Customer Reviews:
disappointing.......2007-06-01
The book deals quite well with Exploratory Factor Analysis, but the confirmatory part is disappointing. The basics are well explained though. Although it is easy to follow, it doesn't exhaust the topic and doesn't tackle cases that are a little bit more complicated than too-easy-to-be-true book examples. Once you have your data that might be not normally distributed, you will hardly understand how to deal with a CFA with this book. When purchasing this book, I thought I would get answers such as "what goodness of fit indexes to use with non normal data? How do I proceed with SPSS or SAS to compute the CFA? etc."
Book Description
This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and applications of structural equation modeling; 2) demonstrating basic applications of SEM using AMOS 4.0; and 3) highlighting features of AMOS 4.0 that address important caveats related to SEM analyses.
Written in a "user-friendly" style, the author "walks" the reader through 10 SEM applications from model specification to estimation to the assessment and interpretation of the output. Each of the book's applications is accompanied by:
*a statement of the hypothesis being tested;
*a schematic representation of the model under study;
*the use and function of a wide variety of icons and pull-down menus;
*a full explanation of related AMOS Graphic input models and output files;
*a model input file based on AMOS BASIC; and
*the published reference from which each application was drawn.
Customer Reviews:
Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming (Multivariate Applications Series).......2007-02-21
Great book, easy to read. It goes well as a companion book about SEM with a more mathematically heavy text. The author makes using AMOS easy! I've already shown my Professor something about AMOS he didn't know!
Great Resource.......2006-01-29
If you are looking for a good resource on learning how to use AMOS for structural equation modeling, this is definitely the book. It is easy to understand and well laid out. Well recommended, especially for teaching SEM to students.
wonderful if familiar w/stats + new to sem.......2001-08-07
This book is a wonderful guide to understanding a good range of basics about sem, getting models to work with Amos, and interpreting your output. You will need to be familiar with one of the stats packages that Amos is compatible with. Very much user-friendly in this complicated topic. All of the statistically-related and theory-related aspects are well-referenced, so you can find sources to reference for different aspects of sem. A great book to fill the gap between the Amos user's manual and books on sem in general. (contact Erlbaum about educ pricng.)
Average customer rating:
|
Statistics: Concepts and Applications for Science with Workbook
David C. LeBlanc
Manufacturer: Jones & Bartlett
ProductGroup: Book
Binding: Paperback
 General
| Science
| Subjects
| Books
General
| History & Philosophy
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Biostatistics
| Biological Sciences
| Professional Science
| Professional & Technical
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 0763717290 |
Book Description
Designed for students majoring in the life, health, and natural sciences, Statistics: Concepts and Applications for Science is a text and workbook package that introduces statistics with an important emphasis on the real-world applications of statistical reasoning and procedures. Through intensive exposure to the core concepts of statistics in the context of science, students acquire the skills and understanding they need to formulate valid research designs, implement statistical analysis, interpret data, and explain their results.
The workbook component of this package offers students the opportunity to actively apply their knowledge in an extensive set of homework problems, exercises, and study problems. To assist in the learning process, study problems that include a detailed answer key are provided for each chapter. Fully elaborated solutions for all workbook problems are available for instructors.
Book Description
In DATA ANALYSIS BY RESAMPLING, Clifford Lunneborg argues that modern computing power has rendered the model-driven and assumption-plagued data analyses of the past unnecessary, obsolete, and inappropriate. This book introduces readers to modern, design-driven analyses that depend only on the observed data, on knowledge of how the data were collected, and on questions the data were intended to answer. Overall, Lunneborg provides a modern and timely approach to statistical inference.
Customer Reviews:
Applied resampling techniques.......2001-08-14
I took several multivariate analysis courses from Dr. Lunneborg as a grad student at the University of Washington and they were pretty difficult being filled with matrix algebra and derivations. With that background, I was pleasantly surprised to find this book so well organized and applied. I do a great deal of resampling in my research and Dr. Lunneborg has done an excellent job of summarizing the various areas where resampling can save your butt, and where it can kick you in the butt if you are not careful. He provides the algorithms for Resampling Stats (a major resampling software package) and S-plus. I would have appreciated if he had included the code for Sas as well, but in most cases you can easily back it out from the S-plus code. If you are a student or an applied statistician and want to either learn how to use resampling techniques or actually apply it in your work, then this is an excellent book. If you are more mathematically oriented, then you would be better off going to the technical journals and reading the original works by Efron et al. to understand the logical, statistical and mathematical bases of this methodology. I have used the Resampling Stats Excel add-in for several years, so it was very useful to find a book that provides the algorithms for this software.
The latest elementary account on resampling methods.......2000-03-25
Professor Lunneborg covers bootstrap methods, permutation methods and subsampling methods and contrasts them in terms of the sampling design. This is a good introductory text at a fairly elementary level. Like Efron and Tibshirani (1993), Davison and Hinkley (1997) and Chernick (1999), he emphasizes the value of resampling in the age of modern fast computing and explores the variety of applications. This book is unique in that it could be used as an introductory text for students with only high school algebra. It also views the appropriateness of methods according to the experimenters sampling design. Use bootstrap when the data constitute random samples, permutation methods in randomized designs such as randomized trials and subsampling for non-random studies. While this is an interesting way to view the methods it is not universally accepted and both the bootstrap and the permutation tests have been applied in wider contexts.
Book Description
The new volume of Computational Statistics represents a comprehensive overview of Partial Least Squares (PLS) methods with specific reference to their use in marketing and with a discussion of the directions of current research and perspectives.
The handbook covers the broad area of PLS methods -from regression to structural equation modeling applications, software and interpretation of results. It features papers on the use and the analysis of latent variables and indicators by means of the PLS path modeling approach from the design of the causal network to model assessment and improvement.
Within the PLS framework, the handbook also addresses advanced topics such as the analysis of multi-block, multi-group and multi-structured data, the use of categorical indicators, the study of interaction effects, the integration of classification issues, the validation aspects and the comparison between the PLS approach and covariance based structural equation modeling. Most chapters comprise a thorough discussion of applications to marketing and related areas, some tutorials focus on key aspects of PLS analysis with a didactic approach.
This handbook serves both as an introduction for those without prior knowledge of PLS and as a comprehensive reference for researchers and practitioners interested in the most recent advances in PLS methodology.
Book Description
Learn how to develop models for classification, prediction, and customer segmentation with the help of Data Mining for Business Intelligence
In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. Data Mining for Business Intelligence, which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business, uses real data and actual cases to illustrate the applicability of data mining intelligence to the development of successful business models.
Featuring XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of data mining techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples are provided to motivate learning and understanding.
Data Mining for Business Intelligence:
* Provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction, exploration, and affinity analysis
* Features a business decision-making context for these key methods
* Illustrates the application and interpretation of these methods using real business cases and data
This book helps readers understand the beneficial relationship that can be established between data mining and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions.
Customer Reviews:
An Excellent Introduction, Works with Excel.......2007-03-19
Data mining is the extraction of useful information from large amounts of data. Perhaps the best example of this is Amazon. If you go to Amazon to look at a book, you'll find such tidbits of information as a section on the page headlined 'Customers who bought this item also bought' and another 'What do customers ultimately buy after viewing this item?'
That's datamining, dozens or hundreds, or thousands of people looked at the page about this item. Then they went on to take these other actions. Among all the data that Amazon has collected they mine their database and pull out information to fill in these blocks.
This book, intended for MBA level students gives an excellent introduction to data mining. It further includes access to an Excel add-in called XLMiner that is specifically set up to allow the student to use Excel to learn how data mining is done.
The one thing I would ask the authors to do in their next edition is to provide a brief review of the commercially available data mining software products that are available. If not all of the software, perhaps just the top half dozen or so. In real life we aren't going to use Excel for data mining, our data resides in a database somewhere.
Condensed Discussion of DataMining.......2007-02-10
This book discusses some of the techniques used
in Data Mining.
It goes into Data Exploration as well as Evaluating
Classification and Predictive Performance.
Some of the more advanced techniques such as
Neural Nets and Cluster Analysis are
also discussed.
To learn more about database design and relational data modeling visit
[...]
From the authors:.......2007-01-27
This book got its start as notes for a data mining class that one of us (Nitin Patel) was teaching at MIT, and was completed while another of us (Galit Shmueli) was teaching a similar course at Maryland. Both courses were part of an MBA program. We found that, while there are a lot of books on data mining, there were none that actually gave business students the skills and tools to implement data mining algorithms. So we set ourselves the task of writing a book that (1) provides real data sets with a business decision-making context and a hands-on orientation , (2) provides a theoretical and practical understanding of the key data mining methods of classification, prediction, data reduction and exploration at a level that is appropriate and useful for MBA's, and (3) bundles a powerful version of a commercial data mining tool that works in Excel (XLMiner). For this reason, we think our book will be appropriate not just for students, but also for business analysts with a quantitative orientation, on, indeed, anyone who wants to learn data mining via self-study. Have we succeeded? You be the judge! - P. Bruce (for G. Shmueli and N. Patel)
Book Description
This book illustrates the ease with which various features of LISREL 8 and PRELIS 2 can be implemented in addressing research questions that lend themselves to SEM. Its purpose is threefold: (a) to present a nonmathmatical introduction to basic concepts associated with SEM, (b) to demonstrate basic applications of SEM using both the DOS and Windows versions of LISREL 8, as well as both the LISREL and SIMPLIS lexicons, and (c) to highlight particular features of the LISREL 8 and PRELIS 2 progams that address important caveats related to SEM analyses.
This book is intended neither as a text on the topic of SEM, nor as a comprehensive review of the many statistical funcitons available in the LISREL 8 and PRELIS 2 programs. Rather, the intent is to provide a practical guide to SEM using the LISREL approach. As such, the reader is "walked through" a diversity of SEM applications that include both factor analytic and full latent variable models, as well as a variety of data management procedures.
Customer Reviews:
Structural Equation Modeling With Lisrel, Prelis, and Simpli.......2000-05-05
Offer different softwares(LISREL8, PRELIS2,SIMPLIS) and cover single, multiple groups analyses and provide MTMM model, I thought Dr. Byrne's book one of the most useful resource to apply structural equation model for social science research.
Book Description
Practical and up-to-date,
Structural Equation Modeling includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. Written by internationally recognized leaders in structural equation modeling, this book targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences.
Customer Reviews:
Highly Theorectical.......2006-03-03
Comprehensive coverage of SEM, highly technical and heavy with references. Better for advanced students of SEM rather than novices.
A must read for the novice SEM user.......1998-08-29
This book was my saving grace in writing my dissertation. The book provides an excellent review of SEM's concepts, issues, and applications in both EQS and Lisrel, in a manner which is understandable to a budding researcher.
Average customer rating:
|
Investigating Statistical Concepts, Applications and Methods, Preliminary Edition
Allan J. Rossman , and
Beth L. Chance
Manufacturer: Duxbury Press
ProductGroup: Book
Binding: Paperback
General
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 0534391109 |
Book Description
This text contains a balanced mixture of investigations and exposition. The activities lead students to explore and discover statistical ideas and techniques, while the exposition explains and reinforces what the activities are designed to reveal. A combination of practice, homework, and application problems all focus on actual studies. The book is intended for a course that provides mathematically inclined students with a data-oriented and conceptually based introduction to the fundamental ideas and techniques of statistics. Additional resources are available from the authors at http://www.rossmanchance.com/iscam/.
Book Description
INVESTIGATING STATISTICAL CONCEPTS, APPLICATIONS, AND METHODS (WITH CD-ROM) combines investigation and exposition to explore statistical ideas and techniques. Many of the investigations ask you to use technology such as statistical software and Java applets. A combination of practice, homework, and application problems emphasize actual studies.
Customer Reviews:
Utterly useless text........2006-12-15
Key formulas were scattered everywhere, with students being required to work through the caveats on their own. For teachers thinking this is a great idea, bear in mind that the vast majority of your students even at elite colleges and graduate programs will not have the time nor will be willing to expend the effort. Unique numbering system for problems, as well as not uniformly placing them at certain points in each section, caused students to frequently turn a wrong question or two on problem sets or not be able to find a question at all. Most students began reading online definitions of concepts instead.
Books:
- Extraterrestrial Contact: The Evidence and Implications
- Extraterrestrial Contact: The Evidence and Implications
- Faust's Metropolis: A History of Berlin
- Fishing the Everglades: A Complete Guide for the Small Boater
- Flotsam (Caldecott Medal Book)
- Food of the Gods: The Search for the Original Tree of Knowledge A Radical History of Plants, Drugs, and Human Evolution
- Frontiers of Complexity: The Search for Order in a Chaotic World
- Fundamentals of Anatomy & Physiology (7th Edition) (MyA&P Series)
- Fuzzy Sets and Fuzzy Logic: Theory and Applications
- Getting Started with MATLAB 7: A Quick Introduction for Scientists and Engineers (The Oxford Series in Electrical and Computer Engineering)
Books Index
Books Home
Recommended Books
- Dwight D. Eisenhower: Soldier, President, Statesman
- Choosing a Jewish Life: A Handbook for People Converting to Judaism and for Their Family and Friends
- Transgressions: The Offences of Art
- Walled Gardens
- 104 Activities That Build: Self-Esteem, Teamwork, Communication, Anger Management, Self-Discovery, C
- Applications of Interval Computations
- A Field Guide to the Birds of Eastern and Central North America
- Miss America 1945: Bess Myerson and The Year That Changed Our Lives
- Who's in Charge Here, Anyway: Reflections on a Life in Business
- MacArthur and the American Century: A Reader
Principles and Practice of Structural Equation Modeling, Second Edition (Methodology In The Social Sciences)
Easy Guide to Factor Analysis
Scaling Procedures: Issues and Applications
Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research
Confirmatory Factor Analysis for Applied Research (Methodology In The Social Sciences)
