Book Description
This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes.
Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.
The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses.
The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).
From the reviews:
"This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered."
Journal of Biopharmaceutical Statistics, 2005
"This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book"
Technometrics, February 2006
"Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally."
Journal of the American Statistical Association, March 2006
Customer Reviews:
very good book, compact but comprehensive.......2007-05-12
This book covers a wide range of topics in Biostatistics, in a comprehensive, but not overwhelming way. In my opinion this book has the potential of being useful to a broad audience, from Statisticians to other professionals who do health related research.
Excellent book ..........2007-01-09
A very specific book, with a lot of details for a statistitian
Book Description
Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling, analysis of variance, and the design of experiments. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text proceeds through linear and nonlinear regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Comments" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, projects, and case studies are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and the use of automated software without loss of understanding.
Customer Reviews:
Outstanding Non-Theoretic Linear Models Book, HUGE.......2007-07-15
Second year Ph.D. student in Statistics at Iowa State University
I can't think of a single better non-theoretic linear models book. You need to have at least one semester of undergraduate statistics under your belt to follow this book, but it's useful and readable for everyone else. Undergraduates, graduates, professionals...whoever. Given its non-theoretic approach and extremely clear explanations, it can be read by undergraduates with only a minimal background in statistics, but it is comprehensive enough to be useful to anyone. There is no better linear models reference. The textbook is thick (almost 1400 pages) and covers most linear models topics in great detail including regression, ANOVA, and analysis of covariance. My only disappointment regarding content was the rather slim coverage of random and mixed effects models and GLM's. On a positive note, the book provides excellent coverage of diagnostics and remedial measures, which is very often skimmed over in linear models books. Additionally, it has exceptionally well-written, though fairly brief, coverage of model selection and validation, another topic that is a little lacking in many linear models books.
The explanations and choice of exercises are both well-done. The explanations and examples are both clear and thorough, although I would have definitely preferred to see more graphs. It's the kind of topic where visual illustration greatly increases understanding. Generally, the exercises seem a little bit too easy, especially for graduate students, but they do mix in a few harder problems and they pick good, non-contrived problems.
Whether you want a linear models book for learning purposes or if you just want a reference, this book is an excellent choice.
Emminetly Readable.......2007-04-07
This book was a required text for my Data Analysis course. I am not a stats person and have had only a rudimentary introduction to the subject, so I was surprised to find that this is a very approachable book. It is A TOME, but only because the authors are so thorough in their explanations. If you have seen hypothesis testing and are comfortable with the normal distribution, you will be able to face this book. If you are not, be aware that the exercises in the first chapter refer to the prerequisite material not covered by the book.
After the introductory chapter, the authors gave just the right amount of theory to explain the topic at hand and give extensive footnotes for further information. Lots of graphs and example software output are included, all very helpful. I found the text to be well-organized, with coverage given to explanation and examples of each topic.
My one complaint with the book is that it included no instruction on how to work with software programs to get the desired results, so if you are entirely new to the area and do not know how to use Statistix (which has a thorough and self-explanatory help system), R, Minitab, and SAS (which do not), going will be rough. One of the other reviewers mentioned a SAS guide. You may need it if your professor does not demonstrate software use in class.
a non-stat guy likes this book....worth the money........2007-02-23
This is truly an applied text. If you've had basic stats courses and a you have a competent professor then this text will not "run away" from you with wild references to theory and obscure terminology. The authors are quite deliberate and patient in their explanations when they introduce new terminology OR they feel a review of the terminology/concept is in order. The heft and look of the book is VERY intimidating, but it's just an illusion...since the book is truly applied, the theoretical stuff is kept to a minimum. The example data help to bring this book alive. Now don't get me wrong. I have done lots of outside reading on basic stuff like error, variance, and knowing the difference between a parameter and a statistic to get prepped for this class and it paid off. I will keep this book to refer back to it frequently.
Great reference.......2007-01-11
Thus book is comprehenisve and clear. A must-have for those who frequently to regression analysis.
Awesome book ! .......2007-01-09
This book if not for business majors , engineering students and psycology students.
This is an EXCELLENT book for statistics undergrad/grad and PhD students.
I spent over 10 hours weekly just reading the book every week. Plus my assignments will take another 10 hours . So be prepared for a 20 hr week.
YOU NEED TO TAKE A BASIC STAT / INTRO STAT course before this. If you dont know the meaning of P-values , T-test , F-test , DO NOT TAKE THIS COURSE. This book will not introduce you to those things. Unfortunately many buiness schools ( including top 10 ) dont offer a good intro stat course, so buiness majors jumping in to this course is a wrong idea.
This book is also a "good to own book". The first 15 or so chapters has regression and the second half ( next 15 chapters ) has DOE (design of experiments). GREAT BOOK !
One piece of advice - make sure you learn to use SAS with this course . In real world applications many industries are using SAS. Even if your teacher insists on using R package / splus , YOU MAKE SURE YOU know how to do those things in SAS . There is a SAS student manual with this book, specially written for this book . buy it ISBN - 0-07-302177-6
good luck !
Book Description
Thoroughly updated and more straightforward than ever, Applied Linear Regression Models includes the latest statistics, developments, and methods in multicategory logistic regression; expanded treatment of diagnostics for logistic regression; a more powerful Levene test; and more. Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.
Customer Reviews:
Must have reference.......2007-02-16
If you are going to spend money, buy the best. This book is the best and IS the standard. I'd consider this the "Gray's Anatomy" of Applied Linear Statiscal Models (i.e. Design of Experiments, Regression, hypothesis testing).
This book is geared for an entry level masters or 400 level student. If you don't fall into this category, this could be worthwhile, just know you'll need to put more time in to learn the material...or...you could get a book geared toward your level. Vardeman's applied statistics for engineers would be one that comes to mind for subject matter that is geared for knowledge below KNNW's Applied Linear Statistical Models.
Bottom line is that this is a must have in anyone's library who is going to do statistical analysis using linear models. It's one of my (and most of my co-workers) go to books if we need to refresh on a quick method to approach a problem.
All in all, it covers all the basics and for the money is a great applied book.
Cheaper Versions Available.......2007-02-12
This hard-bound text was received in excellent condition and should last for as long as I plan on using it; however, there are cheaper versions (like the international version) that contain exactly the same information (plus additional information about ANOVA designs). I am still happy with my purchase, but if you are low on cash, I would recommend purchasing a different edition of this book.
the author don't know how to express in simple language.......2007-01-16
the author don't know how to express in simple and understandable language, although he know very well in this major. I have already read some other books of this major, it is still confusing me a lot to understand some sentences in this book.
Super ! .......2007-01-09
This book if not for business majors , engineering students and psycology students.
This is an EXCELLENT book for statistics undergrad/grad and PhD students.
I spent over 10 hours weekly just reading the book every week. Plus my assignments will take another 10 hours . So be prepared for a 20 hr week.
YOU NEED TO TAKE A BASIC STAT / INTRO STAT course before this. If you dont know the meaning of P-values , T-test , F-test , DO NOT TAKE THIS COURSE. This book will not introduce you to those things. Unfortunately many buiness schools ( including top 10 ) dont offer a good intro stat course, so buiness majors jumping in to this course is a wrong idea.
This book is also a "good to own book". The first 15 or so chapters has regression and the second half ( next 15 chapters ) has DOE (design of experiments). GREAT BOOK !
One piece of advice - make sure you learn to use SAS with this course . In real world applications many industries are using SAS. Even if your teacher insists on using R package / splus , YOU MAKE SURE YOU know how to do those things in SAS . There is a SAS student manual with this book, specially written for this book . buy it ISBN - 0-07-302177-6
good luck !
Popularly accepted regression text book.......2006-11-06
I bought this book because I needed it for a class, and I have only used it a few times for the class. It's hard to learn stats from a textbook unless you start at the beginning, but this book is useful to accompany a previously-knowledgeable statistics mind seeking to learn more about regression.
Great book, but probably will not help a rookie to self-teach regression.
Book Description
Kutner, Nachtsheim, Neter, Wasserman, Applied Linear Regression Models, 4/e (ALRM4e) is the long established leading authoritative text and reference on regression (previously Neter was lead author.) For students in most any discipline where statistical analysis or interpretation is used, ALRM has served as the industry standard. The text includes brief introductory and review material, and then proceeds through regression and modeling. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Comments" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in any discipline. ALRM 4e provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor.
Customer Reviews:
Useful book with shortcomings.......2002-02-26
When studying about linear models, this book is a very good resource. The very title gives one a sense of this book's target audience: _Applied_ Linear Statistical Models. Throughout its 1400 some odd pages examples and applications are sprinkled, neatly illustrating concepts relevant to the section. One problem: the end-of-chapter exercises. All of the data for use in these exercises are contained on a diskette. Fine. What happens if one were to lose this disk? Better make friends quick in order to have someone from whom to copy the data. Hypothetically, you've gone the entire semester without losing the disk. Datasets are reused throughout the book, yet explanations are only given the first time the data are used. When reusing the data one has to turn to the section where it was first used and decipher the book's difficult labelling system. The exercises do just that, and well, yet they take much more time than if their organisation were better.
Save Your Money........1999-06-14
Save Your Money. Spend your money on more usefull things like paying all those parking tickes your have received thus far. This student solutions manual has the soulutions to some and I repeat some of the many problems in the text. Having mear soulutions to problems is not enough depth to place in a manual of solutions. Most solutions manuals work out the problem to show where the answer came from, not this one.
Book Description
In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method allows parametric assumptions to be realized in regression problems, in those approached by generalized linear modelling, and in many other contexts. The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.
Book Description
"I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with--and he does not avoid the slippery ones--he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks and that matches the works of the leading researchers within each field."
--Georges Monette, Department of Mathematics and Statistics, York University
"The selection of examples throughout the book is one of its strengths, as they are generally quite engaging in ''real-world'' interest, and demonstrate the practical use (and limitations) of the statistical methods far better than contrived data. I appreciate the fact that John Fox describes what each example ''means'' in terms of the substantive problem behind the data--students would find this quite useful."
--Michael Friendly, Psychology Department, York University
Aimed at researchers and students who want to use linear models for data analysis, John Fox's book provides an accessible, in-depth treatment of regression analysis, linear models, and closely related methods. Fox incorporates nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences. He begins the book with a concise consideration of the role of statistical data analysis in social research. He next covers graphical methods for examining and transforming data, linear least-squares regression, dummy-variables regression, and analysis of variance. Fox also explores diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear regression, robust regression, and nonparametric regression; and empirical methods for assessing sampling variation, including the bootstrap and cross-validation. More difficult material is segregated in separate sections and chapters and several appendixes are also included presenting background information. Scholars, professionals, researchers, and students in research methods, evaluation, education, sociology, and psychology will appreciate the enhanced and thorough treatment that regression analysis, linear models, and other related methods have received by author John Fox.
Customer Reviews:
Useful and understandable.......2007-02-19
This book takes an unusual start. It begin with the assumption that regression usually has to the data and illustrates how the assumption can be violated, illustrates why graphical analysis is important for data analysis and, in chapter 4, explains how to "fix" the violations of the requirement to the data, before actually starting to explain regression models. I find this unusual approach very insightful. Moreover, difficult parts are marked with an asterisk and can be left out if this is more convenient for the reader.
Although some math is required, I find this book very understandable throughout due to its focus on application. The book covers linear models and some extensions (for the large part of the book) and also Logit- and Probit models for nominal data (in Chapter 15). Chapter 16 deals with bootstrapping, and the appendices give some introduction to statistical and mathematical requirements that the book poses.
Overall, a good buy for people who apply regressions (as the title says), probably not so much for those who are in statistics, math, or econ.
Not suitable as an introduction to regression analysis.......2006-03-08
While this book is no doubt useful to students with a solid background in math and statistics, I certainly would NOT recommend it as an introduction to regression analysis. The explanations tend to be far too complex and inaccessible for most graduate students in the social sciences. Put it this way: after having spent almost $100 on this book, I've had more success finding useful explanations of some of the book's topics on Google than I have had by reading the book itself.
Useful but disorganized.......2006-02-15
This book is a useful first book in linear regression. Fox covers the basics effectively, and the book nicely complements Fox's guide to Regression in R and S Plus.
My biggest problem with the book is Fox's meandering prose style. Few of his paragraphs start with topic sentences, and the formatting of the text means it's almost impossible to figure out what the take-away points are. (It would have been nice for Fox to reverse-engineer his chapters from the end-of-chapter summaries, which are the most helpful guide to his book, and actually happen to be organized.
For a more organized and more clearly written guide to regression, see Basic Econometrics by Gujarati.
Good but Flawed.......2005-05-19
Dr. Fox has written in a thoughtful original manner. Example, pretty much all regression books starts out with a graph of simple linear regression model statisfying all the strong assumptions that went into it. Dr. Fox starts out by showing graph of data that violates every single assumption. This is the sort of innovative and creative approach that shows what is best about this book. Dr. Fox has a deep conceptual understanding of this material.
The book doesn't get 5 stars becuase a significant flaw. Dr. Fox (or perhaps the publishers) wanted every kind of student to be able to read this book. Both students with advanced and also students with no statistical/mathematical expertise and sophistication. The result is a fragmented text. For instance, the geometrical interpretation of least squares fit is not integrated into the initial discussion (it comes 130 pages later!). If it was integrated then many of the derivations and discussions would be far simpler and intuitive. This sepration allows a student with no linear algebra background to read this text but it also wastes the time of the advanced students who have to wait for the more simpler and intuitive approach.
Get it now!!! Best on the subject........2004-01-16
Dr. Fox makes an excellent contribution to the student community across geographies. The text is an excellent balance between theory and practical applications of the linear regression methodology. The author is extremely clear in explaining not only simple and multiple linear regression, but also topics such as bootstraping, logistic and other regression techniques for non normal response variables. The book do not fall down near your toes: the topics are covered in a depth that is amenable for a PhD student.
It is very interesting also to look at the many side comments and suggested readings that the author introduces many times in the book. I congratulate Dr. Fox for this clear, understandable and easy to follow text.
Customer Reviews:
developed by Stanford graduates students.......2002-04-10
Believe it or not this important topic in applied statistics was developed by Hastie and Tibshirani when they were graduate students, a sure sign of greatness to come. After their graduation this highly acclaimed book came out explaining both the theory and pratice of generalized additive models in a clear and concise way. Generalized additive models are similar to generalized linear models in their additive structure but the form of the additive functions is much more general.
Both Hastie and Tibshirani are now Stanford professors in the Statistics Department and both have written other excellent books including their joint publication with Jerry Friedman "The Elements of Statistical Learning" and Tibshirani along with Efron wrote an excellent monograph on bootstrap.
A complex topic made readable........2000-04-14
A medical doctor recommended that I (a statistician) use generalized additive models on a project that he was involved with. We were pleased with the results of the modelling as they gave us some new insights on his topic and it was very rewarding
Because we were so impressed with the results, we both took the above book out of the library to read. I started the book with some trepidation as I feared it was going to be a complex topic and in some respects I was right. However, right from the encouraging quotes in the preface and into the text itself, I felt the authors were making a great effort to make the book readable.
The medico found that the explanations and examples were well written. His comment was that even a non-statistician could grasp what was going on but that there was enough theory that a statistician would be happy too!
Average customer rating:
- this explains everything...
- The quanlity is fair
- Applied Linear Regression
- This is the ONE that will get you through advanced stats!
- Best Book Out There
|
Applied Linear Statistical Models
John Neter ,
Michael H Kutner ,
William Wasserman , and
Christopher J. Nachtsheim
Manufacturer: McGraw-Hill/Irwin
ProductGroup: Book
Binding: Hardcover
 Statistics
| Economics
| Business & Investing
| Subjects
| Books
General
| Accounting
| Industries & Professions
| Business & Investing
| Subjects
| Books
General
| Engineering
| Professional & Technical
| Subjects
| Books
Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
| Applied
| Chaos & Systems
| Geometry & Topology
| Mathematical Analysis
| Mathematical Physics
| Number Systems
| Pure Mathematics
| Transformations
| Trigonometry
General
| Accounting
| Accounting & Finance
| Professional & Technical
| Subjects
| Books
General
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
General
| Engineering
| New & Used Textbooks
| Stores
| Books
Statistics
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
General
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
General
| Accounting
| Business & Finance
| New & Used Textbooks
| Stores
| Books
General
| Business & Finance
| New & Used Textbooks
| Stores
| Books
Quantitative Business
| Business & Finance
| New & Used Textbooks
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Business & Investing
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
jp-unknown1
| Specialty Stores
| Books
Similar Items:
-
MP Applied Linear Regression Models with Student CD-rom
-
Statistical Inference
-
Applied Multivariate Statistical Analysis (6th Edition)
-
Applied logistic regression (Wiley Series in probability and statistics)
-
Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences)
ASIN: 0256117365 |
Book Description
There are two approaches to undergraduate and graduate courses in linear statistical models and experimental design in applied statistics. One is a two-term sequence focusing on regression followed by ANOVA/Experimental design. Applied Linear Statistical Models serves that market. It is offered in business, economics, statistics, industrial engineering, public health, medicine, and psychology departments in four-year colleges and universities, and graduate schools. Applied Linear Statistical Models is the leading text in the market. It is noted for its quality and clarity, and its authorship is first-rate. The approach used in the text is an applied one, with an emphasis on understanding of concepts and exposition by means of examples. Sufficient theoretical foundations are provided so that applications of regression analysis can be carried out comfortably. The fourth edition has been updated to keep it current with important new developments in regression analysis.
Customer Reviews:
this explains everything..........2007-01-18
It's the only book in our library that (a) doesn't assume that you know everything already, and (b) doesn't assume that you want to skip over any of the details. Adding in an excess of examples it makes for a very long book, but when you find yourself needing to decypher someone else's statistical software (like I did) it's a life-saver.
The quanlity is fair.......2006-08-30
The quanlity is fair. the cover is somewhat broken.
someone split drink in the first few pages.
Applied Linear Regression.......2005-10-12
An extremely comprehensive and well written textbook. Very useful as a reference on linear statistical models but at 1400 pages not a straightforward read. Each section is supported by a number of well explained examples.I would strongly recommend this book as a reference but there are a number of alternatives which I prefer in terms of readability and accessibility of the material.
This is the ONE that will get you through advanced stats!.......2004-11-07
I cannot recommend this book highly enough, especially if one is struggling through a grad level stats course. I spent days looking through texts and reading material on the web, this is the book that is detailed enough and explanatory enough so that I finally understood what was going on with statistics. I went from confused about stats to enjoying them, primarily due to this book. I have it tabbed and write all my class notes in this one... this is a keeper. I am looking forward to the fifth edition if they ever do one.... this text covers regression, logistic regression, correlation, anova and study design (actually covers the material for 3 different stats programs in this one text)--- over 1300 pages and all worth reading!!!(reading hint for the confused.... pay little attention to the reams of formulae and lots of attention to the editorial comments, explanations and discussions that accompany the formulae) Update: This text is now in its 5th edition. The author list has changed slightly (Kutner, Nachtsheim, Neter, Li), and the book now has a CD rom with it (isbn 0072386886).
Best Book Out There.......2003-12-19
I have used this book when it was in its first edition and only by Neter and Wasserman. An absolute must for those who use linear models (regression and ANOVA) and want the most exhaustive book out there. This book is one of the rare texts that is also extremely well written. You can not go wrong reading it and studying it on your own. If you can take only one statistics book with you, this is the one. I use the 4th edition so much, I wore my first one out and am now on the second.
Customer Reviews:
a practical reference.......2006-06-13
Experimental design analyzing with linear models has been on the notation for decades. The book, although somewhat antique, is still an envaluable reference.
Superbly written book on Linear Statistical Models.......1998-12-03
This book blends the necessary theory with practical application to provide the reader with a riviting insight into the world of linear statistical models.
Books:
- Sarbanes-Oxley: A Practical Guide for Corporate Executives, Risk and Audit Professionals
- Small Business Management: An Entrepreneurial Emphasis (with CD-ROM and InfoTrac®)
- Structured Credit Portfolio Analysis, Baskets and CDOs (Chapman & Hall/Crc Financial Mathematics Series)
- Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications (New York Institute of Finance)
- The 2007 Microsoft Office System Step by Step
- The ART of Risk Management
- The Attachment Parenting Book : A Commonsense Guide to Understanding and Nurturing Your Baby
- The Berenstain Bears' Trouble with Money (First Time Books(R))
- The Black Belt Memory Jogger: A Pocket Guide for Six Sigma Success
- The Credit Secrets Bible
Books Index
Books Home
Recommended Books
- Global Sustainability: Bending the Curve
- Blood Stripes: The Grunt's View of the War in Iraq
- The Limits to Capital, New Edition
- The New York Times Ultimate Crossword Omnibus: 1,001 Puzzles from The New York Times
- What's Wrong With My Mouse: Behavioral Phenotyping of Transgenic and Knockout Mice
- Best of Ann Landers: Her Favorite Letters of All Time
- 2000 Pay To Win: How America's Successful Companies Pay Their Executives
- Accounting Primer for Prospective Nba's & Others
- The Limits to growth: A report for the Club of Rome's Project on the Predicament of Mankind
- Unnatural Causes
Epidemiologic Methods: Studying the Occurrence of Illness (Medicine)
Applied Longitudinal Analysis (Wiley Series in Probability and Statistics)
Epidemiology: Beyond the Basics
Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data
Fundamentals of Clinical Trials
Implementing an Electronic Health Record System (Health Informatics)
Handbook of Injury and Violence Prevention
