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
APPLIED REGRESSION ANALYSIS applies regression to real data and examples while employing commercial statistical and spreadsheet software. Covering the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis, the text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets.
Customer Reviews:
Great Minitab Resource.......2007-05-15
Dr. Dielman was a professor of mine. The book is well organized and useful for all people on all levels.
Excellent.......2006-12-26
For my class, the professor assigned Kleinbaum et al's textbook rather than this one. As I mentioned in my review for that book, it was so confusing and poorly organized. Luckily, I found this book in the library and used it instead and ended up a lot less confused in class than my classmates who were trying to understand the Kleinbaum book. Dielman's book is very well organized and laid out. It doesn't have colorful bells and whistles since it's a fairly upper level book, but it does have a very user-friendly layout. Furthermore, the formulas are never presented without an accompanying explanation in plain English and examples of how and when to use them. Another thing I really like about this book is that it gives thorough directions on how to do a lot of the analyses on some common statistical packages. Many of the instructions are accompanied by screenshots. They're at the end of each chapter rather than interspersed in the text, which makes them easy to find. This is actually becoming a great SAS manual for me.
For anyone struggling with the Kleinbaum book, or for any instructor considering using the Kleinbaum book, I would highly recommend this one instead.
A Cross-platform textbook.......2006-05-15
I have bought Dr. Dielman's Applied Regression 4e textbook in Taiwan) for preparing my MBA thesis regarding the interaction effects. Given the widespread use of commercially available packages, this book provided considerately coverage on ALL computer packages about the field of regression work.
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
Adonis Yatchew provides simple and flexible (nonparametric) techniques for analyzing regression data. He includes a series of empirical examples with the estimation of Engel curves and equivalence scales, scale economies, household gasoline consumption, housing prices, option prices and state price density estimation. The book is of interest to a broad range of economists including those working in industrial organization, labor, development, and urban, energy and financial economics.
Download Description
This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples include estimation of Engel curves and equivalence scales, scale economies, semiparametric Cobb-Douglas, translog and CES cost functions, household gasoline consumption, hedonic housing prices, option prices and state price density estimation. The book should be of interest to a broad range of economists including those working in industrial organization, labor, development, urban, energy and financial economics. A variety of testing procedures are covered including simple goodness of fit tests and residual regression tests. These procedures can be used to test hypotheses such as parametric and semiparametric specifications, significance, monotonicity and additive separability. Other topics include endogeneity of parametric and nonparametric effects, as well as heteroskedasticity and autocorrelation in the residuals. Bootstrap procedures are provided.
Average customer rating:
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Applied Multivariate Data Analysis: Volume II: Categorical and Multivariate Methods (Springer Texts in Statistics)
J. D. Jobson
Manufacturer: Springer
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Applied Multivariate Data Analysis: Volume 1: Regression and Experimental Design (Springer Texts in Statistics)
ASIN: 0387978046 |
Book Description
This books presents an easy to read and wide-ranging introduction to techniques in multivariate analysis. It covers all the traditional topics of multivariate analysis including multidimensional contingency tables, logistic regression, cluster analysis, multidimensional scaling, and correspondence analysis. It is the companion volume to Volume I: Regression and Experimental Design published in 1991. The emphasis on the practicalities of the subject, and the author has included numerous analyses of real data sets drawn from a wide range of business, social sciences, and biological sciences settings. There are also many exercises which are designed to extend the analyses of the data sets including the use of statistical computing packages, and to cover further theoretical results relevant to the book. As a result, any student whose work uses these techniques will find this to be an excellent introduction to the subject.
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Applied Multivariate Data Analysis: Volume 1: Regression and Experimental Design (Springer Texts in Statistics)
J. D. Jobson
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
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Applied Multivariate Data Analysis: Volume II: Categorical and Multivariate Methods (Springer Texts in Statistics)
ASIN: 0387976604 |
Book Description
An easy to read survey of data analysis, linear regression models and analysis of variance. The extensive development of the linear model includes the use of the linear model approach to analysis of variance provides a strong link to statistical software packages, and is complemented by a thorough overview of theory. It is assumed that the reader has the background equivalent to an introductory book in statistical inference. Can be read easily by those who have had brief exposure to calculus and linear algebra. Intended for first year graduate students in business, social and the biological sciences. Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications.
Book Description
Intended for the regression analysis course for students of business and economics or as a second course in business statistics; found in schools of business or in departments of statistics and economics.
Customer Reviews:
Good for Excel and Minitab User.......2006-05-15
I checked Dr. Dielman's Applied Regression textbook out from Tsing-Hua Univ (Taiwan) Library for preparing my MBA thesis regarding the interaction effects. Given the widespread use of the SPSS or SAS, there are fewer texts writen in other commercially available packages. This book provided an alternative option for conducting the regression work.
The best book ever.......2001-05-24
This book takes you along the process of learning regression analysis easily. The author takes the time to show you how to solve real problems, the disc that comes with the book allows to even go deeper on the subject of study. The one who buys this book will never sell it, you'll need it all your professional life.
Product Description
Third Edition, Solutions Manual
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Applied Regression Analysis in Econometrics (Statistics: a Series of Textbooks and Monogrphs)
Doran
Manufacturer: CRC
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ASIN: 0824780493 |
Book Description
A textbook for a one-semester course for advanced undergraduate and graduate students in economics. Covers regression techniques in the context of single equation econometric models, featuring MINITAB and SHAZAM software examples for attacking real-world problems. Annotation copyright Book News, Inc
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Statistical Inference
Categorical Data Analysis (Wiley Series in Probability and Statistics)
The Little SAS Book: A Primer, Third Edition
SAS and SPSS Program Solutions for use with Applied Linear Statistical Models
Applied logistic regression (Wiley Series in probability and statistics)
