Book Description
Valuable software, realistic examples, and fascinating topics . . . everything you need to master the most widely used management science techniques using Microsoft® Excel™ is right here! Learning to make decisions in today's business world takes training and experience. Cliff Ragsdale--the respected innovator in the field of management science--is an outstanding guide to help you learn the skills you need, use Microsoft Excel for Windows to implement those skills, and gain the confidence to apply what you learn to real business situations. SPREADSHEET MODELING AND DECISION ANALYSIS gives you step-by-step instructions and annotated screen shots to make examples easy to follow. Plus, interesting sections called The World of Management Science show you how each topic has been applied in a real company.
Customer Reviews:
A Good Book for Finance/IT majors.......2007-09-17
This book does what it sets out to do: teach spreadsheet modeling. I'm only on the third chapter, but the author does a good job including step by step instructions on how to create winning models. The author is also very easy to understand. So if you're going to be doing optimization and modeling in your work, I highly recommend this book.
Great book, and includes @RISK.......2007-08-06
Ragsdale really makes spreadsheet modeling accessible to real-world business situations. It was a great asset to my MBA coursework. As a student, it came with a free student version of @RISK risk analysis software as well.
Good practical text.......2006-11-12
A good book for those studying decision making techniques or as a reference for managers looking to upgrade their skills
Decision analysis.......2006-11-02
Excellent book; I am considering it as a textbook for a Managerial Sciences course. The examples are clear and real increasing the interest of the students.
Good book , worth to read.......2006-02-17
This book is designated as the textbook for our master's level management modeling class. The author concerntrated on the application of Microsoft Solver to solve various of optimazation problems that we freqently faced in the real business opreations. Overall, this is good book for entry-level management modeling study.
Book Description
This classic text on multiple regression is noted for its non-mathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for a solid understanding of the rest of the text.
The third edition features an increased emphasis on graphics and
the use of confidence intervals and effect size measures and an accompanying CD with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT.
Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters. The book is an ideal text for courses on multiple regression and correlational methods.
Customer Reviews:
Second Grad Stats.......2007-05-06
I've adopted this text for my graduate seminar in Multiple Regression. I choose it over other texts for the topics AND because it's focus is on concepts rather than math. Now that we can carry SPSSX in our brief case, there is no need to focus on that computation.
Can't beat it.......2001-04-17
...This book is the source of all you need. It's hard going at times, but so's the subject. The book's 15 years old and remains the best guide to the analysis of correlated data. It's a reference book, one I value as much as a good dictionary. To use it as a text would be misguided unless the instruction was aimed at a sophisticated audience.
Best MRC Book Ever.......2000-03-24
I agree with the previous reviewer that there are times when the exposition in the book gets a bit intense; but c'mon! We're dealing with statistics. You gotta sweat a bit. That's when learning happens. In my opinion the book is extremely clearly written. And although you may have to re-read a few sentences a few times, the basic tools for understanding most every major aspect of MRC is embedded in the text. In sum, this was a great book that I read as a 2nd-year graduate student in psychology. Unlike the first reviewer, I turned to this text when I got confused during the course lectures!
MRC Analysis---good book overall.......1999-12-15
Cohen and Cohen's MRC analysis book is well versed and easy to understand for someone that is familiar with MRC terminology, however, for first year graduate students, the text is very equivocal. The book is lacking ample illustrations of complex problems, leaving students to rely on outside sources. Also, the book uses unfamiliar symbols that do not correspond with other MRC books, which intensifies the confusion level of the students even more.
Overall, the text is a great addition to a statistical library, and this reviewer recommends it, in spite of being a sub-par book for first year graduate students.
Book Description
Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Customer Reviews:
Fantastic!.......2007-09-26
Just wanted to add to the praise of this book. If you're not following the backtesting practice of this book then you're playing slots with your trading (hey, maybe you'll get lucky!!). Some of the material is tough going and will require a second reading, but it'll be worth it. As another reviewer said about this being a kind of in-depth follow on to "Fooled by Randomness", I couldn't agree more. As matter of fact it's what I read just prior, so I couldn't help smiling as I went through this book, because he was putting the meat on the plate that Nassim set! Thank you, thank you..
The previous reviewer (Useless..) that gave it one star clearly did not get the concepts of the book. Did he even read it? That review does not compute. The *only* negative I would say is that if you're just looking for how to do robust backtesting, then the extensive material on the scientific method might be a bit much (but you can always read lightly those sections). But I understand why he put it in there, since it's the entire premise of taking a different and more rigorous approach to TA.
Now back to re-reading Chapter 6... Thank you Mr. Aronson!
Useless.......2007-08-29
I found this book useless..a total waste of time and money.Instead of analyzing the results obtained by using the various technical indicators,the author simply trashes their use,and does so in a preverse use of mathematical formulas,from which the reader gains nothing.I truly felt like my money was taken,for the purchase of the book,under false pretenses.
Make backtesting meaningful.......2007-08-24
Most trading books are pseudoscience or entertaining reminiscences of successful traders. Aronson has done an admirable job of applying the requisite rigor to the many difficulties associated with analyzing the results of historical backtesting.
Best for professional, intellectual and philosophical trading system developers.......2007-08-08
I had thought of using another review title "For fans and followers of Victor Niederhoffer" as inspired by his praise on the front cover. Pardon me to assume the following: if you had not heard of Niederhoffer, the chance is high that you have no prior experience/idea of testing the statistical significance of various TA tools, nor dwelling into the philosophical/scientific aspects of TA at all. Please accept the fact that this book is not for you. For trading professionals who deem themselves philosophical and intellectual (preferably with a college level of knowledge on statistics), this book is an inspiration. Highly recommended!
A must-have for TA practitioners.......2007-08-01
This book shakes some of your most deep beliefs in TA - and this is a healthy thing. Read it with an open mind.
Book Description
"This is a first-class book dealing with one of the most important areas of current research in applied statistics…the methods described are widely applicable…the standard of exposition is extremely high."
--Short Book Reviews from the International Statistical Institute
"The new chapters (10-14) improve an already excellent resource for research and instruction. Their content expands the coverage of the book to include models for discrete level-1 outcomes, non-nested level-2 units, incomplete data, and measurement error---all vital topics in contemporary social statistics. In the tradition of the first edition, they are clearly written and make good use of interesting substantive examples to illustrate the methods. Advanced graduate students and social researchers will find the expanded edition immediately useful and pertinent to their research."
--TED GERBER, Sociology, University of Arizona
"Chapter 11 was also exciting reading and shows the versatility of the mixed model with the EM algorithm. There was a new revelation on practically every page. I found the exposition to be extremely clear. It was like being led from one treasure room to another, and all of the gems are inherently useful. These are problems that researchers face everyday, and this chapter gives us an excellent alternative to how we have traditionally handled these problems."
--PAUL SWANK, Houston School of Nursing, University of Texas, Houston
Popular in the
First Edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been reorganized into four parts with four completely new chapters. The first two parts, Part I on "The Logic of Hierarchical Linear Modeling" and Part II on "Basic Applications" closely parallel the first nine chapters of the previous edition with significant expansions and technical clarifications, such as:
* An intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical sophistication in Chapter 3
* New section on multivariate growth models in Chapter 6
* A discussion of research synthesis or meta-analysis applications in Chapter 7
* Data analytic advice on centering of level-1 predictors and new material on plausible value intervals and robust standard estimators
While the first edition confined its attention to continuously distributed outcomes at level 1, this second edition now includes coverage of an array of outcomes types in Part III:
* New Chapter 10 considers applications of hierarchical models in the case of binary outcomes, counted data, ordered categories, and multinomial outcomes using detailed examples to illustrate each case
* New Chapter 11 on latent variable models, including estimating regressions from missing data, estimating regressions when predictors are measured with error, and embedding item response models within the framework of the HLM model
* New introduction to the logic of Bayesian inference with applications to hierarchical data (Chapter 13)
The authors conclude in Part IV with the statistical theory and computations used throughout the book, including univariate models with normal level-1 errors, multivariate linear models, and hierarchical generalized linear models.
Customer Reviews:
pre-req: mid-level stats experience.......2006-07-12
I had taken a class in HLM before, and I bought this book to refresh myself on the details. It takes a good deal of attention to detail and concentration to really get the full measure from this book, although it's all in there. Despite the authors' best efforts, there is a good bit of stats jargon in the book, so a reader who is not familiar might have some difficulty. If you're at a point where learning HLM is a logical next step, you'll be fine and I recommend this book. However, if your over-eager faculty advisor told you to learn HLM, despite your minimal experience in stats, you're better off enrolling in a class or workshop.
Good but sometimes skipping ahead too fast.......2006-03-09
This book gives a detailed description of the use of an advanced method to deal with nested data sets.
At a general level the constructs and ideas are well written and can be followed reasonably easily.
However the mathematics is often written very dense, which makes reading and understanding complex.
My main problem with the book, is that in many of the examples they provide, the given formula's, and data skip rapidly to the solution. Thus it is often not insightfull at all, how the data led to the numerical outcome (and I and several of my colleagues could not reproduce all of the example outcomes). A more extensive discussion and a more step-by-step construction of the examples would have been helpful there.
So in short: Conceptually this book is fine, but for practical use mathematics are too dense, and examples are too hard to follow
Useful, but need solid background in stats.......2004-06-05
This book describes important advances in statistical analysis of social science data, circa 1992. Much of this data has a natural hierarchical grouping. But traditional statistical methods proved inadequate at coping. The biggest drawback was the failure of the assumption of independence. If at the lowest level, Items I1,...,In are grouped into sets J1,...,Jm, where m
To handle this, Hierarchical Linear Models were developed. The book gives a detailed treatment. A very comprehensive discussion. Including the handling of meta-analysis, where we wish to combine results across different studies. Which then involves using empirical Bayesian estimates. This method has also seen important usage in evaluating medical studies, conducted by different researchers on the same topic.
The book also illustrates the essential development of non-trivial computer programs to perform the gruntwork.
You will need a solid background in statistics to find this book useful. At a minimum, a year of statistics at the undergraduate level.
Book Description
This market-leading book offers a readable introduction to the statistical analysis of multivariate observations. Its overarching goal is to provide readers with the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data.
Chapter topics include aspects of multivariate analysis, matrix algebra and random vectors, sample geometry and random sampling, the multivariate normal distribution, inferences about a mean vector, comparisons of several multivariate means, multivariate linear regression models, principal components, factor analysis and inference for structured covariance matrices, canonical correlation analysis, and discrimination and classification.
For experimental scientists in a variety of disciplines.
Customer Reviews:
Not as Applied as I Hoped.......2007-06-22
While this text covers a variety of multivariate techniques, the term "applied" is used loosely, in my opinion.
This is more a math-stat textbook than an applied statistics text.
I wish I had read the reviews (if they existed when I purchased the 4th edition), for I would have purchased a different text.
NOT a good intro to MVA.......2007-02-28
My prof used this book for multivariate statisitical analysis. I absolutely despise this book. For one, the answers to exercises come in a separate book, so the homework questions are worthless to me. The solutions will cost you an extra $100 or so if you buy that book. The index is extremely light, so if you want a quick reference to a topic - forget it. You'll need to skim through hundereds of pages that aren't referenced in the index. Important topics are illustrated in 1 example usually, and the reader is often left to guess how such problems could be adapted to different situations than what is illustrated.
Book Contents.......2006-03-10
The "search inside this book" feature was not available when this review was posted. Hope it helps.
CONTENTS
I. GETTING STARTED.
1. Aspects of Multivariate Analysis.
2. Matrix Algebra and Random Vectors.
3. Sample Geometry and Random Sampling.
4. The Multivariate Normal Distribution.
II. INFERENCES ABOUT MULTIVARIATE MEANS AND LINEAR MODELS.
5. Inferences About a Mean Vector.
6. Comparisons of Several Multivariate Means.
7. Multivariate Linear Regression Models.
III. ANALYSIS OF A COVARIANCE STRUCTURE.
8. Principal Components.
9. Factor Analysis and Inference for Structured Covariance Matrices.
10. Canonical Correlation Analysis
IV. CLASSIFICATION AND GROUPING TECHNIQUES.
11. Discrimination and Classification.
12. Clustering, Distance Methods and Ordination.
Appendix.
Data Index.
Subject Index.
I'm also a dullard, like the other reviewers here..........2006-02-10
I'm also a dullard like the other people reviewing the book on this sight. I'm not Greek, so I've never seen a capital sigma or other squiggles - frankly I didn't know that these squiggles existed!! I was looking for a statistics book that described statistics in a wooly, general, hand waving sort of way, just the way that I b@##%&i! my boss in meetings when statistics arise. Unfortunatley, this was not the book for me to learn this technique from. I don't know - I might have to finish my study of arithmetic (including long division), and then algebra, and then squiggles before I try again with this book. If you're a dullard like me, then keep away from this book - on the other hand it's an excellent book on applied statistical methods.
Yipes!.......2006-02-01
I used this text in one class for a PhD program that is now complete. Oh Boy! This is probably a good text if you have a very solid mathematics background, but it is totally incomprehensible to a mathematics greenhorn. I spent hours and hours trying to decipher the mathematical codes and formulas. Some of the symbols were figures I didn't even know existed.
Applied? Nope - totally theoretical from stem to stern.
Book Description
Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models. Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods. Visit http://www.ats.ucla.edu/stat/examples/alda.htm for: BL Downloadable data sets BL Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more BL Additional material for data analysis
Customer Reviews:
A Wonderful Work.......2007-07-15
I find Professor Singer's Book to be a most informative and useful tool for anyone who wishes to better understand Multilevel Modeling.
Applied Longitudinal Data Analysis by Singer,et al.......2007-03-13
Clearly written text... and usefull for researchers.
I would recommend it to anyone starting to learn about the subject!
The Clearest and Most Useful Book on HLM for Longitudinal Studies.......2006-07-28
This is simply the best book for those analyzing longitudinal data (data measured at more than one time point). Singer's coverage of Hierarchical Linear MOdeling (HLM) is clear, well-written (sprinkled with humor, it's like a lecture by the most popular prof. at your school), and geared towards researchers who need their programs to run, not just learn the mathematical underpinnings. Singer and Willett (the coauthor, not listed above!) set the standard for presenting math/statistics book examples.
THe authors accomplish the latter by keying her examples to data located at a UCLA website; you can run the same programs on the same datasets used in the book (wow!), and compare your output, troubleshooting any problems you may have. Singer and Willett (her coauthor, not listed here!) provide outputs and programs correspoing to several of the most popular statistical programs, including SAS and SPSS.
SInger and Willet also explain the rationale for using HLM over more traditional techniques such as regression. Simply stated, regression aggregates at a level that cause one to lose information (and hence the power to detect differences.) HLM allows one to look at overall differences due to time, but also the trajectories of individual differences who are "nested" within those time points. It's the (relatively) new thing, and is increasing used by investigators, and desired by peer reviewers.
As supplements, I suggest using the UCLA website mentioned above, subscribing to an e-mail LISTSERV for interesting (though sometimes compicated discussions of "multilevel modeling" (MULTILEVEL@JISCMAIL.AC.UK), and searching for Judith Singer's website through Google or A9 (if you use A9--"Alexa"--enough you'll get a small discount at Amazon.com). Also, compare Amazon's and Judith Singer's (through her website) current prices on this book.
Breaking down complex analyses .......2006-03-18
This is an excellent book. Multilevel modeling and survival analysis are becoming increasingly important in psychological studies, but are pretty complicated procedures. Singer & Willet offer both a conceptual background and practical ways to do the analyses in a clear, understandable manner. The book is very readable and will be an important reference for future analyses!
very clear and thorough.......2006-03-16
This book does a particularly good job of explaining the substantive meaning of the equations involved in multilevel modeling analyses. It spends a lot of extra time explaining what the equations mean in real world terms using examples from actual data sets. I teach a graduate level course on HLM and I much prefer this book to the Raudenbush & Byrk book because it not only does a better job of explaining the math (for graduate students less comfortable with statistics) but the chapters are also sprinkled with incredibly useful advice on actually running the analyses (getting them to converge, interpreting them, etc.) The Raudenbush & Bryk book probably does a slightly better job of presenting the equations, but it falls short on explanation and practical advice. If you were only going to buy one HLM book, I would start with this one.
Book Description
Still brief - but with the chapters that you wanted - Steven Chapra’s new second edition is written for engineers and scientists who want to learn numerical problem solving. This text focuses on problem-solving (applications) rather than theory, using MATLAB, and is intended for Numerical Methods users; hence theory is included only to inform key concepts. The new second edition feature new material such as Numerical Differentiation and ODE's: Boundary-Value Problems.
Book Description
This text comprises Chapters 0-7 of Larson and Edwards' Calculus: An Applied Approach, 6/e. For a complete description of this text's features, refer to the entry for that text.
Customer Reviews:
Easy book.......2007-03-27
Easiest calculus book ever, wish it had thorough answers in the back of the book.
Not that helpful for trying to teach yourself.......2003-09-21
This book assumes a knowledge that not everyone will have. It has an algebra/pre-calc review section, but the review is very basic (ie what an exponent is). The problems require you to remember about negative exponents and cube roots and whatnot.
The explanation parts are very simple and the problems are much more complex.It's hard to make the connection, and the answers in the back don't explain anything. (Don't buy the solutions manual - it's not any more help.) The answers are also simplified in inconsistent ways, so it's sometimes hard to use even if you have the problem right. Calculus for Dummies was more helpful, and explains a little better. It's still not as in depth as the problems in Brief Calculus, though.
(Sidenote: I'm "trying to teach myself" because my professor is incomprensible and has illegible writing as well.)
Yeah, maybe on the cover.......2002-03-01
I used this book for my high school curiculum and will use the exact same book in my collge calc class. And I have enough experience to say that, although this book seems to be user-friendly, it is by far not. The layout is relatively simple, however is not very in depth. Additionally, this book smashes together several large topics together with very little explanation. This lack of explanation, in turn, makes some of the problems practically impossible due to the fact that you haven't seen any problems like them before. All in all forget this book, and pay attention to your instructor.
Student Friendly Text.......2000-09-07
This is a great book. It helped me pass my business calculus course.
Excellent for Business majors.......2000-04-18
This text is an excellent text for business majors of all disciplines. It features real world applications and examples to learn from, and comprehensive excersises to demonstrate mastery of the material. The text is jam packed with helpful and clear illustrations and pictures.
Book Description
Master data analysis, modeling, and spreadsheet use with DATA ANALYSIS AND DECISION MAKING WITH MICROSOFT EXCEL! With a teach-by-example approach, student-friendly writing style, and complete Excel integration, this business statistics text provides you with the tools you need to succeed. Margin notes, boxed-in definitions and formulas in the text, enhanced explanations in the text itself, and stated objectives for the examples found throughout the text make studying easy. Problem sets and cases provide realistic examples that enable you to see the relevance of the material to your future as a business leader.
Customer Reviews:
Managerial Statistics Text book.......2006-11-03
It was the text book the professor wanted me to buy.
It was good.
Sanjay Chheda.......2006-10-06
The book is very good with really good explanations and examples on descriptive analysis and inferential analysis.
Better Title: Intro to Statistics using Excel Add-ins.......2001-06-04
On the positive side, this book has many excellent case studies and examples. It is well written and interesting. However, I was disappointed, as I was expecting use of Excel to rigorously solve decision making and data analysis problems. The focus of the book is mostly traditional statistics solved using a group of commercial add-ins for Excel. If this is what you want, then the book would get five stars. However, for data analysis and decision making, I think a more thorough treatment using Excel without relying so much on the add-ins would have been appropriate.
Serious Excel 2000 Problem.......2001-04-12
The text book is great. I have many of Winston's other books and they are all great. The Palisade stuff works just fine. However, the StatPro Addin that accompanies this text does not work with MS Excel 2000. I contacted the IT guy that the authors directed me to--he was stumped. He just gave up and suggested I return my book for a refund because he could not figure out it out. Again, the book is great but the StatPro Addin sucks!
No trouble with Excel.......2001-01-31
I find the text and software a useful set of tools. It assumes familiarity with basic statistics and Excel, and builds on them to develop a powerfull ability to analize data and make decisions from it. I experienced no trouble with the software install or operation.
Book Description
From the reviews of the First Edition.
"An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."
âChoice
"Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent."
âContemporary Sociology
"An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."
âThe Statistician
In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.
Download Description
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." --Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." --Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." --The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.
Customer Reviews:
read this before going for it.......2007-04-24
Logistic regression has taken a new life after new vision has developed all over the world to have efficent and effective risk management system. Since this topic is new for lot of people, this guide goes an extra mile to make people understand and practice the concepts in social sciences using SAS, STAT and / or SPSS. Must buy if you really want to taste the benefit of logistic regression. The guide explains the concepts and soloutions to the bestseller. Once again good book, but not to be read from cover to cover rather on need basis when encounter any problem.
Advanced practical cookbook.......2006-11-06
This text was intended to give practical, procedural, authoritative advice to practitioners on how to build models using logistic regression. It is not an introductory text. It is so concise that just about every sentence has a point to note. The reader should have some prior exposure to logistic regression and be fairly expert in modern linear regression model building using standard software, such as SAS, SPSS, STRATA or BMD.
Excellent book for learning logistic regression details.......2006-01-31
I found this book to be an excellent account of logistic regression techniques. It was clear and used a minimum of mathematical detail , focusing instead on the understanding of the concepts presented. There were two small problems that I found with this book: (1) The subsections of the text were not adequately identified which made finding specific things occasionally difficult. (2) The mathematical notation was often different than other references that I own. Overall, a highly recommended purchase.
update of very well written and popular text.......2001-06-02
Hosmer and Lemeshow point to the massive growth in applications of logistic regression over a ten year period from the time of publication of the first edition of their text. They found over 1000 articles that used logistic regression during that time frame. There also have been many software advances that make it easier to apply logistic regression. The authors do their computing mostly in STATA. But they also acquaint the reader with many other useful standard packages for applying logistic regression. They also provide a web site from the publisher where data sets can be found.
New topics include the use of exact methods in logistic regression, logistic models for multinomial, ordinal and multiple response data. Also included is the use of logistic regression in the analysis of complex survey sampling data and for the modeling of matched studies.
The book is intended for a graduate course in logistic regression requiring the student to be familiar with linear regression and contingency tables. Similar in spirit and objectives to the first edition, this text also maintains the clarity of thought and presentation that these authors have a history of providing.
This is an important update to the first edition and is worth having on the bookshelf in any biostatistics library. I have my own personal copy and I think many others would also benefit by having it as a reference.
Should suit the needs of most, especially analysts.......2000-10-15
This is an excellent beginning and intermediate text on logistic regression analysis. Avoids the thorny details, but provides a wealth of references for those who are interested.
Anyone who is serious about doing logistic regression analysis should have this book.
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- Structural Equation Modelling: A Bayesian Approach (Wiley Series in Probability and Statistics)
- System Reliability Theory: Models, Statistical Methods, and Applications, Second Edition
- The Art Student Survival Guide
- The Variational Principles of Mechanics (Dover Books on Physics and Chemistry)
- Tool and Object: A History and Philosophy of Category Theory (Science Networks. Historical Studies)
- Vector Calculus
- Viscous Fluid Flow (Mcgraw Hill Series in Mechanical Engineering)
- Welding: Principles and Applications, Fifth Edition
- What Went Wrong?, Fourth Edition: Case Studies of Process Plant Disasters
- A Biologist's Guide to Mathematical Modeling in Ecology and Evolution
Books Index
Books Home
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General
| Business & Investing
| Subjects
| Books
Financial Accounting: A Valuation Emphasis
Training In Interpersonal Skills: Tips for Managing People at Work (4th Edition)
Statistics for Business and Economics and Student CD (6th Edition)
Operations Management with POM Software CD-ROM
Microeconomics, 6th Edition
