7/31/2011

A Beginner's Guide to Structural Equation Modeling: Third Edition Review

A Beginner's Guide to Structural Equation Modeling: Third Edition
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No one expects statistics to be easy reading, especially when it concerns complicated models such as structural equation modeling (SEM). Nevertheless, this book manages to do just that.
Schumacker and Lomax have successfully put together a guide that explains to beginners (like myself) in simple terms how the whole thing works. As with most books that treat complex models, some basic knowledge of statistics is preferable before you begin to read it. But if your statistics is rusty and you have only vague impressions of probability sketches in your memory, fear not! Schumacker and Lomax are kind to us poor souls, and begin by introducing some basics in chapter 1 to prod your memory: terminology, variable scales, how to treat missing data, outliers and normality. And in chapter 2, they discuss correlation and covariance.
Before talking about structural equation models, Schumacker and Lomax dedicate chapter 3 to a number of statistical methods on which SEM is built. This chapter gives a basic overview of regression, path analysis and factor analysis. The review of these methods helps you to understand SEM better later on. They also provide an excellent understanding of the methods, in case you have not used them before or it's been a while ...
The rest of the guide covers SEM: how to develop and measure a model (chapters 4 and 5), how the model parameters are estimated and how you can check for reliability and validity (chapter 6), and checking for goodness of fit of your model (chapter 7).
In chapter 8, you are shown some examples of computer outputs by two software packages that can conduct SEM, EQS5 and LISREL8-SIMPLIS.
Chapter 9 goes into more detail on models and diagrams (regression, analysis of covariance, path, measurement and structural models). For those that feel by this point that they've gained enough experience, advanced topics such as cross validation, simulation, bootstrap and jacknife methods as well as multiple same and interaction models are covered in chapter 10. And for the super-keen, the technical bits are covered in chapter 11 (health warning: you better be up to speed on matrix algebra).
The great thing about this book is that you most likely will be able to run models and interpret results by chapter 7, and you don't need to go into the nitty-gritty if you don't want to. On the other hand, the details are there if you need them. In essence, the authors start at the beginning, building up slowly until you are able to handle a basic model, before going into more complex issues.
One drawback, I have found, is that this book was published in 1996. That's nearly a decade ago, and (fortunately) computer power and statistical modeling has come a long way since then. The authors, for example, are convinced that WordPerfect is the software of choice for word processing and that at some point in the future it would be possible to copy and paste diagrams into a word processing program. We've come a long way since then. Today, many SEM packages exist that are much more user friendly than some of the older stodgy packages that require you to enter data in a very specific way and interpret results by going through reams of data output. As such, the authors (or publishers) probably ought to update it with a second edition.
Nevertheless, the strength of the book lies in its guidance and explanatory power. And even if you use a different package, you can skim through the data outputs they use, and focus on your model, how to construct it, and of what pitfalls to beware.
I highly recommend this for anyone starting on SEM - your modeling days will be much happier with this guide.

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This best-seller introduces readers to structural equation modeling (SEM) so they can conduct their own analysis and critique related research. Noted for its accessible, applied approach, chapters cover basic concepts and practices and computer input/output from the free student version of Lisrel 8.8 in the examples. Each chapter features an outline, key concepts, a summary, numerous examples from a variety of disciplines, tables, and figures, including path diagrams, to assist with conceptual understanding.The book first reviews the basics of SEM, data entry/editing, and correlation. Next the authors highlight the basic steps of SEM: model specification, identification, estimation, testing, and modification, followed by issues related to model fit and power and sample size. Chapters 6 through 10 follow the steps of modeling using regression, path, confirmatory factor, and structural equation models. Next readers find a chapter on reporting SEM research including a checklist to guide decision-making, followed by one on model validation. Chapters 13 through 16 provide examples of various SEM model applications. The book concludes with the matrix approach to SEM using examples from previous chapters.Highlights of the new edition include:A website with raw data sets for the book's examples and exercises so they can be used with any SEM program, all of the book's exercises, hotlinks to related websites, and answers to all of the exercises for Instructor's onlyNew troubleshooting tips on how to address the most frequently encountered problemsExamples now reference the free student version of Lisrel 8.8Expanded coverage of advanced models with more on multiple-group, multi-level, & mixture modeling (Chs. 13 & 15), second-order and dynamic factor models (Ch. 14), and Monte Carlo methods (Ch. 16)Increased coverage of sample size and power (Ch. 5) and reporting research (Ch. 11)New journal article references help readers better understand published research (Chs. 13 - 17) and 25 % new exercises with answers to half in the book for student review.Designed for introductory graduate level courses in structural equation modeling or factor analysis taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. An understanding of correlation is assumed. To access the website visit the book page or the Textbook Resource page at http://www.psypress.com/textbook-resources/ for more details.

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Data Modeling Made Simple: A Practical Guide for Business and IT Professionals, 2nd Edition Review

Data Modeling Made Simple: A Practical Guide for Business and IT Professionals, 2nd Edition
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I think very highly of Data Modeling Made Simple (the first edition), so when this second edition came out I had great expectations - which were not only met but also exceeded. Although this second edition is more than twice the number of pages as the first edition, it is still an easy read.
Here are my favorite things about this book:
1.Clearly delivers on its ten objectives. Read the back cover and you will understand the key takeaways you will get after reading the book. After I read the book, I went back over each of these objectives and I was able to check each of these off as accomplished. Everything from justifying the model to building data models to assessing data models was knowledge I gleaned from the book. If you are interested in just one or a subset of these ten objectives, read the Read Me First section and it will reference the sections and chapters you need to read to meet your specific objective.
2.More examples more thoroughly presented. The first edition took a business card example from beginning to end. This edition further expands the business card example and adds several other examples including an ice cream example and many real world examples. The author uses spreadsheets to illustrate many modeling examples, and I too have found spreadsheets to be a very effective way to communicate data and business rules.
3.Data Model Scorecard. The first edition touched on the Scorecard which is the author's technique to reviewing a data model. This second edition goes into detail including providing the template which I can use on my modeling assignments to review my models.
4.Treating a dimensional model as more than just a physical data model. Many texts treat the dimensional as only a physical data model yet there is a business level that this book illustrates at both the subject area and logical levels.
5.Getting other Greats for free. Bill Inmon, Graeme Simsion, and Michael Blaha have all written chapters in this book. I have already starting using Simsion's technique of a diary on my assignments and found it very useful.
My only area for improvement would be to expand the book with more modeling conventions such as ORM and IDEF1X. There is a chapter on UML though that I did find informative. I question however if adding these extra notations would detract from the book's simplicity.
Overall, an excellent read that I would recommend to every business or techie that works with data.


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Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives:
Know when a data model is needed and which type of data model is most effective for each situation
Read a data model of any size and complexity with the same confidence as reading a book
Build a fully normalized relational data model, as well as an easily navigatable dimensional model
Apply techniques to turn a logical data model into an efficient physical design
Leverage several templates to make requirements gathering more efficient and accurate
Explain all ten categories of the Data Model Scorecard
Learn strategies to improve your working relationships with others
Appreciate the impact unstructured data has, and will have, on our data modeling deliverables
Learn basic UML concepts
Put data modeling in context with XML, metadata, and agile development


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Financial Modeling - 2nd Edition: Includes CD Review

Financial Modeling - 2nd Edition: Includes CD
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I have used Simon Benninga's "Financial Modeling with Excel" for five years to teach undergraduate computational finance [...]. My thinking remains that my students have been well served by this textbook.
The inadequacies that limit my assessment to four stars and need to be addressed in the third edition are: 1) frustrating errors in the text and models, for which the errata sheet and corrected models (available at: [...] only improve, but do not heal. My students find new, undocumented, errors each semester. 2) the data sets and examples are getting, frankly, a little old. It is the year 2005 as I write this, but the data sets and examples end in 1999, a year in which my current students were in high school. 3) the models, while excellent as introductions to the field, are now at the point of being fundamental, rather than exemplary. This is not Prof. Benninga's fault, but as the other reviews from professionals here attest, Excel modeling has advanced in all fields (option pricing, financial statements, portfolio optimization, bond metrics, etc). When this volume was introduced, it was adequate for helping MBA and Master of Science in Finance students build essential modeling skills. Sadly, it now is only appropriate for raw beginners or undergraduates. A new text with a larger scope that addresses advances in the fields is called for. 4) While it is a subject in itself, the book is seriously hindered by not introducing basic Monte Carlo simulation in Excel. 5) No information on downloading data from BLOOMBERG, REUTERS, and other historical and market data providers. It would add to the scope of the text, but 6) fitting DCF models to yield curves also would be welcome.
Even with these criticisms, Benninga's Financial Modeling remains the best book in the field for what it seeks to accomplish. It covers the major topics of finance that are appropriately addressed with models: financial statement, firm valuation and credit metrics, portfolio construction, fixed income metrics, option pricing, etc. Benninga's FM also compares favorably with his two nearest competitors.
Powel and Baker's "The Art of Spreadsheet Modeling" is a two pronged monster: it seeks to be a meta-level theoretical work on spreadsheet modeling, and then introduces modeling Monte Carlo simulation as a fundamental component of Excel (a student edition of CrystalBall is included in the text, and is the only reason to buy this book). The gap between the two is a Grand Canyon's worth of knowledge space that this text does not fill in and nearly ignores. The student who uses only Powel and Baker is ill served; whereas if he uses Benninga, he knows how, why, when and what to model. Consider Powel & Baker as sketches of a concept car with simulated wind tunnel runs, whereas Benninga shows how to build your own kit car and drive it around. Powel and Baker's concept car is beautiful, advanced, gracious, but doesn't exist and doesn't run; Benninga's kit car is like a Lotus Super Seven: simple, runs, is a blast to drive, but is dangerous in heavy traffic and you would not want to go on a 1,000 mile journey with it (i.e. or build a DCF model for the Goldman Sachs LBO team with only Benninga).
Chandan Sengupta's "Financial Modeling Using Excel and VBA" is the only book that comes close to Benninga, and I recommend it as another perspective for my students who want to continue with financial modeling. However, Sengupta's work is flawed on two counts: 1) it is clear throughout that he had read Benninga, and 2) he dropped much of Benninga's content in favor of adding wordy explanatory paragraphs to soften the blow of the fact that modeling is mathematically and technically both boring and intense work. With those criticisms in mind, his work still has neater, leaner, more compressed models with updated contemporary detail.
There are three other books, Scott Proctor's "Building Financial Models with Microsoft Excel: A Guide for Business Professionals," which focuses on building vanilla financial statements, as does John Tjia "Building Financial Models." Mary Jackson & Mike Staunton's "Advanced Modeling in Finance using Excel and VBA" is also now dated and seriously flawed and limited in scope), however it is the next step following Benninga.
For those working in top-tier banks, the internal training and modeling documents, and examples built by colleagues, will likely surpass by light years what is offered in these books. And so for beginners, Benninga remains the the best choice and first step, until something better comes along, or Benninga himself produces a new edition.

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Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. Financial Modeling bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial models with spreadsheets. Simon Benninga takes the reader step by step through each model, showing how it can be solved using Microsoft Excel®. In this sense, this is a finance "cookbook," providing recipes with lists of ingredients and instructions.Areas covered include computation of corporate finance problems, standard portfolio problems, option pricing and applications, and duration and immunization. The second edition contains six new chapters covering financial calculations, cost of capital, value at risk (VaR), real options, early exercise boundaries, and term structure modeling. A new technical chapter contains a potpourri of tips for using Excel®.Although the reader should know enough about Excel™ to set up a simple spreadsheet, the author explains advanced Excel® techniques used in the book. The book includes chapters dealing with random number generation, data tables, matrix manipulation, and VBA programming. It also comes with a CD-ROM containing Excel® worksheets and solutions to end-of-chapter exercises.

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7/30/2011

College Algebra with Modeling and Visualization (4th Edition) Review

College Algebra with Modeling and Visualization (4th Edition)
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This book is the cat's ass. It was required for my online algebra course. This basically consisted of teaching yourself the material using only the book and then heading to the professor's office hours if you had any problems/questions. So I taught myself college algebra using only this book and I received an A for the course. I haven't used any other college algebra books so I have nothing to compare it to. But this book will definitely lay it all out for you and get you where you need to be. Highest recommendation!

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Gary Rockswold teaches algebra in context, answering the question, "Why am I learning this?" By experiencing math through applications, students see how it fits into their lives, and they become motivated to succeed. Rockswold's focus on conceptual understanding helps students make connections between the concepts and as a result, students see the bigger picture of math and are prepared for future courses. Introduction to Functions and Graphs; Linear Functions and Equations; Quadratic Functions and Equations; More Nonlinear Functions and Equations; Exponential and Logarithmic Functions; Trigonometric Functions; Trigonometric Identities and Equations; Further Topics in Trigonometry; Systems of Equations and Inequalities; Conic Sections; Further Topics in Algebra For all readers interested in college algebra.

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The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition) Review

The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition)
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There are a lot of data warehousing books out there that try to answer the question: 'Why'? Why data warehouses are needed to help businesses make better decisions - why the OLTP systems that run the business can't do this - and sometimes even why businesses ought to invest in data warehouses. These books were terrifically useful to us years ago, when we needed help (and scholarly footnotes) in our data warehouse project proposals. This book is not one of those - it is all about:
How
How to actually design and build a repository that will deliver real value to real people. In this reviewer's opinion, Ralph Kimball's many contributions related to the 'how' of data warehousing stand alone.
An engineer wishing to jump-start his or her data warehouse education would need to read Ralph's Data Warehouse Toolkit first edition, his Data Webhouse Toolkit... a bunch of "Data Warehouse Designer" Intelligence Enterprise magazine articles... AND lurk on the Data Warehousing List Server...for a few years (all terrific resources - by the way) - in order to stockpile the knowledge that is crisply presented here.
No shortcuts taken by the authors that I can spot: all of the toughest dimensional design issues that I've tripped on - and that I can remember surfacing on in discussion groups over the past few years - are addressed in this significantly updated text. Not all of the solutions are 'pretty' - but it is clear that they thoughtfully address the problem. This approach, in my opinion, instills student confidence - and lets us know that we are getting sound instruction - not dogma.
The authors have been listening to and addressing the data warehouse community's 'pain' through periodicals and posts for years - but this book pulls these point solutions together very nicely. I learned a surprising number of really useful new techniques, and was genuinely enlightened by the 'Present Imperatives and Future Outlook' section.
As in the first edition, there is minimal philosophical lecturing, and zero religion. Instead, we get generous helpings of real-world case studies - aptly applied to progressively more advanced series of design concepts.
This style absolutely works for me. And I suspect that engineering mindsets typical of the folks that build these things will likely agree. In short, the Data Warehouse Toolkit Second Edition will significantly lighten the load of books that I carry between data warehouse engagements.
Jim Stagnitto
Llumino, Inc.
www.llumino.com

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The latest edition of the single most authoritative guide on dimensional modeling for data warehousing!
Dimensional modeling has become the most widely accepted approach for data warehouse design. Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated.
The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including:
* Retail sales and e-commerce
* Inventory management
* Procurement
* Order management
* Customer relationship management (CRM)
* Human resources management
* Accounting
* Financial services
* Telecommunications and utilities
* Education
* Transportation
* Health care and insurance
By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.
This book is also available as part of the Kimball's Data Warehouse Toolkit Classics Box Set (ISBN: 9780470479575) with the following 3 books:

The Data Warehouse Toolkit, 2nd Edition (9780471200246)
The Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775)
The Data Warehouse ETL Toolkit (9780764567575)

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Workflow Modeling: Tools for Process Improvement and Application Development, 2nd Edition Review

Workflow Modeling: Tools for Process Improvement and Application Development, 2nd Edition
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Rarely do I get excited about books on workflow modeling. I have a few good books on the subject, all of which provide solid approaches and most of which are well written. This book stands out because it goes beyond merely "solid" or "well written" by giving one of the most comprehensive approaches to workflow modeling I've had the pleasure of reading.
First, like most books on the topic, none of the components of the approach are new. What makes the approach refreshing is the way the authors take standard techniques and tie them together into a coherent process. Second, this book can be used as a workbook during a workflow modeling project, and is well suited to this because of the numerous checklists and diagrams that will prove invaluable every step of the way. Finally, this is the first book of its kind that incorporates use cases, making it invaluable to project teams that have standardized on UML (Unified Modeling Language)or wish to integrate an object-oriented approach into a workflow modeling project. If you're not familiar with use cases I strongly recommend Writing Effective Use Cases by Alistar Cockburn (the best book on the subject in my opinion); UML Distilled by Fowler and Scott is an excellent introduction to that subject if it's new to you.
The approach is straightforward: frame the process and define its scope, understand the existing process (if there is one), design the "to-be" process and develop use case scenarios. I wish to offer one caveat at this point: if you are reengineering a process that is seriously broken you might consider skipping the "as-is" process. Understanding the existing process is useful if your goal is incremental improvement. Reengineering efforts usually radically transform existing processes, making efforts to understand them both moot and wasted.
Some of the highlights of this book include the authors' clear definitions and way of decomposing complex systems into discrete steps and components. For example, they use a five tier view of processes that ensures you have a complete view of all issues and factors. The views are: (1) mission, strategy and goals (I personally extend goals further into Goal-Question-Metric), (2)business processes, (3) presentation, (4) application logic and (5) data. Note that the last three align nicely to a 3-tier client/server architecture. This observation clearly shows how coherent the authors' approach is and how it can foster alignment of technology to business requirements.
I also like how the authors clarify the key issues in process design by pointing out six enablers that you need to account for during the analysis and design phase: (1)workflow, (2) technology, (3) human resources, (4) motivations and measurements, (5) policies and rules and (6) environmental constraints (facilities, external process capabilities, etc.). There is one minor point of disagreement I have between their workflow modeling technique and the one I use. The authors use swimlane diagrams (also called Rummler-Brache diagrams), while I use deployment diagrams. The difference? Swimlane diagrams do not capture phases or cycles. I always place workflows into the context of Entry Criteria-Task-Validation-Exit Criteria (ETVX), which is nearly identical to the TQM Plan-Do-Check-Act (PDCA) cycle. I insist on ETVX because it allows me to spot missing validation points in an existing workflow, and ensures that I clearly define entry and exit criteria, as well as validation points in a "to-be" workflow. Of course I am stating personal preferences - following the authors' approach verbatim will definitely result in a workflow design that is not only "bulletproof", but will align information systems and business process almost perfectly.
This book is a gem. It's readable, full of ideas and, with the incorporation of use cases into the approach, completely up-to-date with respect to IS/IT methodologies. If you want a fresh, modern approach to workflow design this book is the only one that will provide it.

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At last - here's the long-awaited, extensively revised and expanded edition of the acclaimed and bestselling book, "Workflow Modeling". This thoroughly updated resource provides proven techniques for identifying, modeling, and redesigning business processes, and explaining how to implement workflow improvement, this book helps professionals define requirements for systems development or systems acquisition. By showing how to build visual models for illustrating workflow, the book helps practitioners assess their current business processes and see where process improvement and systems development can take place. Leading author Alec Sharp is an internationally recognized expert in business process management and is in high demand as a speaker and seminar leader in the field.

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7/29/2011

Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Management Science (with Printed Access Card) Review

Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Management Science (with Printed Access Card)
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Since Lotus 1-2-3 burst onto the scene almost thirty years ago, spreadsheet software has been a vital tool in aiding business decision-making. There are many books offering instruction in learning to use a spreadsheet. Some books promise to teach business processes but end up delivering a course on basic spreadsheeting with only a passing nod to the business processes the student was expecting to learn.
This fine book actually delivers the goods. First and foremost, it is a solid text on decision analysis in business management. It teaches the student on how to model optimization problems and solve them using linear programming. It covers sensitivity analysis and the simplex method, network modeling, integer linear programming, goal programming and multiple objective optimization, non-linear programming and evolutionary optimization, regression analysis, discriminant analysis, time series forecasting, introduces simulation, queuing theory, project management, and concludes with a chapter devoted to decision analysis. This final chapter covers both probabilistic and non-probabilistic methods, the expected value of imperfect information, decision trees, analyzing risk in a decision tree, computing conditional probabilities, and finally, utility theory.
What is wonderfully useful about this book is that it teaches these important principles of business decision making by turning them into practical tools using Excel spreadsheets. It not only shows the reader (student) how to build the spreadsheet, it also does the important task of teaching the WHY of the tool, not just the how.
It is clearly written, is laid out logically, and comes across as supportive of the student trying to learn this material.
Included in this book are 2 CDs. Included are: an advanced Solver, a 140 day trial of the Crystal Ball software, which will limit your use of it to the term you first study the material, but won't be of use to you unless you buy the software. The same goes for the 120-day trial of Microsoft Project. It is great to be introduced to these tools, but once you have invested time learning them, you will need to make other investments to keep using them. This is OK with me; I just think you ought to know that up front.
I think this is a fine text and could be the foundation of a very useful course.

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SPREADSHEET MODELING AND DECISION ANALYSIS, Sixth Edition, provides instruction in the most commonly used management science techniques and shows how these tools can be implemented using Microsoft Office Excel 2010.

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The Model Posing Guide For Fashion And Glamour Photography Review

The Model Posing Guide For Fashion And Glamour Photography
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A quick read for the photographer and model alike. The book hits all the points on preparing for a shoot from the Models perspective. As a photographer, I'm keeping a few on hand to give to newer models - as a way to help them get started. The book has groups and series of poses that the model can practice ahead of the shoot. (It always makes a shoot go smoother when a model can cycle through poses and you only have to help them make fine adjustments.) This book is a great reference for photographers, because you can visually breeze through similar poses to find one that fits what you are looking to capture. All in all, I'm glad someone finally came out with a book just like this! Kudos to the author!

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A posing guide for models interested in the Fashion and Glamour Photography Industry. Designed for Fashion and Glamour Models, it is about the rules for posing with sample poses and other tips, hints, and bits of information for models. A must have for Photographers too!

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Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling Review

Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling
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Snijders and Bosker's Multilevel Analysis is mathematically demanding but more readable than Raudenbush and Bryk's Hierarchical Linear Models. Snijders and Bosker's text would be much more useful for the less-experienced reader if it contained a directory identifying essential material. As is often the case with books of this kind, it is difficult to distinguish between really important topics, those crucial to understanding multilevel models, and ancillary topics which can be treated as non-essential, at least for the first pass through this dense and difficult material.
It would also help if the authors located multilevel modeling within a statistical context likely to contain material that readers already understand. As it is, multilevel analysis is treated as a separate and new topic, and is readily accessible only to those with generalized mathematical maturity.
The authors do, however, cover a broad range of pertinent material. Thus, while it is not a good choice for beginners looking for a self-instructional tool, the statistically sophisticated reader will find it to be an excellent reference. While just as difficult to understand as the rest of the book, Snijders and Bosker's develop some really informative and interesting examples of three-level models.
This text has been in print for a decade, and is still widely used. I've found that as I become more familiar with multilevel modeling, the book becomes more valuable.

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The Second Edition of this classic text introduces the main methods, techniques, and issues involved in carrying out multilevel modeling and analysis. Snijders and Boskers' book is an applied, authoritative, and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book has been comprehensively revised and updated since the last edition, and now includes guides to modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and Mix.

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7/28/2011

Management Science: The Art of Modeling with Spreadsheets Review

Management Science: The Art of Modeling with Spreadsheets
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This book takes time to adjust to the crowded typesetting first. Then it gets more interesting as you read more of it. The authors know the subject in depth as well as breath. One problem I have with my students is that many of them do not have the quantitative background required of the book, but the level of the book is what we should aim for in the future. We have to raise the level of our education. The book is well written except for some expected typos for a new edition.

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Now in its third edition, Management Science helps business professionals gain the essential skills needed to develop real expertise in business modeling. The biggest change in the text is the conversion of software from Crystal Ball to Risk Solver to reflect changes in the field. More coverage of management science topics has been added. Broader coverage of Excel demonstrates how to create models. Additional open-ended case studies that are less structured have also been included along with new exercises. These changes will help business professionals learn how to apply the information in the field.

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Microsoft® Office Excel® 2007: Data Analysis and Business Modeling (Bpg -- Other) Review

Microsoft® Office Excel® 2007: Data Analysis and Business Modeling (Bpg -- Other)
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Microsoft® Office Excel® 2007: Data Analysis and Business Modeling (Bpg -- Other)
This book should be on the desk of anyone analyzing data. It IS NOT for someone who doesn't know Excel 2007 and the basics of analyzing or working with data.
However, I've gone through Chapter 39 and have found this book is filled with all kinds of errors. I couldn't find any place on the internet that addresses these errors. Files missing or wrong (ie. Chapter 9 solution file problem numbers are incorrect), examples not matching my Office, Home, Student 2007 version (ie. pg. 43 references a DATEIF function that doesn't exist), plus many more.
The author or Microsoft needs to do a better job of proofreading or at least have a website where readers can post the errors they find so everybody using this book doesn't spend their time refinding the same errors.

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Master the analysis and business modeling techniques that help you transform your data into bottom-line results. Award-winning business professor and corporate consultant Wayne Winston shares the best of his real-world experience in this practical guide—now updated for Excel 2007. Use Wayne's proven practices and hands-on exercises to help you work smarter, make better decisions, and gain the competitive edge.

Solve real-world business problems with Excel 2007!

Maximize profits—determine NPV, optimize your product mix, calculate ROI
Create best, worst, and most-likely case scenarios for sales
Analyze investment performance and help minimize risk
Track your personal finances, calculate loan terms, and plan for retirement
Use trend and seasonality to forecast revenue
Estimate a product's demand curve and manage inventory with precision Interpret the effects of price and advertising on sales
Assign a dollar value to customer loyalty
Solve work scheduling problems and shorten wait times for customer service queues
PLUS—predict outcomes of sporting events, presidential elections, and more!

CD Includes:

Sample files from each chapter
Problem-and-solution sets—build your expertise!
Fully searchable eBook

A Note Regarding the CD or DVD

The print version of this book ships with a CD or DVD. For those customers purchasing one of the digital formats in which this book is available, we are pleased to offer the CD/DVD content as a free download via OReilly Medias Digital Distribution services. To download this content, please visit OReillys web site, search for the title of this book to find its catalog page, and click on the link below the cover image (Examples, Companion Content, or Practice Files). Note that while we provide as much of the media content as we are able via free download, we are sometimes limited by licensing restrictions. Please direct any questions or concerns to booktech@oreilly.com.


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Stats: Modeling the World (3rd Edition) Review

Stats: Modeling the World (3rd Edition)
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I have taught AP Stats for several years suffering through with a book I really hated. I felt that perhaps it was the subject though I continued to think Stats was really an awesome course. Now that I have my hands on this book, I have read every word on every page (the humor is most appreciated), truly reviewing the book to determine if I wanted to adopt it for my school. Not only am I planning on using it for my AP Stats class, I am going to use it in my regular class as well. It just makes such sense--and when it doesn't (because Stats is notoriously vague on some concepts--like why we divide by n-1 for s) the authors admit that though many have offered explanations, the reason is more likely just to drive you crazy. I've honestly never actually read a text and enjoyed it so thoroughly--now my husband REALLY thinks I'm a math nerd. I love, love, love this book. If it had a facebook page, I'd be a fan.

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KEY BENEFIT: By leading with practical data analysis and graphics, Stats: Modeling the World, Third Edition, engages students and gets them to do statistics and think statistically from the start. With the authors' signature Think, Show, Tell problem-solving method, students learn what we can find in data, why we find it interesting and how to report it to others. Instructors praise this text as clear and accessible, while students report that they actually enjoy reading the book while learning how to do statistics. Additional examples with updated data make this new edition even easier to read and use.

EXPLORING AND UNDERSTANDING DATA; Stats Start Here; Data; Displaying and Describing Categorical Data; Displaying and Comparing Qualitative Data; Understanding and Comparing Distributions; The Standard Deviation as a Ruler and the Normal Model; EXPLORING RELATIONSHIPS BETWEEN VARIABLES; Scatterplots, Association, and Correlation; Linear Regression; Regression Wisdom; Re-expressing Data: Get it Straight!; GATHERING DATA; Understanding Randomness; Sample Surveys; Experiments and Observational Studies; RANDOMNESS AND PROBABILITY; From Randomness to Probability; Probability Rules!; Random Variables; Probability Models; FROM THE DATA AT HAND TO THE WORLD AT LARGE; Sampling Distribution Models; Confidence Intervals for Proportions; Testing Hypotheses About Proportions; More About Tests and Intervals; Comparing Two Proportions; LEARNING ABOUT THE WORLD; Inferences about Means; Comparing Means; Paired Samples and Blocks; INFERENCE WHEN VARIABLES ARE RELATED; Comparing Counts; Inferences for Regression; Analysis of Variance (on DVD); Multiple Regression (on DVD)

For all readers interested in introductory statistics.

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7/27/2011

Principles and Practice of Structural Equation Modeling, Third Edition (Methodology In The Social Sciences) Review

Principles and Practice of Structural Equation Modeling, Third Edition (Methodology In The Social Sciences)
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We use this book in my the SEM class in my doctoral program and my professor has used it for years. Great book, easy to follow and understand!

Click Here to see more reviews about: Principles and Practice of Structural Equation Modeling, Third Edition (Methodology In The Social Sciences)



This bestselling text provides a balance between the technical and practical aspects of structural equation modeling (SEM). Using clear and accessible language, Rex B. Kline covers core techniques, potential pitfalls, and applications across the behavioral and social sciences. Some more advanced topics are also covered, including estimation of interactive effects of latent variables and multilevel SEM. The companion Web page offers downloadable syntax, data, and output files for each detailed example for EQS, LISREL, and Mplus, allowing readers to view the results of the same analysis generated by three different computer tools.

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The Art of Modeling Dynamic Systems: Forecasting for Chaos, Randomness and Determinism (Dover Books on Mathematics) Review

The Art of Modeling Dynamic Systems: Forecasting for Chaos, Randomness and Determinism (Dover Books on Mathematics)
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I find myself agreeing with all the comments made so far.
It's not too common to find a book that is able to describe in simple terms, such a large and diverse range of mathematical tools.
The author uses a framework - to tie together tools used in describing and handling deterministic, semi deterministic, and stochastic systems. For an example of Deterministic, try ODE's (ordinary differential equations), for semi deterministic - try Periodic but noisy wave-forms (some stock prices), and finally Stochastic - Random looking waveforms that have underlying patterns that can be described using either using Chaotic indicators (Hurst, Liapunov ) or probability type descriptors.
This book is the kind of thing you needed to help steer you through those dry mathematical books that are divorced from reality - A sort of classification system for deciphering what kind of gunpowder was used in those display's of intellectual fireworks from the tops of ivory towers. Kinda "So thats what all that maths means, but in plain english".
A depth of understanding, for practical application, without intellectual egotism and opaqueness. (But then maybe I'm just a bit thick ... :)
I'd tend to call this book as an equivalent to the Rosetta Stone for the maths of dynamical systems.
You may not use it directly - but you will benefit and grow in understanding from its' plain and simple sign posts along your journey.
It has its place on my book shelf.

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This text demonstrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. Written by a well-known authority in the field, it employs practical examples and analogies, rather than theorems and proofs, to characterize the benefits and limitations of modeling tools. 1991 edition.

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Professional Model Portfolios: A Step-by-Step Guide for Photographers Review

Professional Model Portfolios: A Step-by-Step Guide for Photographers
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This is not a bad book and I'm not going to trash it. It is, however, like many of the Amherst Media books, a little disappointing for anyone pretty far along in the business. I would consider it a complete beginner's guide to modeling and model photography. In that light, it's a useful and interesting book. I found the photos to be less than stellar and a bit dated, but this is totally subjective. (You can see a lot better by browsing the showcased photos on OneModelPlace.com.)The entire book left me wishing for more. With all this stated, I did learn some things from this book, which probably compensated for the cover price. In short, don't expect miracles from this book.

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This photographer's guide to creating successful model portfolios encourages a dynamic, diversified artistic approach and shares essential knowledge about the modeling industry, portfolio basics, and agency requirements. Photographers learn how to work with models for the best possible results, create and refine a standout portfolio, and sell that product to agents in the United States, England, and Asia. Three actual portfolios are included to help photographers conceptualize, sculpt, and refine their own portfolios to maximize their client's reach in the industry. Photographers learn why particular images were chosen for opening and closing shots, how to arrange the interior images, and what constitutes an appealing design. Featuring information on working with women, men, and children, this book will help new and experienced models and photographers alike in getting the results they desire.

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7/26/2011

Polygonal Modeling: Basic and Advanced Techniques (Worldwide Game and Graphics Library) (Wordware Game and Graphics Library) Review

Polygonal Modeling: Basic and Advanced Techniques (Worldwide Game and Graphics Library) (Wordware Game and Graphics Library)
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I was looking to learn Maya after years of using 3ds max, and this book's Maya Quick Start chapter got me right to the poly modeling tools and workflow without any detours. The tutorials have lots and lots of pictures--any semi-experienced modeler could work from the pictures alone. There is also a short, well-worded, to-the-point chapter on modeling for games, with the best explanation I've ever seen of poly arrangements and their importance. It's great to see a book with so little fluff and so much substance.

Click Here to see more reviews about: Polygonal Modeling: Basic and Advanced Techniques (Worldwide Game and Graphics Library) (Wordware Game and Graphics Library)

Polygonal modeling is the process of creating objects in a 3D environment. It is the foundation for the creation of all 3D graphics and the essential building block of a career in computer graphics. Polygonal Modeling: Basic and Advanced Techniques provides in-depth coverage of polygonal modeling, including practical lessons on topology construction, a focus on the fundamentals of subdivision workflow, and a discussion of the technical aspects of modeling organic and inorganic objects. The book includes illustrated quick start modeling guides to 3ds max and Maya.Explore and evaluate a variety of subdivision techniques. Learn about polygonal objects and their most common properties. Discover how to use the tools and operations found in major 3D packages for polygonal modeling. Follow along with the step-by-step illustrated exercises that demonstrate the process of character modeling.

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Financial Modeling Review

Financial Modeling
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Simon Benninga's 3rd Edition of Financial Modelling with Excel is the single most useful book for finance students and professionals ever published and continues to offer an outstanding reference and textbook for students and practitioners of applied finance.
For further information, please use the "Look Inside" feature and examine the Table of Contents carefully, because I will emphasize selected portions.
It is difficult to overstate how useful and practical and helpful this work is for a wide audience and Financial Modelling is the single finance book I recommend for everyone after they have taken (or read themselves) Introductory Finance.
For those looking for "one-stop-shopping" for models that resemble those of professional financial analysts then there is no better value than Benninga's FM3.
Benninga's FM3 is a coal-face work for those who must make financial decisions using models. There are further specialist texts in topics covered here (credit modelling, portfolio construction, option pricing), but the models in FM3 are the first advanced models applied to loans, bonds, options, and equity portfolios. Master these and then specialized texts are easier to digest.
"Cookbook" metaphors are too strong and do not do this work justice, for Financial Modelling 3rd (FM3) is not a mere collection of recipes but rather topical introduction, explanation, and then direct technique.
If we can make a comparison with a "cookbook" then FM3 falls somewhere between "The Joy of Cooking" and "Mastering the Art of French Cooking." "Joy" combines chapters on technique, ingredients, and tools with dense pages of endless recipes, whereas "Mastering" emphasises technique and a few well-selected recipes.
The welcome new chapters cover bank valuation, the Black-Litterman approach to portfolio optimization, and Monte Carlo methods and applications to option pricing, and the previous 2nd edition's small chapter on using array functions and formulas has been expanded. The chapter on data downloads from YAHOO is also welcome, especially for those on a budget.
There is a single significant flaw in the work, which is excusable and redeemable. Far too often the discounting in the chapters is done over a flat interest rate curve. While the term structure of interest rates is covered, and historical term structures and parallel shifts and steepening and flattening is covered in isolation in a thorough chapter and with wonderful data files, the necessity and explicit connection of discounting from an appropriate yield curve is left implied and only mentioned in a few exercises. I would have preferred a "round up" chapter where each of the subjects treated (bond discounting, portfolio expected returns, options, etc.) under a yield curve with advanced models. Sure BLOOMBERG and REUTERS have these sort of things (often incorrectly) programmed, but students need to learn explicitly about them and do the exercise themselves to comprehend the importance of curve discounting.
The CD attached in the back of the book is alone worth the price, with over two score of models that are practical and adaptable for students and professionals alike. The files are stored and separated according to chapters and subject matter. Each file has logical progression of the concepts advanced in the book, and each separate sheet either stands alone or appropriately links to data and models on other sheets, so editing for your own purposes is a breeze.
For those who want to train themselves in Finance (not "personal finance") then I suggest reading Copeland, Weston, & Shastri's Financial Theory and Corporate Policy (4th Edition) and Brealey, Myers, and Marcus's "Corporate Finance" and "Investments" followed by working through FM3. Such a course would give any self-disciplined person the equivalent of a Masters of Science in Finance.
Full disclosure: I am thanked in the "Acknowledgements" for providing a few helpful comments on the second edition.

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"The new edition of Simon Begginga's Financial Modeling is acomprehensive and effective learning-by-doing tool in motivating users and makingeasily accessible the concepts of modern corporate finance, investments, andderivatives. In the real world of finance, its clear step-by-step approach empowersthe practitioner to search the internet for financial data, build programs toanalyze them, and make sound financial decisions. I strongly recommend it to thefinance student and practitioner alike."--George Constantinides, Leo MelamedProfessor of Finance, The University of Chicago Graduate School ofBusiness (George M. Constantinides )

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