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Author : S. Christian Albright
Edition : 3
Number of Pages : 1090
Publisher : South-Western College Pub
List Price : $171.95
Amazon Price : $123.30
Used Price : $122.17 |
Product 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 quantitative methods 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. The CD-ROMs packaged with every new book include the following add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, and RISKOptimizer); and SolverTable, which allows you to do sensitivity analysis. All of these add-ins have been revised for Excel 2007. Customer reviews Perfect condition - good deal.  by .. K. Nash (Cincinnati, OH USA)
The textbook was brand new and I saved about $40. I received it on time and the transaction was easy.
Managerial Statistics Text book  by .. Sang Woo Kim (Gainesville, FL)
It was the text book the professor wanted me to buy.
It was good.
Sanjay Chheda by .. Sanjay Chheda ()
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  by .. charledl@aol.com (Gainesveille, FL)
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 by .. Jal Singh (NYC)
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!
Related Search : statistic tools , excel 3e , revised with  |
Author : Mark Allen Weiss
Edition : 3
Number of Pages : 586
Publisher : Addison Wesley
List Price : $114.00
Amazon Price : $75.00
Used Price : $71.99 |
Product Description Mark Allen Weiss' innovative approach to algorithms and data structures teaches the simultaneous development of sound analytical and programming skills for the advanced data structures course. Readers learn how to reduce time constraints and develop programs efficiently by analyzing the feasibility of an algorithm before it is coded. The C++ language is brought up-to-date and simplified, and the Standard Template Library is now fully incorporated throughout the text. This Third Edition also features significantly revised coverage of lists, stacks, queues, and trees and an entire chapter dedicated to amortized analysis and advanced data structures such as the Fibonacci heap. Known for its clear and friendly writing style, Data Structures and Algorithm Analysis in C++ is logically organized to cover advanced data structures topics from binary heaps to sorting to NP-completeness. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm. Customer reviews Horrible text book  by .. Darren Grove ()
The person who wrote this book thinks he's the worlds smartest man. He assumes you know everything, and thus makes steps in examples with no explanation beyond "obviously the next step is...". I would not recommend this book to anyone.
not a good text book by .. Faith (Kansas City)
Doesn't have enough examples. The questions are hard. Also there is no answers in the back or even on the Mark Allen Weiss web page either.
Great book on data structures! by .. Johan Steinrud (Stockholm, Sweden)
This is a great book on data structures. It covers both basic and more advanced data structures.
Good Read for Computer Scientists by .. Jeremy Love (Houston, TX)
I use this book for my Data Structures & Algorithms class as a sophomore Computer Science major.
This book is a tad bit on the advanced side, but the explanations and examples are great all the way through. There's a certain level of knowledge that is expected and it doesn't let up. I'm not too keen on how good the practice problems are, but the few that i've done require a high level of concentration. Before reading, make sure you're up on proofs (read: proofs EVERYWHERE).
I do think it'd be a good addition to any programmer's collection.
Concepts explained well. by .. Casey Wireman (Augusta, GA USA)
I thought that this book did its job in explaining the data structures under consideration effectively, but I did not like the author's coding style, and this is nothing more than taste. The book's goal is the teaching of data structures and it did this. Overall, though, this book is a good reference.
Related Search : c 3rd , algorithm analysis , edition  |
Author : Alan Agresti
Edition : 2
Number of Pages : 400
Publisher : Wiley-Interscience
List Price : $100.95
Amazon Price : $49.36
Used Price : $49.59 |
Product Description Praise for the First Edition "This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended."
—Short Book Reviews "Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few."
—Journal of Quality Technology "Alan Agresti has written another brilliant account of the analysis of categorical data."
—The Statistician The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses. This Second Edition features: - Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models
- A unified perspective based on generalized linear models
- An emphasis on logistic regression modeling
- An appendix that demonstrates the use of SAS® for all methods
- An entertaining historical perspective on the development of the methods
- Specialized methods for ordinal data, small samples, multicategory data, and matched pairs
- More than 100 analyses of real data sets and nearly 300 exercises
Written in an applied, nontechnical style, the book illustrates methods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Second Edition is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control. Customer reviews an elementary version of Agresti's categorical data analysis by .. Michael R. Chernick (Holland PA)
Agresti is recognized as one of the leading experts in categorical data analysis and his advanced book has received treemendous acclaim. This book has much of the important content of the advanced book but watered down a little to be understandable to a broader audience. Alan Agresti is very good at doing that and therefore this book deserves high praise.
much worse than first edition by .. Stat Grad (NY, NY)
I am a statistics graduate student and have read this book, the first edition of this book, and parts of the full version (Categorical Data Analysis - Agresti 2002). This edition (2nd) of Introduction to Categorical Data Analysis is not as good as the first edition or the 2002 edition. The examples are hard to follow and the SAS output is difficult to replicate in some cases. Do yourself a favor and use the 2002 full version. It will save you a lot of time and frustration.Categorical Data Analysis (Wiley Series in Probability and Statistics)
A great reference! by .. B. Schroeder (North Carolina)
Agresti's book 'Introduction to Categorical Data Analysis' has been very valuable for my research and understanding of logistics regression techniques. I am not a statistics major and so I greatly appreciate his use of examples to discuss the concepts. Rather than getting lost in equations with tons of vectors and matrices, Agresti's book focuses on the core concepts and methodologies you need to prepare your data, set up the models and interpret the results. The companion webpage has the SAS code for most of the examples so you can replicate what he did. Highly Recommended!
Informative and concise by .. Jenny (Laramie, WY)
Categorical Data Analysis covers the basics of categorical data in an informative and inclusive manner. It is understandable to most readers, and it follows in logical order.
Excellent resource for scientists! by .. N. M. McNeil ()
This is an excellent resource. It's clear, concise, and informative. It provides readers w/ the perfect mix of conceptual and procedural knowledge. As other reviewers have suggested, it may be a little too light for hard-core statisticians, but it's perfect for scientists who deal w/ categorical dependent variables. I use it all the time!
Related Search : wiley series , probability statistics , introduction categorical  |
Author : Joseph F. Hair
Edition : 6
Number of Pages : 928
Publisher : Prentice Hall
List Price : $177.33
Amazon Price : $86.79
Used Price : $72.95 |
Product Description For graduate-level courses in Marketing Research, Research Design and Data Analysis. Multivariate Data Analysis provides an applications-oriented introduction to multivariate data analysis for the nonstatistician by focusing on the fundamental concepts that affect the use of specific techniques. Customer reviews Great product, great service by .. amoura (USA)
The book was exactly like new. Great condition. The delivery was faster than expected. I like doing business with this seller.
Multivariate data analysis without equations. Not practical.  by .. Marshall (Chapel Hill, NC)
I have some mathematical background and a very basic statistical formation (undergrad class). I bought this book because I needed to actually do some multivariate data analysis, but I obviously bought the wrong book. For starters... the book doesn't have any equations! There are hundreds of pages of prose used to explain concepts that could have been summarized with simple formulas. This is a good book if you are interested in getting an idea of how statisticians or scientist analyze complex data sets, but I doubt it will help you to really understand the techniques, and let alone, implement them. If you are interested in actually using MVDA, then don't waste your money on this book and buy Johnson and Wichern's book instead.
Ph.D. student actually likes this stats book... by .. J. D. Mason (Stillwater, OK)
I've used several texts in my Ph.D. program but this one was by far the best. While I can't speak to the completeness, as a student I have found this one to have adequate examples, well written explanations, and has served as an excellent reference work for those times when I have needed to use the statistics that I have forgotten everything about except the fact that they exist.
If a prof. has made this a "recommended" (but not required) text and you are on the fence about getting it, you really should buy it - it is an investment you won't regret.
Best general Multivariate stats book by .. shawn carraher (Lawton, Oklahoma USA)
This is without question THE BEST introduction to Multivariate Statistics book currently available. It is designed for the user of the techniques, not someone who wants to examine the math underlying the techniques. I have created a collection of the various editions of this book and I have all of them going from the 1st edition to the current one. Personally I really likely the 2nd and 3rd editions but the current one is also very good. Whether you are interested in Exploratory Factor Analysis, Multiple Regression Analysis, Discriminant Analysis [I think that there should have been more on classification analysis in this section], Logistic regression, multivariate analysis of variance, conjoint analysis, cluster analysis, multidimensional scaling, Confirmatory Factor Analysis or Structural Equation Modeling, this book provides a good broad overview as to how to use and interpret the techniques. The key terms for each technique are defined clearly technique by technique. Having taught faculty how to teach multivariate statistics this is the book that I chose to use. It is important to remember that it is BROAD overview and if you are going to do serious analyses that you'd likely want to get additional books about the specific technique or techniques that you are going to use.
Probably the best advanced stats book ever written...GOD bless the authors! by .. FrozenMusic (Atlanta, GA, USA)
Over the course of my undergrad, grad, and post grad, I have read a variety of statistics books. Without a doubt, Hair's Multivariate Data Analysis is THE BEST book of them all. Here is a brief outline of the awesome features of the book:
1. The book itself is very well organized - chapter order and the order within each chapter helps the reader in knowing what is coming next and provides a sense of direction. I think this is a very important feature for any book to have especially when the topics are complex and are discussed over 800 odd pages.
2. The HBAT data set that comes along with the book (or that is provided by the instructor of the course depending on the version of the book you purchase) is really a very good resource. All multivariate techniques in the book can be carried out using this data set. The data set is clearly explained at the end of the first chapter.
3. Tables of examples, the 'Rules of thumb" after each important concept discussion prove invaluable. This is akin to the managerial implication written at the end of lenghty academic articles. This is almost like saying - Here is the deal folks.....Much precise than the summary section, in bullet points, these rules of thumb acts as quick referece that captures the content of the discussion.
4. From chapter 4 onwards till the very end of the book, each chapter is divided into two halves - the first half is the concept dicsussion - in detail, with examples and in very simple and understandable language. The second half is the illustration of the discussed concept through a very elaborate example using the HBAT data set. This arrangement not only helps the reader in better understanding the complex concepts, but also allows the reader to get their hands dirty by actually working out.
5. Keywords at the begining of each chapter provides a list of all the 'jargon' that would be used in that chapter. This list provides a detail definition of each term. Many times while reading the chapter, you would come across a confusing term and in those times the keyword list can prove invaluable.
All in all, this is an invaluable book. If you are a taking stats and you have not read this book, you are missing something. In spite of all the above great things, the best feature of this book is the writing style. I have not come across a book that explains concepts is such easy to understand language but at the same time not over simplifying the subject matter.
My advanced stats became enjoyable because of this book. Really may GOD bless these authors for writing this book!!
Related Search : multivariate data , analysis 6th , edition  |
Author : John A. Rice
Edition : 3
Number of Pages : 6721
Publisher : Duxbury Press
List Price : $178.95
Amazon Price : $138.16
Used Price : $85.00 |
Product Description This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings. Customer reviews Terrible book by .. Aaron G. Black (St. Paul, MN)
I find it interesting that the postive reviews for this book seem to be from other authors of stats books providing an apology for one of their colleagues! But if you look at the majority of the student reviews, you see that this book is not highly rated. As a student myself using this book for a grad level stats course, I also have to give it a very low score. I found this book to be extremely difficult to understand. I've had other undergrad stats courses but even so I found this text difficult to follow. Things are not explained well and I did not think there were enough examples worked out in detail. I found myself having to resort to using other stats books to actually read and learn concepts and only used this text to reference the problems that my instructor assigned for homework. Kind of a waste for a book that costs $100+!
Never use this book - If this is your first stat course by .. awan (Oh USA)
Be careful this book makes things difficult,try to consult some other books if u do not have another option (Forced as text book).Consider Miller & Freund's book as a much better option.
Was this book written in English? by .. Andrew B. (Phoenix, AZ)
I have a finance degree, a math degree, and an M.B.A. The only reason that I mention this is because in obtaining these degrees, I have had to read alot of books.
Up to this point, there hasn't been a book, if I took enough time reading it, that I couldn't understand. I have given up with this book!
Absolutely Terrible by .. Dragon12 ()
This is my first ever statistic class and by the looks of it I'm going to have to withdraw due to this book. I thoroughly read the book and make every attempt possible to understand statistics as I want to get this class done with. This book offers me no hope. If this is your first every statistic course please find a new book you will have a very hard time. Even my tutor can't believe this book is serious.
Multiple Editions by .. William Erwin (San Diego, San Diego)
I wish that I could review the book however, Amazon (USBOOKSHOPS) shipped the International edition--which is considerably different from the standard text.
Related Search : data analysis , data sets , mathematical statistics  |
Author : Matthew B. Miles
Edition : 2nd
Number of Pages : 352
Publisher : Sage Publications, Inc
List Price : $75.95
Amazon Price : $56.00
Used Price : $56.95 |
Product Description In 1984, the first edition of Qualitative Data Analysis addressed a critical need faced by researchers in all fields of the human sciences - how to draw valid meaning from qualitative data. It provided methods of analysis that were practical, credible and reliable. This groundbreaking book has now been revised to take up where the first edition left off and account for the phenomenal expansion of qualitative inquiry since then. In this second edition, Miles and Huberman bring the art of qualitative data analysis up to date, adding hundreds of new techniques, ideas and references that draw on the experience of the authors and many colleagues in the design, testing and use of qualitative data analysis methods. Each method of data display and analysis is described and illustrated in detail, with practical suggestions for adaptation and use. The growth of computer use in qualitative analysis is reflected throughout this volume, which also includes an extensive appendix on criteria useful for choosing among the currently available analysis packages. Using examples from a host of social science and professional disciplines and stressing a hands-on, practical approach, Qualitative Data Analysis, Second Edition, remains the most complete treatment of this topic available to scholars and applied researchers. Customer reviews The Bible for Qualitative Researchers by .. Bakari Akil ()
This book is one of the main reasons I was able to tackle my dissertation so effectively. It is priceless.
Not very helpful for dissertation work by .. Patrick R. Walden (Fort Lauderdale, FL)
This publication is well organized and covers a large scope of data analysis in qualitative research but did very little, in my opinion, to guide me, as a dissertation author, in the process of coding and thematic analysis. A book entitled Qualitative Data Analysis, I think, should cover the actual analysis of qualitative data more than the type of introduction to design of qualitative research. One finds this information in many, many other titles- and to a more useable extent to boot. Two of the 13 chapters were helpful in meeting my needs (Chapter 4: Early Steps in Analysis and Chapter 10: Making Good Sense: Drawing and Verifying Conclusions) While there is a wealth of information presented in a well-written manner such as information about the display of data, my initial reading of the book was followed by immediate shelving.
useful book for Analysis by .. AShkan ()
This book assisted me in my graduate classes for Kinesiology.
I recommend it for any graduate students who need to take similar classes to mine.
Qualitative Data Analysis: An Expanded Sourcebook(2nd Edition) by .. Frank S. Morris (Phoenix, AZ)
Don't let the date published scare you away from this book. The guides are applicable to any person wishing to perform qualitative data analysis.
Fantastic resource for first-time researchers by .. C. Davis (NY, NY)
As a first time qualitative researcher, I found this book indispensible during my data analysis. It clearly explains multiple analytic techniques, providing the researcher with many alternatives to use in developing conclusions. The descriptions are easy to understand and supported by insightful examples. If you are looking for a roadmap to guide you through qualitative research, this is the GPS of qualitative data analysis.
Related Search : sourcebook 2nd , edition , analysis expanded  |
Author : Marija Norusis
Edition : 2
Number of Pages : 672
Publisher : Prentice Hall
List Price : $85.33
Amazon Price : $65.44
Used Price : $64.49 |
Product Description The SPSS 16.0 Guide to Data Analysis is a friendly introduction to both data analysis and SPSS, the world’s leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With the SPSS 16.0 Guide to Data Analysis, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS. Author Marija Norušis incorporates a wealth of data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners. These data files are supplied with the book and are used throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun! Data CD-ROM included. Customer reviews Excellent Introduction to Statistical Analysis Using SPSS by .. Edward Torpy (Chicago, IL USA)
Marija Norusis is a great writer who can clearly articulate complex statistical concepts that the average person can understand. Her writing style is very conversational without sacrificing technical accuracy. Although this book is designed to be used as an introductory statistics book in a college course, it also serves as an excellent SPSS user's guide. The author describes the logic of hypothesis testing, the concept of "statistical significance", and the general concepts behind data analysis that the new data analyst can easily understand.
Part I. Getting Started with SPSS
1. Introduction
2. An Introductory Tour of SPSS
3. Sources of Data
Part II. Describing Data
4. Counting Responses
5. Computing Descriptive Statistics
6. Comparing Groups
7. Looking at Distributions
8. Counting Responses for Combinations of Variables
9. Plotting Data
Part III. Testing Hypotheses
10. Evaluating Results from Samples
11. The Normal Distribution
12. Testing a Hypothesis about a Single Mean
13. Testing a Hypothesis about Two Related Means
14. Testing a Hypothesis about Two Independent Means
15. One-Way Analysis of Variance
16. Two-Way Analysis of Variance
17. Comparing Observed and Expected Counts
18. Nonparametric Tests
Part IV. Examining Relationships
19. Measuring Association
20. Linear Regression and Correlation
21. Testing Regression Hypotheses
22. Analyzing Residuals
23. Building Multiple Regression Models
24. Multiple Regression Diagnostics
Related Search : 0 guide , data analysis , 2nd edition  |
Author : Alan Agresti
Edition : 2
Number of Pages : 734
Publisher : Wiley-Interscience
List Price : $135.00
Amazon Price : $74.06
Used Price : $74.00 |
Product Description Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Categorical Data Analysis was among those chosen. A valuable new edition of a standard reference.
"A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis."
-Statistics in Medicine on Categorical Data Analysis, First Edition The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis. Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of: Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects Stronger emphasis on logistic regression modeling of binary and multicategory data An appendix showing the use of SAS for conducting nearly all analyses in the book Prescriptions for how ordinal variables should be treated differently than nominal variables Discussion of exact small-sample procedures More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercisesCustomer reviews The source to understand categorical data and more by .. Sunny (Raleigh, NC)
The text is comprehensive in covering categorical data. Other reviews make this clear so I wanted to focus on the following. I was able to understand more general topics in statistics because of Agresti's depth of coverage on CDA. For example, for repeated measurements, Agresti clearly explains marginal models, conditional models, and generalized estimating equations. When I needed to understand these topics, I used this text because I have not found clear explanations elsewhere. In addition, SAS code and R code is available for the examples presented.
the masterpiece by the master by .. Michael R. Chernick (Holland PA)
When this book came out in 1990 it was the first book to provide a truely modern treatment of categorical data analysis for both ordinal and nominal data. It provides an excellent treatment of the asymptotic theory for binary and multinomial data. It is extremely well written and is still a favorite of statisticians and practitioners. Because of its popularity and continued value, it should soon be added to the Wiley Classic series.
This is the first book to take the regression approach to categorical data analysis tieing the subject to the methods and theory of the generalized linear models. It also was one of the first to show the modern practicality of exact permutation methods.
The only drawback of this book is that it is 11 years old and there have been many interesting and relevant research developments in computer-intensive methods, analysis of missing data and mixed effects linear models to make a revision useful. Some of the latest developments can be found in Lloyd's new book "Statistical Analysis of Categorical Data" that was recently published by Wiley.
Agresti provides clear advice and also gives a nice historical perspective on the development of the subject. The book is authoritative and includes numerous relevant references. Each chapter contains many exercises and a wealth of practical examples for illustration of the techniques. This is a good text from both practical and theoretical perspectives. It is excellent for a graduate level course on categorical data analysis.
Dense and comprehensive by .. kmir (Nashville, TN US)
Please read this in addition to the other reviews! I agree with the other reviewers except on one aspect: I found the style of writing a little bit choppy at times. The author uses short sentences when a few connecting words like e.g. "because", "due to", would have made understanding a little easier. Also, examples are not integrated optimally into the text so that there seems to be a gap between abstract conceptual explanations and the examples.
The one to have by .. Peter Flom (New York City)
If you want one book on Categorical Data analysis, this is the one. But there are others that are easier to read, if your math is not great (including the same author's book with an almost identical title)
Good reading, but how do I analyze my data? by .. H. Ward ()
In the theoretical sense, this book provides a very thorough overview of categorical data analysis. However, this book should not be used as a reference for the scientist needing to do the occasional number crunching of categorical data. The examples are vague and the tests are not well explained. If you want to derive the tests, this book is for you. If you're not a statistician at heart and just want the answer, I suggest looking at Conover's "Practical Nonparametric Statistics" for a good explanation of which tests to use and how to use them.
Related Search : series probability , analysis wiley , categorical data  |
Author : Andrew Gelman
Edition : 2
Number of Pages : 696
Publisher : Chapman & Hall/CRC
List Price : $73.95
Amazon Price : $52.86
Used Price : $40.00 |
Product Description Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: ·Stronger focus on MCMC·Revision of the computational advice in Part III·New chapters on nonlinear models and decision analysis·Several additional applied examples from the authors' recent research·Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more·Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life. Customer reviews Decent for engineers by .. John Salvatier (Seattle, WA)
This seems to be the best book out there for learning Bayesian statistics. The book is well written and usually quite clear. I think it be better organized, and pointers to programming examples would be welcomed, especially in the introductory computation section.
I am an engineer, and unfortunately for me, this book is geared towards social scientists. However, no other bayesian statistics books currently teach from an engineering perspective, so this is your best be if you are an engineer.
This book does assume a good deal of familarity with mathematical statistics, which many engineers do not have. However, it is possible to get though it by looking this up on wikipedia.
great coverage of Bayesian Methods including MCMC by .. Michael R. Chernick (Holland PA)
This is a well written text that is fast becoming a classic reference. It contains a wealth of good applications. It is one of the new books that presents the growing use of Bayesian methods in practice since the advancement of Markov Chain Monte Carlo approach. It includes a whole chapter the Markov chain approach to computation. Other strengths of the book include the chapter on missing data and the chapter that provides expert advice. It is one of the best books ever written on the practical aspects of modern Bayesian analysis. I know one of the authors very well (Hal Stern) and am familiar with the fine research work of the others. Don Rubin brings a wealth of knowledge and experience in statistical methods and Bayesian analysis to the table. He is also the inventor of the Bayesian bootstrap.
Another text in the CRC series Markov Chain Monte Carlo in Practice by Gilks, Richardson and Spiegelhalter provides more detail on these methods along with many applications including some Bayesian ones.
Comprehensive, but not well-written by .. dodd9702 (Cambridge, MA)
This book is a very comprehensive treatment of Bayesian data analysis. However, it is not well-written. I find Lancaster's book to be much more well-written and interesting to read.
Very Excellent, but non-statisticians should start elsewhere by .. MrDNA (Spokane, WA)
Gelman's book is an excellent and complete introduction to Bayesian methods. It covers a number of topics not touched by other intros I've read, and focuses much more on regression and ANOVA than other texts.
There are two downsides, coming from someone in psychology. First, the book seems to hover between an introductory text and a more advanced one. The topics covered are mostly introductory, but the examples aren't always entirely easy to follow. A tighter integration with the R and Bugs code would help. Perhaps a section at the end of the chapters containing a code example for each topic would be ideal. It's not that the topics themselves are necessarily opaque, but Gelman moves too fast at times, making it hard to think in terms of notation, theory, experimental design AND code at the same time (for those of us constantly thinking about how this affects our own research).
Second, as a general rule, this book is outside the ken of most psychologists. This is unfortunate since the methods are ideal for our discipline, and since many psychologists already perceive a large barrier of entry to statistics. As a psychologist with minimal undergraduate training in stats, I would (and did) start with a standard statistics book like Casella and Berger, and then move on to a gentler introduction to Bayesian methodology, like _Bayesian Methods: A Social and Behavioral Sciences Approach_ by Jeff Gill. Also, you can barely do anything in this book with SPSS so you'll have to learn R and Bugs.
As Good As It Gets For An Intro To Bayes by .. Charles Saunders (Tallahassee, FL United States)
Yes, it is an introduction to Bayesian methods. That means you have to have a very good understanding of classical statistics (at the level of Casella and Berger would be optimal) and then be willing to use the WinBugs program to further your knowledge. A great book.
Related Search : statistical science , analysis second , edition texts  |
Author : Victoria L. Bernhardt
Edition : 2
Number of Pages : 308
Publisher : Eye on Education
List Price : $39.95
Amazon Price : $33.25
Used Price : $78.25 |
Product Description "Data Analysis for Continuous School Improvement" (First Edition, 1998, Second Edition, 2004) What separates successful schools from those that will not be successful in their reform efforts is the use of one, often neglected, essential element—data. With clear and concrete examples from both elementary and secondary schools, "Data Analysis for Continuous School Improvement" shows what data to gather and how to use data to improve all aspects of schools. "Data Analysis" enables you to find out where you are, where you want to be, and how to get there—sensibly, painlessly, and effectively. Schools are powerful organizations. Every day, across the United States, schools are impacting the lives of millions of children and the future of our very existence. Schools become even more powerfully efficient and effective when data play an active role in their operations. The purposes of this book are to update the original "Data Analysis for Comprehensive Schoolwide Improvement" book with new and improved strategies and knowledge, and to clarify: • why data are important and what data to gather
• how data—gathered, analyzed, and properly used—can make a difference in meeting the needs of every student in the school
•how to communicate and report data results
• the data analyses required to meet "No Child Left Behind" (NCLB) legislation Customer reviews If you're buying this, you HAVE to - but there are better choices by .. Robert Cortez ()
This book contains a lot of good information, but is very redundant - the charts and graphs retell what is written in the text, and it "talks down" to the reader.
If you're buying this book, you probably HAVE TO for a class or something; if you're looking for a book for reference reading, skip it and find a better choice.
Data Analysis for schools by .. M. Birkelund (Plainfield, IL United States)
Extremely practical and useful book! This book was easy to read and to use.
Excellent Book by .. Brian J. Evans ()
The book was exactly what I needed for my Educational Administration classes. It was a required book for my graduate studies.
This book is a critical part of any educators library. by .. Daniel B. Keck (St. Louis, Missouri)
This book is a companion to Barnhardt's work on the school portfolio. It is a beautiful introduction to basic data analysis for teachers and administrators in today's schools. The introduction to data bases, the importance of clear identification of dissagregation points and simple but critical rules of good action research make it a must for anyone interested in real accountability and reflective practice.
This is just what we needed!! by .. ()
Our whole school district and infact 12 out of 13 school districts in the state are using this book along w/ Vickie's other book on School Portfolios.
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