"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.
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
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 collection Bayesian 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:
Comprehensive, but not well-written.......2007-01-06
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.......2006-06-05
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.......2005-10-28
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.
It is a good book, but not a bible of Bayesian analysis........2005-08-31
[1] A good introductory book, but definitely not a bible of Bayesian analysis.
[2] The example-based introduction may be a try of new generation of Bayesian. Many people, especially the beginners, may like this style.
[3] Some of the authors are good at programming in BUGS, R, etc, so the part of MCMC methods seems worthy to skim through.
[4] The book is suitable for the undergraduate and the first year graduate level.
A good introductory book, but..........2005-01-26
I read the other reviews and agree with them to some extent. This is
a good introduction to applied Bayesian analysis. Lots of
good examples, illustrations and exercises.
If you are the kind of person who learns by way of examples, then
this might be the text book for you. If you are looking for the
bigger picture, then you will be lost here. There is very little in the way
of theory. Why is this the right method? What is gained theoretically
over a frequentist method? What are the theoretical properties of the
proposed approach? To a large extent these kinds of questions remain a mystery.
In terms of flexibility an applied Bayesian approach has some decided
advantages. However, in terms of theory
it's almost as if the authors want you to believe that once
you adopt the Bayesian approach then the benefits of averaging
by way of using a prior will always be the right thing to do.
You could argue that advanced questions like this are better suited for
a more advanced text book. I tend to ask more out of a book.
Book Description
The emphasis of the text is on data analysis, modeling, and spreadsheet use in statistics and management science. This text contains professional Excel software add-ins. The authors maintain the elements that have made this text a market leader in its first edition: clarity of writing, a teach-by-example approach, and complete Excel integration.
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
Assuming no prior MATLAB experience, this clear, easy-to-read book walks readers through the ins and outs of this powerful software for technical computing, including:
- Generously illustrated computer screen shots and step-by-step tutorials applied in the areas of mathematics, science, and engineering
- Clearly shows how MATLAB is used in science and engineering
- Includes a completely new chapter on Symbolic Math
- Thoroughly updated to match Matlab's newest release, Matlab 7
Customer Reviews:
Great for learning the basics of MATLAB........2007-08-18
I purchased this title because I am starting a numerical analysis sequence next year using Matlab and I knew only how to plot in 2D and do simple calculations at the command line. After studying from Gilat's text for the past month or so I feel very comfortable using Matlab for all the basics and I am ready to learn how to exploit the full power of the program.
Each chapter gives just enough mathematical background to provide anyone with at least college algebra/trig enough to understand what is going on.
Although this book does not cover any topic too deeply, it does cover the fundamentals of many aspects of Matlab in a way that allows the reader to move fairly quickly through the whole book without getting bogged down in any one area.
In the end you will know the basics about how Matlab operates: how to work with vectors and matrices, how to write simple programs and function files, how to plot and format data, how to fit data to a curve, and how to differentiate and integrate both numerically and symbolically, and a bunch of other great tools for solving problems.
Also, as the other reviewers mentioned, the book makes very good use of graphics to show how input and output should look, as well as what exactly each line means.
I would recommend this text to anyone wanting to learn the basics of Matlab.
Reader.......2007-04-23
If you plan to start with Matlab with no prior experience, this book beats most of the other available titles.Since an inside view of the book is not available on Amazon, I will for the benefit of others list out the chapters here.Ch1 begins with the necessary introduction,developing familiarity with the command window,display formats and precedence of operators.It moves on to Ch2 and Ch3 where arrays are introduced and the mathematical operations on them explained.Ch4 is about script files,Ch5 on elementary plotting techniques using in-built functions like plot and fplot.Ch6 introduces functions and Ch7 extends the previous material to formal programming techniques like loops and control structures.Ch8 explains curve fitting and interpolation,Ch9 is about three dimensional plots and special graphics.Ch10, the last one of the book uses Matlab to do symbolic math which cover elementary algebraic equations.The examples contained in the book are from elementary physics and engineering,so if you are looking for more advanced material that has been treated using Matlab,this might be a little less helpful.The numerical techniques again cover simple problems like projectile trajectory,flow of water from a vessel with a small hole punched in its sidewall,RC circuits, viscosity and so on.Relatively advanced topics like Fourier transforms and applications to signal processing are also left out.If you are done with this book or feel that the material isnt of much help, I will suggest that you might try "Numerical Computing with Matlab" by Moler(he is perhaps one of the architects of Matlab).This book(electronic version) is available for free from the mathworks website [...].Overall this book does a good job in explaining details and is also generously sprinkled with figures and screenshots.Please try it if you are first timer to Matlab.
Very good introduction.......2006-05-04
I had never used matlab when I started reading this book and I found it very easy to follow. I now have a good working understanding of the matlab basics and I recommend that anyone who's looking to get started with matlab pick up a copy.
The perfect introductory text for MATLAB.......2005-12-08
If you are completely new to MATLAB then you will find no better book to guide you through the basics. It is perfectly suited for teaching yourself several basic but still very interesting and useful programming techniques. Topics are presented to the reader in an order carefully determined to produce maximum benefit and knowledge. The book is short and very readable, with many example programs.
In short: if you want a FIRST introductory textbook for MATLAB, you can't beat this book. And it covers the latest version (Release 14).
A truly excellent text!.......2005-11-21
This book was written for teaching Matlab to freshmen in an introductory engineering course, so most of the examples are from first year physics and engineering. Nevertheless, after looking at all competing texts, I chose it to teach Matlab to sophomore geology majors, most of whom had not yet taken calculus or physics. I was very happy with the results; by the end of the semester the students were well on their way to being competent programmers, and I think they will find calculus and physics much easier because of their experience with this book.
I chose this text because it is very well written--you can tell the author has had long experience teaching the subject--and because of its many excellent examples. Most people learn faster by example than by theory, and the examples in this book are easier to follow than those of other texts. Each example shows the command window with a gray background and white insets, or call-outs, containing explanations. The pages are attractive.
In the main text, Matlab commands are set in Courier to clearly distinguish them from the discussion itself. Sections are fairly short and easy to follow, and at the end of each chapter there are many problems of gradually increasing difficulty. The solutions to some problems are given at the back of the book. The abundance of complete examples makes it easy to skip around in the book as soon as students are familiar with Matlab syntax. There are astonishingly few typos and none were serious. Cell arrays and structures are used only where needed for particular commands, a wise pedagogical decision. I particularly enjoyed the second edition's new chapter on symbolic math, as I had never used this part of Matlab in my own research.
The book is 7.5"x9.25" in size with 343 pages, and so is easy to carry around. It's inexpensive, as textbooks go nowadays.
Book Description
The SPSS 14.0 Guide to Data Analysis is a friendly introduction to both data analysis and SPSS. 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 book, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS. The goal of this book is to provide an unintimidating introduction to data analysis and to SPSS. This edition focuses on topics that interest today's students-in particular, the role of the Internet in society. It is designed for use with SPSS 14.0, including the Student Version. A data CD is included with this book.
For additional information, go to http://www.norusis.com This site offers a detailed Table of Contents, features, examples included in the book, and a sample chapter for download.
Customer Reviews:
Excellent for learning to do SPSS software and/or to learn/understand statistics.......2007-09-21
I have used this book (previous editions) in teaching a graduate level research methods and statistical software class in the late 1990s. It is the best book available for anyone who needs to use SPSS or who needs to know how to organize data, interpret statistical output and understand the process of quantitative research. I now teach short courses and do statistical consulting for faculty, staff and students at a university. Whenever anyone asks what I recommend if they want to get SPSS and/or statistical thinking, its a no brainer. This book is hands-down the best for either or both of those goals.
Stats made easy.......2007-06-12
The book is written in an easy to understand language. The examples help to recreate the steps explained in the different chapters. I can only recommend this book.
Wrong Item.......2007-01-05
I had to return this since it did not indicate that it was "student version" which limits the number of variables.
teaches statistics and SPSS .......2006-07-11
In the humanities and social sciences, SPSS is probably the most heavily used statistical package. Norusis helps you understand why. Even if you do not have a strong background in statistics. The book teaches both statistics and the use of SPSS to analyse your statistical data.
The text starts off with the most basic material, like showing a simple frequency table. Or displaying it visually using a pie chart or a bar chart. Then, when there are too many values for a bar chart, you can use a histogram, which has bins, each representing a range of values of the independent variable. SPSS has the ability to quickly display in these formats.
Then the text progressively takes you into analysis. Starting with the computation of mean, median and variances. Later, when there are several independent variables, other graphing formats like scatterplots come into play. But the more challenging sections involve testing hypothesis. From these come the use of chi square tests, Student's T-distribution, nonparametric tests and so on.
If you make it through the book, you get an impressive self taught education in statistics and SPSS.
Average customer rating:
- I liked it
- A good book
- Excellent Reference, Not For Beginners.
- Excellent
- More Than a Simple Spread Sheet
|
Statistical Analysis with Excel For Dummies
Joseph Schmuller
Manufacturer: For Dummies
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ASIN: 0764575945 |
Book Description
- This book makes it easy to crunch numbers and interpret statistics with Excel, even for the math-challenged
- Using plain English and real-life examples, the author provides information that will help readers improve their performance on the job or in the classroom
- Covers formulas and functions, charts and PivotTables, samples and normal distributions, probabilities and related distributions, trends and correlations, as well as statistical terms like median vs. mean, margin of error, standard deviation, permutations, and correlations-all using Excel
Customer Reviews:
I liked it.......2007-08-23
very helpful for someone who has little previous knowledge of the subject. I needed a simple lead in and this provided.
A good book.......2007-05-04
I bought this book as a reference for Stats analysis , it is good for this , dont buy if you expect to get a deep knowledge in the subject.
Excellent Reference, Not For Beginners........2007-02-09
I bought this book to help me with the statistical analyses involved with my senior dissertation at my university. I am a psychology major and I could use all the help I could get understanding the Results Sections in the literature. This book explains all kinds of statistics, including the very helpful ANOVA and regression analysis amongst many other. However, it doesn't explain very well when or why you use these statistics. They don't provide many examples of research or problems that require such analyses. This book is great for a step by step tutorial using Excel and handwriting statistics problems, and reading your data.... but unless you have an idea of what you're looking for in the first place, don't bother. I am totally ignorant to statistical analyses and coming into this book, I didn't know when to use ANCOVA or even what precisely it was demonstrating in relation to the research I am conducting... and I still only have a vague idea... Hopefully this will all be explained in course. But, this is a valued reference for all Excel users, without a doubt!!
Excellent.......2005-03-17
This book is excellent for seasoned Excel users and people who were taught (but didn't learn) statistics in your average graduate school program. I have never seen statistical concepts so briefly and at the same time well explained. Actually applying the concepts adds another level of learning. I highly recommend this book.
More Than a Simple Spread Sheet.......2005-03-05
Excel is of course first and foremost a spreadsheet. They were designed to allow you to play what if senarios. You can change this part of the budget to see what the effect is over there.
But beyond the spread sheet functionality Excel has numerous functions and capabilities to do all kinds of analysis capabilities.
This book is on using these functions to perform a whole range of statistical functions. Not only does this book cover the functions themselves, but gives the background and description of what this particular kind of function is doing. Both numerical analysis and charting functions are included and in detail.
Don't skip the part in this book called the Part of Tens. This section in the For Dummies books often has some interesting points, but here the summation of statistical limitations is just great.
Book Description
Biomedical and social science researchers who want to analyze survival data with the SAS System will find just what they need with this easy-to-read and comprehensive guide. Written for the person with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book ensuring that even the uninitiated becomes a sophisticated user of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered such as time-dependent covariates, competing risks, and repeated events.
Supports releases 6.09 and higher of SAS software.
Customer Reviews:
Nice reference for survival analysis.......2007-01-11
So far, this book has been a useful reference for survival analysis. It is clearly written and the xplanatins are understandable and helpful. It would be nice to have a newer edition that addresses changes in later versions of SAS.
Learn By Doing.......2005-06-14
If you have data that fit the general category "time to event," and are not suitably analyzed by repeated measures ANOVA, you are probably looking at doing a survival analysis (also known by several other names). If you are working largely on your own, and you learn best by doing, you cannot--as far as I know--do better than Allison's book. Of course it all but locks you into using SAS for analyses, but his explanations of proportional hazards and other models are the best I've found among a dozen textbooks and stats package manuals (some of which made sense only after reading Allison). What makes this book so good is that it will have you running your analyses in just hours. The examples are superb take-off points. I was not a SAS user before reading the book and therefore took a little extra time to figure out dataset manipulations and such in SAS, but that was minor effort compared to the rewards of having Allison's clearly written book as a guide. The price of this book represents only a fraction of its value.
Extraordinarily Clear and Useful.......2000-02-06
I've used a number of this author's books and they all share in common lucidity, utility, and rigor. This book makes it easy to grasp complex ideas, provides comprehensible examples, gives sample SAS code so that implementing the methods is as straightforward as possible. Plus, it is clear that the author is a subtle and first-rate methodologist, who innovates in this area as well as teaches it.
Best how-to book on survival analysis using SAS. Very useful.......1999-06-22
This book is well-written, well-organized, and very practical. I found it invaluable in conducting my research. My only recommendation for the author for his next edition is to include a chapter on dealing with correlated event times, like time-to-promotion and time-to-quiting in his policemen example (pg 249).
Book Description
This popular text provides an accessible guide to the application, interpretation, and pitfalls of structural equation modeling (SEM). Reviewed are fundamental statistical concepts--such as correlation, regressions, data preparation and screening, path analysis, and confirmatory factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression models, latent growth models, and multilevel SEM. The companion Web page offers data and program syntax files for many of the research examples, electronic overheads that can be downloaded and printed by instructors or students, and links to SEM-related resources.
Customer Reviews:
Excellent introduction to SEM.......2007-01-10
Kline's book provides a very readable introduction to and explanation of structural equation modeling. The book does not include statistical proofs, so it would not serve well as an advanced text. But if you are looking for a book that explains what SEM is and how it fits within the larger framework of inferential statistics, I recommend it.
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