are carried through for several chapters to help the reader better understand the subject. Although, even with the examples they are a bit inconsistent in how complete they are. For example, in one case they started to discuss the use of statistics to compare the salaries of male and female employees in the same job, but they never completed the discussion. The examples of racial bias in jury selection, and the gas mileage comparison of two different types of gas are much better. This is a decent book, but not up to the level of Gonick's excellent "Cartoon History of the Universe" series, and not strong enough to give it more than three stars.

Very funny and cute book. I love it!
If you want to learn complicated things like statistics, but are feeling quite overwhelmed by the complexity, I highly recommend you learn visually from a book like this. Larry has a great sense of humor and is a creative genius.

Zev Saftlas, Author of Motivation That Works: How to Get Motivated and Stay Motivated

Best intro to stats around
I read this book because I had to take a Linear Regression stats class, and I lacked the pre-requisite knowledge of basic statistics. After attempting to skim some of the 800 page intro books in the library, I decided to give this one a try.

It contains everything you need to know about introductory statistics. Some things are a little unclear, but this stems from the fact that the author's did not want to burden the reader with the derivations of the basic equations. So at the expense of some clarity, they cut out a lot of junk that you will never need, probably even if your major is statistics.

So even though you may need to supplement this book with a more detailed book, and even though the cartoons are far from funny, I give this book 5 stars because it is simply the best intro that you will find. You could easily get through an introductory college course with this book alone, and its a shame more courses don't try to do that.

Book Got Me Through College
I am math phobic and taking Statistics in college made me wonder if I was one of those people who "wasn't cut-out for college". But I got this book and it made statistics fun and a lot less intimidating. After college, an interviewer asked me about Bayes Theorum and I immediately pictured the illustration from the book! Recently, while studying for the GMAT, I recalled the fun lessons from the book - especially probability and nailed that section of the test.
This would be great for High School or college students or ANYONE who is intimidated by math or stats. ... Read more

Book Description

Gravetter and Wallnau's proven best-seller offers the straightforward instruction, accuracy, built-in learning aids, and wealth of real-world examples that professors AND students have come to appreciate. The authors integrate applications to ensure that even students with a weak background in mathematics can achieve mastery of statistical concepts. They skillfully demonstrate that having an understanding of statistical procedures will help them not only understand published findings, but also become savvy consumers of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support instructors with class preparation and testing. ... Read more

Reviews (7)

Gravetter's Statistics book
This is one of the clearest books on introductory Statistics that I have read. Extremely logically written in a straight forward style. If you can't grasp Statistics using this book...try a different pursuit in college. Every concept is precisely explained and one subject builds upon the next. Gravetter provides one example after another in an attempt to hammer the concepts home...and a successful one I might add. This book also provides a solid foundation for the 1st half of an advanced, Stats II course.

This book has saved my life
I am about half way through this book and I actually understand, maybe even a bit excited about statistics. This book is definetly the best math/statisics textbook I have ever used. If you have hidden in fear from math but want to go to grad school, pick up a copy of this and you will not regret it.

A must buy!
This is great book for learning statistics. The best I've seen so far. Statistics is a subject I hate, but this book has given me hope. I know use it as a supplement for other textbooks. It was a book that was written with the student in mind. I am in a class with an awful stats book now, Statistical Methods for Psychology. But, the Statistics for the Behavioral Sciences text will be a permanent fixture on my shelf and I recommend it often. I will continue to look for textbooks written by these guys. Thanks, you made one of my semesters much better.

statistics for the math phobics
OK, here it is: I am a math phobic, have been all my life, as long as I can remember myself! So, when I started studying psychology as a second degree, I was kind of anxious about taking all kinds of statistics courses: it seems that statistics are a major part of any psychology degree, & so it was important for me to learn them well, from the beginning. Well, with this book (which I shopped around for, looking for the best introductory book on the subject) my math-phobia has not disappeared, but is slowly & surely getting smaller & smaller. This is a textbook that guides you, step by step, so you can understand all the basic concepts of statistics, without feeling you're making an effort. Lots of problem-solving & learning checks help, lots of revision at the end of each chapter...the book is organized in an excellent & thoughtful way, perfect for a student who will take the time sto study (it covers almost everything) but who wants to do it in an organized way.

Kudos to these guys!!!
I used an older copy of this book as an undergrad and was asked by a fellow doctoral student what I might recommend for use as a good stats book for the "stat phobic" ... Hands down, I say that THIS is the book to use. I've used thinner stats books that pretend to be cute. But if "cute" is not what you need, and you need to learn the stuff as well as reference the stuff. This is the book for you.

I suppose I ought to update my copy ;-) mine is dog eared!

Need stats? Buy this book to learn. Good stuff! ... Read more

Book Description

Renowned for thoroughness and accessibility, this book offers a challenging and enjoyable study of linear algebra that is infused with an abundance of applications. Balancing coverage of mathematical theory and applied topics, concepts are explained with precision so that all readers can understand the material. Worked examples are heavily integrated into each chapter. The book stresses the important role geometry and visualization play in understanding the subject.

Reviews (13)

Proofs: Simple, but not rigorous
Background: Electrical engineering grad student. Lots of math. Prior linear algebra course.

Reason to read book: Wanted a text to review proofs of many of the important theorems that are used in the matrix formulation of quantum mechanics. Stuff like why Hermitian matrices provide orthogonal eigenvectors and real eigenvalues. Also, wanted a review of vector spaces, basis sets, etc. That means pretty much most of the book.

How much of the book I've studied: Most of the proofs in the entire book. Some of the worked problems. None of the exercises.

Analysis: The book provides a comprehensive list of the useful proofs. However, the proofs are simple but not rigorous. They give you good insight on why the theorems are what they are, but they don't remove all doubt as to their validity.

Good Book for the Most Part
Overall, I thought was well laid out. I would probably like to see more practical application of linear algebra to real world problems.

don't waste your money
If you buy this book then get used to phrases such as: "It can easly be seen that...." and "It can be shown that..." and let us not forget everyone's favorite "...which is left as an exercise for the reader." You will see at least one of these phrases in every section (yes section not chapter). ... For [the money] I think Leon could work out just 1 example in detail. Fortunately there is enough information on the internet you won't need to read this book, instead just carry it around so your professor thinks your using it (although it makes a great door stop when you done with the class). Overall I think that 1 star is too much for this but Amazon won't let me give it 0 stars.

Starts Off Great, Wears Down
My background: Computer science / mathematics undergraduate with experience in calculus, discrete mathematics, and differential equations

Leon's text on linear algebra isn't bad, but there is room for improvement. Chapters 1, 2, and 3 do a good job of introducing the basic concepts of linear algebra, including matrix row operations, determinants, and linear independence. The book seems to lose clarity beginning in Chapter 4. The concepts become more abstract and Leon's notation interferes with the ability to clearly understand what he is talking about when it comes to linear transformations and issues regarding R(A) and orthogonality. Very important results are frequently understated as well. In a few cases, there aren't enough examples to go around - especially in Chapters 4 and 5. It is ironic compared to the relative overexplanation found in Chapter 1, for example.

Another qualm I have with this text is the chapter review sections, which are limited to MATLAB exercises and simple true/false questions. I think these sections need actual math problems devoted to them that force the reader to combine and use concepts learned in the preceeding chapter, rather than overly simple true/false questions.

On the other hand, the homework problems the book offers for each section are fairly worded and interesting to solve. There is an answer section, of course, for the odd numbered exercises. Also, there are several "Application" sections that demonstrate how linear algebra is used in real-life scenarios that provide a relevance to this study, just so the casual student doesn't wind up wondering "Where am I ever going to use this?"

The book is just okay, but it needs a really good professor to go along with it and elaborate on the concepts Leon either understates or fails to present clearly. On a side note, my book is only two years old (I bought it like new) and the binding is already falling apart.

Flawed, but conceptually complete.
I used this Linear Algebra text in an undergraduate Linear Algebra course. Before I get to the problems of the text (and there are numerous) let me just say that it is conceptually complete, in that every topic in linear algebra is given very close attention. (Eigenvectors/Eignenvalues were given a very elegant treatment, as an example) All the concepts are well organized and also some applications are thrown in to the mix.

With the above statement, it seems that this book has everything going for it to be a fantastic linear algebra book. Unfortunately, it hits some pitfalls. Although its conceptually complete, it is very dense. ( a common math textbook pitfall) Places where explanations could have been expanded quite a bit are not. Being a very dense math textbook leads to the next problem. Leon's notation is unneccasarily formal for an introductory linear algebra text. It is quite fustrating getting used to notation before you get to the key concepts. (His notation is not often explained well enough.) Although I got passed the overlyformal notation and got to the meaty concepts, I can completely sympathize with others who get stuck on it and have absolutely *NO* clue what the author is trying to say. Let's face it, not everyone taking Linear Algebra is a math major (I for one am a physics major and there were quite a few engineering majors in my class.)

Another pitfall of this book is the absolute decrepid writing style. Do not laugh when [someone] states that this book is boring and well "Just not fun..." because that statement is the truth! The writing style has a very sleep-inducing tone, which is a shame because linear algebra is a very important topic and an interesting one. (With far reaching applications.) It is very difficult to describe... get through the book without much trouble and you will see what we mean. The only concrete example I could think of is the mind-numbingly dry explanation of vector spaces in the third chapter.

In closing, this book does not need much to become a great linear algebra book. All the concepts are there, so the hard part is done. Hopefully Leon in the 6th edition will clean up the notation a bit and add some life into the explanations and writing style, this book could be an undergraduate linear algebra standard. ... Read more

Book Description

Now your students can become intelligent consumers of scientific research, without being overwhelmed by the statistics! Jaccard and Becker's text teaches students the basic skills for analyzing data and helps them become intelligent consumers of scientific information. Praised for its real-life applications, the text tells students when to use a particular statistic, why they should use it, and how the statistic should be computed and interpreted.Because many students, given a set of data, cannot determine where to begin in answering relevant research questions, the authors explicate the issues involved in selecting a statistical test. Each statistical technique is introduced by giving instances where the test is most typically applied followed by an interesting research example (each example is taken from psychology literature). ... Read more

Reviews (2)

An Excellent Introduction
The book is up-to-date and effectively presents the basic concepts. Deals with current power and sphericity concerns. Example SPSS-keyed analyses and APA-format results sections are especially valuable for research training. Uses post-hoc Tukey HSD test. Separate nonparametric chapters. The authors know their material (not always the case with statistics texts) and they provide a solid (higher-level) introduction. Good selection of topics and fairly thorough. Perhaps a bit wordy at times. One of the best available introductions. From a long-time teacher of statistics with no connection to authors.

The Best Introductory Text for Today's Students
Jaccard and Becker's preface says it all:

"Introductory statistics, unlike content areas in the behavioral sciences, does not become dated quickly. Many of the concepts taught ten years ago are still relevant today. So why another text?

....Most introductory statistics texts fail to integrate sufficiently the subject matter of statistics with what students will encounter in the behavioral science journals. A statistics course should not only teach students basic skills for analyzing data but also make them intelligent consumers of scientific information.

....Because of the way chapters and exercises are organized in most texts, students are essentially told which statistical procedure to use on a given set of data. This state of affairs is simply unrealistic. It is just as important to teach students when to use a particular statistic and why it should be used as it is to teach them how to compute and interpret the statistic.

....A common complaint among students is that statistics is irrelevant and boring. This view is fostered, in part, by the tendency of statistic texts to use examples and exercises that are irrelevant and boring. Yet, it is possible to provide interesting applications of statistics (which this text does successfully).

....In the present book, a unifying structure is provided [(1)in contrast with other texts and (2) in order to provide students with conceptual relationships among the various stastical analyses].

....The book emphasizes a conceptual understanding of statistics [rather than the chosen outdated computational emphasis of the vast majority].

....Another unique characteristic of this text is a chapter on research methods.

....Appendixes to several chapters explain in more detail certain advanced concepts referred to in the body of the text [for advanced students].

....[The material covered is systematically thorough, allowing the professor to choose a customized curriculum and providing the student with a tremendous resource for further study and reference long after the course]." (pp. xiii-xvi)

The book triumphs as the most relevant introductory text on the market today. ... Read more

Book Description

Updated to reflect the latest technological advances in statistical tools, this solid text presents ideas and concepts more clearly for students who have little or no background in statistics. The Tenth Edition retains all the elements and style that educators nationwide have come to expect—clear prose, excellent problems and precise presentation of mathematics involved—while eliminating some of the computational drudgery. The seamless integration of technology gives professors multiple teaching options.The volume outlines all aspects of summarizing data, possibilities and probabilities, rules of probability, expectations and decisions, distribution, sampling, problems of estimation, tests of hypotheses, analysis of variance, regression, correlation and nonparametric tests.For Statistics professionals and others using elementary statistics. ... Read more

Book Description

A brief introduction to business statistics that balances a conceptual understanding of statistics with the real-world application of statistical methodology.This essentials version features selected core topics from the authors' market-leading Statistics for Business and Economics, 8th, presented in 13 chapters. It includes the highly-regarded strengths of the longer text, including the problem-scenario approach that uses real-world examples to introduce statistical techniques.Methods, Applications, and Self-Test exercises include hundreds of problems based on real data.Examples and exercises throughout focus on ways that statistics contribute to improving the quality of products and services. This text can also be computer integrated at the discretion of the instructor. Instruction for data analysis based on Microsoft Excel and Minitab is included in appendices of appropriate chapters. Case problems are also provided with the text, with data sets available on disk for both Minitab and Excel formats. ... Read more

Reviews (2)

Great Text!!
The information in this book is clear-cut, concise, and easy to read. Easily understandable examples are given for the various statistical formulas, and extras like z-score value charts and the like help a lot. If you have a talented instructor leading your Stats class (like I did) in addition to this text, you will be sure to ace this course (like I did)!

P.S.: If you happen to be an Information Systems/Information Technology major (such as myself) DO NOT RE-SELL THIS BOOK! You will need the information in this book in your future Info Systems courses, and you will definitely realize the TRUE value of this text!

A useful book. . .
. . .by authors who remember that they are writing for persons who are NOT professional mathematicians.

In today's world, frequently persons enter the business profession from a background in something other than what in the past might have been considered traditional avenues. Not all business textbooks recognize this (see my review for "Mathematical Applications")! However, this book seems to be an exception.

The material is presented in a logical format; key formulae are highlighted and set off from the rest of the text; and in-depth business examples are given in each chapter, demonstrating the particular statistical tools to be taught.

A useful and recommended volume. ... Read more

Book Description

Here is a much-needed professional book that will instruct readers in the many newmethodologies now at their disposal to make the best use of longitudinal data. This book explains how to select an appropriate method given a research question, including how to use both individual growth modeling and survival analysis. Throughout the chapters, the authors employ many cases and examples from a variety of disciplines, covering multilevel models, curvilinear and discontinuous change, in addition to discrete-time hazard models, continuous-time event occurrence, and Cox regression models. Using Longitudinal Data is a unique contribution to the literature on research methods and will be useful to a wide range of behavioral and social science researchers. ... Read more

Reviews (2)

Great if you really want to do longitudinal data analysis
One of the great features of this book is that it is addressed to the empirical researcher and it really tells you how to conduct good data-analysis with longitudinal data. It doesn't push one particular piece of software, either, but uses a variety of different software packages. The book is really easy to read, and clearly explained -- and, there's so much in it!

Best thing since sliced bread!
This is a great book, it tells you in a straightforward way how to analyze your longitudinal data to answer questions of critical importance in the social sciences. It's not wedded to one particular piece of software, as many books on statistical topics are, but uses examples of real data and different software (HLM, MLwiN, SAS, Stata) to conduct the analyses. An absolute must for the researcher who collects longitudinal data. ... Read more

Reviews (10)

Good intro for self-study
This is an introductory book. It also fits in introductory level of Mathematical Statistics. The prerequisites are introductory calculus and linear algebra. Most theorems are proved in calculus style but there are some gIt can be shownsh that are not proved. So some readers may not be satisfied with the book, especially Math majors.

Logical steps are shown in detail; else logical gaps are contained within a level such that a first time reader can fill in the gap with a pencil and paper. Occasional mix with Bayesian perspective is also a feature. Answers to odd-numbered exercises are provided except ones that ask derivations and proofs. Exercises that require some tricks are provided with hints. In these respects, this textbook is suitable for self-study.

Upon completion of the entire material, I feel concepts are developed well up to Hypothesis testing Chapter 8 where the presentation of material reaches climax and its level of exposition is somewhat higher than other chapters. Thereafter, simple linear regression is treated in detail, but coverage and detail of materials seem to deteriorate from the following general regression section, nonparametrics and thereafter. Kolmogorov-Smirnov Tests section is treated nicely though. Anova section lacks in coverage. The new simulation chapter is presented more like a demonstration rather than an introduction.

I have never seen the previous 2nd edition (unfortunately Dr. Degroot is no longer with us), but according to the preface of this 3rd edition, Dr. Schervish describes 8 major changes from the previous edition. Notable are some material removed from the previous (likelihood principle, Gauss-Markov theorem, and stepwise regression), some added (lognormal distribution, quantiles, prediction and prediction intervals, improper priors, Bayes test, power functions, M-estimators, residual plots in linear models and Bayesian analysis of simple linear regression), more exercises and examples, special notes, introduction and summary to each section, and so on. I find the last in the list is somewhat disturbing, especially introduction parts that are often redundant with the very next paragraph. On the other hand, I find that special notes provide good insights.

I wish they included introduction to Statistical Decision theory, full coverage of regression analysis to be usable such as diagnosis, transformation and variable selection, coverage of Multivariate Normal distribution, more coverage and depth in nonparametrics and simulation, and lists of recommended readings for further study at the end of each section with comments.

There are a noticeable number of typos as of this first printing I have. I sent suggestions for typos and was impressed that Dr. Schervish updated errata list within a few days at his homepage. I wish all authors were like him being responsible.

How to remain a classic
This new editon mantains the features that have made it a classical for a long time:

- Clearly written;
- Tough subjects are made understandable even for beginners;
- Classical results are presented rigorously after a bunch of examples;
- Many exercises, well posed, whose solutions are found in the end of the book (just even exercises).

This books has been long without a revision and we can see easily that it is much better. The main improvement is the computational treatment of Statistics in terms of theory and exercises. And, of course, it is visually more pleasant.

You may think this is little, though. But, a classical is so well done that there is not much more to do. This is the case. So the second author adds what was difficult when DeGroot first wrote it (computational stuff, as I said) and suppress what is out of fashion or has been overcome.

I think it is still the best option to start out to learn Statistics.

Cannot follow the logic --2nd Ed.
First of all I don't know how the 3rd and 2nd Edition differ.

I am trying to learn Probability and Statistics on my own, and I find it very difficult with this book.

The book does do somethings well. It does explain concepts better than what I have read so far (Schaum's). However, in the sections on combinatorics, especially, and thereafter I cannot follow the logic. I read an example problem, the solution is given immediately with little explanation as to how. The author says the bare minimum e.g. here n=52 and k=13. I have seen the combinatoric calculations, that are the solutions, in a multitude of ways, with sums in the numerator, products in the numerator, and it is not at all obvious as to why. There is insufficient discussion in the solution.

Then in working the exercises, there is nonuniform quality with the even-number solutions. Some answers just have a number, others have the formula, and some have numbers with factorials so you can kind of guess what the author did. But in the case where there is just a number, you can't.

Can you learn from this book? Sure you can, but my prediction (after reading Ch. 1) is that it's about as difficult as trying to learn a programming language by looking at syntax and running the code, having no programming experience.

Great stats book
I used to hate statistics, but this book is pretty clear and concise, and gets the idea across very quickly and easily. The exercise questions were of reasonable difficulty, and are put forth in a clear manner, unlike other books which present the questions in round-about manner. The examples tend to follow on or build upon from the earlier chapters, so it is best to tackle the book in the order as prescribed by the chapters.

best introduction to the field
I have looked at many introductory books to probability and statistics and this one is definitely the best. It is very clear and readable and yet gets to pretty advanced stuff. ... Read more

Book Description

This self-teaching volume provides extremely readable coverage of the principles of finite mathematics and their applications in business, social science, and the life sciences. Topics are presented in a straight-forward, interesting manner (with topics from elementary mathematics reviewed as the need for them arises), and an abundance of worked examples with computational details, practice problems, exercises, chapter self-assessment tests, and reviews of fundamental concepts allow readers to work through the material confidently at their own pace. Contains many examples similar to those found on CPA, GMAT, and GRE Economics exams. Features optional, explicitly detailed use of graphing calculators, electronic spreadsheets, and mathematical software, wherever relevant.Linear Equations and Straight Lines. Matrices. Linear Programming, A Geometric Approach. The Simplex Method. Sets and Counting. Probability. Probability and Statistics. Markov Processes. The Theory of Games. The Mathematics of Finance. Difference Equations and Mathematical Models. Logic. Graphs.For anyone who needs to get up to speed with the applications of mathematics in business, social sciences, or life sciences. ... Read more

Reviews (13)

Used in Graduate Class on Probability and Random Processes
I used this book for a graduate class in Probaility and Random Processes and we covered every chapter. I gave the book three stars based on other probability books I have used, but compared to other engineering books I would rate it lower.

I feel main problem with the book is the examples not very helpful in solving the 100+ problems that accompany each chapter. Most of the examples were just useless explanations graphs. The book also seems to gloss over some of the important concepts needed to solve the homework problems. The only homework problems that I found useful were the MATLAB examples. I would recommend doing these problems even if they are not assigned.

The book also does a poor job covering applications, especially in the later chapters on random processes. I would have been interested in more signal processing and communications applications, the main reason I took a course on probability and random processes.

As far a background for a person using this book, I would recommend the person be graduate student with a solid math background.

What a terrible book
I am a graduate student using this book in a class. I would really like to warn other people from using it.

The book describes everything with a lot of examples. As a result of this you do not get a basic understanding, but rather some examples that you can adapt and use for a problem that you have to solve.

It is like learning that a wheel is turning because you might turn it with your hand, rather than because you are applying a torque to it. Or that a lamp is turned on because you might hit the switch, rather than because a current flows through it.

For some reason everything has to be described with CDFs instead of PDFs in the book. It seems like PDFs are something that is difficult to imagine for the author.

I once had a teacher in a class, and a book containing a lot of examples like this one. He claimed that he could write everything the book contained on 2 pages - He was right!! I think the same thing could be done with this book.

Do not choose this book. It is highly unrecommended.

I can't believe something like this even exists!
This book is just god awful. I think probablity theory is a very fascinating subject, however, I don't think this is a good book to learn it from.

Where do I begin:

-The biggest grip I have with this book is the problem set. The problems in this book are, literally, just plain hard. The author expects you to do problems,using the techniques they used in proving an actual theorem! I'm not talking about using the actual theorem, but the actual steps they used. I'm an undergrad in a graduate course, and most of the graduate students aren't even doing well on the homework assignments. I consider myself a pretty decent student. I was able to learn DSP using the Oppenheim book(with the aid of a teacher's solution manual of course). The problems in this book are harder than the problems in Oppenheim's DSP book(and I have a teachers solution manual for this prob. book). The bottomline is that 80-100 problems per chapter won't do anyone any good if they can't solve those problems.

-The author's notation is extremely weird, confusing, and downright bad.

-I just have the strangest feeling that the author is trying to make the students,whom are using the text, feel like they're stupid.

-This book is nine years old. I think the author should rewrite the text from scratch.

-My instructor is literally terrible, so I'm going through a lot of hell in this course.

-And finally, the author, when explaining the theory, uses alot of tedious reasoning and formulas when doing certain theorems. For example, when he's explaining the concept of a bernoulli distribution, the author uses the indicator function to explain the concept. This is not even needed to explain this concept(I have checked this several books, and this was not done), and it's a bit tedious and pointless to include it in the theory.

-My communication systems teacher told our class last semester, that learning from enigneering books is not a good way to learn material. This is all because the authors like to show off their intellectual skill and nothing more. They usually forget to include problems by the time of publishing, and have to delay the release of the book to include problems. And what do they include, diffcult problems, which are really not needed to learn introductory concepts.

Useful, non-rigorous reference
I used this book in a sophomore-level probability course for electrical engineers and I found the book a bit confusing at the time. The notation is somewhat awkward and examples are interleaved throughout general concepts, making it difficult to discern key ideas.

During my doctoral studies, I gained a different perspective. I consistently found the book to be a valuable starting point for many concepts and I now find the examples a quick way to brush up on elementary principles.

However, Leon-Garcia doesn't give a thorough approach to probability theory (there are essentially no theorems) and avoids set theory almost entirely. To really put my teeth into something, I would have to track down a more advanced text for any particular concept I was interested in. Basically, Leon-Garcia tries to seperate "Probability and Random Processes" from rigorous mathematics.... something similar to eating fat-free cheesecake.

so so book
I used this textbook for a junior level class. Frankly, although the book is good initially, the end of chapter problems are way too hard, especially in chapters 3,4,6 and 7. Also, much of the book is formula, which is a bit too much for undergrads. ... Read more

Book Description

Fundamental topics and new methods in time series analysis
Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described.
The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. Timely topics and recent results include:
* Value at Risk (VaR)
* High-frequency financial data analysis
* Markov Chain Monte Carlo (MCMC) methods
* Derivative pricing using jump diffusion with closed-form formulas
* VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process
* Multivariate volatility models with time-varying correlations
Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods. ... Read more

Reviews (3)

Analysis of Financial Time Series
This book is awesome. It starts with bedrock concepts needed for analysis of financial data and it takes the student up to the most recent and important techniques used in the industry today. However, if one expects to fully utilize this text, one should have at least one semester of applied econometrics or some equivalent course in statistics and continuous probability, although it will be practical to study the two topics concurrently.

A very practical book
This is not a reference book, and it's not about "big" theory either. It's pretty practical, and good for self study. You should have access to some econometric/statistical software (i.e. EViews, S-Plus, etc.) to fully understand this book.

Petition: please provide table of contents!
I want to see the table of contents of this book. How can the author and the publisher expect people to buy this book without providing the table of the contents?... ... Read more

Book Description

This is the most widely used mathematical statistics text at the top 200 universities in the United States. Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid undergraduate foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. ... Read more

Reviews (8)

Solid Presentation But Lacking Concision
The sixth edition of Math. Statistics w/ Applications is a solid book with good information. However, the form of presentation was not for me. The authors have chosen an explicative style which tends to be overly wordy.

When I begin to read a chapter, I tend to get frustrated and impatient because they either try to show you all the subtleties at once or give you a long-ass paragraph that can be said with one sentence. Thus, The most important stuff is buried in a mountain of over-whelming text.

I have ditched this book in favor of Ghahramani's "Fundamentals of Probability, Second Edition" for my Math Stat I class.

Best statistics book for econometricians
This book is a book on mathematical statistics and hence goes further than most entry-level statistics books, which mostly deal with business statistics. This book does not reinvent the wheel, but is goes further where other books end. You will find a mathematical explanation and theorems are proved as well. Soms more advanced topics are moment generating functions and power tests. The consequention is that the learning curve is steeper. At my university, econometrics students use this book, and they couldn't have made a better choice. Logically, since econometricians don't have enough on a book with only a minor focus on formulas.

Worst stat book ever
I work as an actuary, and I have passed the first actuarial exam (the calculus and stat exam with a <30% pass ratio). My friend uses this book for her stat class, and I have found it to be a terrible book.

I hope that any teacher reads this, and looks at the book before assigning it to a class.

There are very few examples of problems, very little discussion of theory, and it is structured in a way that does not allow you to easily reference other texts.

If you want a good text for challenging problems and relevant examples, try Hogg and Tanis.

A great book!
This is definitely one of the best introductory statistical books around. The writing is lucid and masterly, and includes a wide variety of topics. The authors have included an abundant number of well-chosen exercises and these cover a wide spectrum showing the application of statistics to the engineering, biological, etc., sciences. My only complaints are that there is not enough on residuals and influence in the chapter on regression; the use of the hat matrix in this context would have been most beneficial, in my opinion. Also I would have very much liked to see the Fisher information in inference and the Smith-Satterthwaite procedure in hypothesis testing included. Nonethless both students and instructors will find the book extremely useful and it gets my highest recommendations!

Three standard deviations from the mean...
As a student in Engineering Science at the University of Toronto who used "Introduction to Mathematical Statistics" by Rice as a textbook for a course on Probability and Statistics, I must say that my life would have been so much easier had I owned a copy of Wackerly's text. It is a concise, easy to follow, practical textbook that covers the material thoroughly while still presenting it in a most digestible form. ... Read more

Book Description

Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Categorical Data Analysis was among those chosen.

A valuable new edition of a standard reference.
"A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis."
-Statistics in Medicine on Categorical Data Analysis, First Edition

The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis.

Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of:

• Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects
• Stronger emphasis on logistic regression modeling of binary and multicategory data
• An appendix showing the use of SAS for conducting nearly all analyses in the book
• Prescriptions for how ordinal variables should be treated differently than nominal variables
• Discussion of exact small-sample procedures
• More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises

Reviews (3)

A classic, made even better
This is a very demanding, thorough, and clear description of just about everything anyone could want to know on the subject. The second edition is considerably more rigorous than the first. Agresti stresses that logistic models are one kind of generalized linear model. This offers solid connections to many other models, but places corresponding demands on the reader. In particular, Chapter 4 is difficult going, but might be skipped or skimmed on first reading.

Given the mathematical level and rigor, this is a remarkably clear book. Anyone who analyzes categorical data on a regular basis should read it and have it on his or her shelf.

Categorical Data Analysis
Book comes with great condition, although the shipping speed is somehow disappointing.

some day should be a Wiley classic
When this book came out in 1990 it was the first book to provide a truely modern treatment of categorical data analysis for both ordinal and nominal data. It provides an excellent treatment of the asymptotic theory for binary and multinomial data. It is extremely well written and is still a favorite of statisticians and practitioners. Because of its popularity and continued value, it should soon be added to the Wiley Classic series.

This is the first book to take the regression approach to categorical data analysis tieing the subject to the methods and theory of the generalized linear models. It also was one of the first to show the modern practicality of exact permutation methods.

The only drawback of this book is that it is 11 years old and there have been many interesting and relevant research developments in computer-intensive methods, analysis of missing data and mixed effects linear models to make a revision useful. Some of the latest developments can be found in Lloyd's new book "Statistical Analysis of Categorical Data" that was recently published by Wiley.

Agresti provides clear advice and also gives a nice historical perspective on the development of the subject. The book is authoritative and includes numerous relevant references. Each chapter contains many exercises and a wealth of practical examples for illustration of the techniques. This is a good text from both practical and theoretical perspectives. It is excellent for a graduate level course on categorical data analysis. ... Read more