Early Reading Assessment: A Practitioner's Handbook Review

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(More customer reviews)I assess children's reading skills as part of my job. I was so impressed by this book, I showed it to my director who also ordered it. This is a comprehensive text that describes tools for reading assessments. I have expanded the tests I use based on Rathvon's recomendations and have found them to be "right on." I think my professional knowledge has been enhanced by this book.

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This indispensable resource offers a cutting-edge framework and practical tools for screening and assessing K-2 students at risk for reading problems. Provided are critical reviews of 42 specific measures, selected for optimal technical quality and presented in a clear, standardized format. Encapsulated are the scientific basis for each instrument; the components of reading acquisition measured; administration, scoring, and interpretation procedures; the instrument's psychometric soundness and usability; linkages to intervention; source; and cost. Detailed case examples drawn from the author's practice help the reader better understand the type of information generated by each measure and demonstrate how results can be written up in a variety of effective report formats.

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Expert Trading Systems: Modeling Financial Markets with Kernel Regression Review

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(More customer reviews)The book is actually quite good and Kernel Regression might very well be a good modelling technique. What destroys much of the credibility is that the author is actually the founder of a company that produces KR software. This fact isn't mentioned ANYWHERE in the book. The author just HAPPENS to use a specific software in all his examples. Guess what software? You have to go to the company website to find the connection.
If we set that aside, the book is well written and interesting. Not for the math impaired, though. University level math and statistics needed to be enjoyed in full.

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Expert Trading Systems "This book is an excellent introduction to advanced statistical modeling of financial markets. Wolberg’s explanation of kernel regression is lucid and direct. The author carefully leads readers through each stage of a trade system design and points out to them any potential difficulties they might encounter along the way. In addition, the examples give a concrete grasp of the subject without getting tangled up in any lengthy mathematical derivation." —Peter F. Borish, President, Computer Trading Corporation "The successful application of advanced modeling methods to the development of expert trading systems and financial market forecasting models requires both theoretical and practical knowledge. Wolberg was a pioneer in the development and application of kernel regression modeling to this area, and his book displays both deep theoretical understanding and practical knowledge in a highly readable how-to manner. Moreover, Wolberg’s advanced kernel regression algorithm is orders of magnitude faster than existing methods, thus broadening its application tremendously. I highly recommend this book to any practitioner in this area." —David Aronson, President, Raden Research Group Inc. "Kernel regression is a powerful statistical modeling technique that gives excellent performance in a wide variety of applications, including financial market prediction. Its use has traditionally been limited by its potentially overwhelming computational requirements, but Wolberg provides an effective algorithm that speeds computation by orders of magnitude, making it universally available." —Timothy Masters, author of Neural, Novel & Hybrid Algorithms for Time Series Prediction "This book presents an excellent overview of nonlinear modeling techniques used to build predictive models for financial time series. It is suitable both as a text for a financial modeling course or for a financial analyst who wants to use kernel methods for modeling. Wolberg describes his innovative approach to speeding up kernel regression, which allows these methods to be applied to a more complex set of problems. His software can be used to develop, test, and generate technical trading systems with more flexibility than other software that is commonly available." —Sandor Straus, PhD, Merfin, LLC, former partner of Renaissance Technology Corp.

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Regression Basics Review

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(More customer reviews)I bought this book as a supplement to my primary Econometrics text book last semester, and I'm glad it was just a supplement. Very brief and rather dry, this book lays out the basics of the discipline, but does it entirely too quickly for a beginner. For a more advanced Econometrics student it may be enough, and it will certainly be a useful resource to check back on as my studies progress; I just wish it had been more thorough for my current purposes.

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Using a friendly, nontechnical approach, the Second Edition of Regression Basics introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics.



New to the Second Edition



• Offers greater coverage of simple panel-data estimation: Because the availability of panel data has increased over the past decade, this new edition includes coverage of estimation with multiple cross-sections of data across time.

• Provides an introductory discussion of omitted variables bias: As a problem that frequently arises, this issue is important for those new to regression analysis to understand.

• Includes up-to-date advances: Chapter 7 is expanded to include recent developments in regression.

• Uses a diverse selection of examples: Engaging examples illustrate the wide application of regression analysis from baseball salaries to presidential voting to British crime rates to U.S. abortion rates and more.

• Includes more end-of-chapter problems: This edition offers new questions at the end of chapters that are based on the new examples woven through the book.

• Illustrates examples using software programs: Appendix B now includes screenshots to further aid readers working with Microsoft Excel® and SPSS.



Intended Audience

This is an ideal core or supplemental text for advanced undergraduate and graduate courses such as Regression and Correlation, Sociological Research Methods, Quantitative Research Methods, and Statistical Methods in the fields of economics, public policy, political science, sociology, public affairs, urban planning, education, and geography.

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Statistical Models in S Review

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(More customer reviews)S programmers refer to this as "the white book", and it is a key reference for understanding the methods implemented in several of S-PLUS' high-end statistical functions, including 'lm()', predict()', 'design()', 'aov()', 'glm()', 'gam()', 'loess()', 'tree()', 'burl.tree()', 'nls()' and 'ms()'.
It's apparently out of print, but it shouldn't be.
Even with the recent arrival of S-PLUS releases that incorporate S version 4 and many of the ideas discussed in "the green book" (, also by John Chambers), this classic S reference is an indispensable tool for the serious statistician. It needs to be reissued--with a white cover, of course.
Here are the titles of the chapters, for reference:
1. An Appetizer
2. Statistical Models
3. Data for Models
4. Linear Models
5. Analysis of Variance: Designed Experiments
6. Generalized Linear Models
7. Generalized Additive Models
8. Local Regression Models
9. Tree-Based Models
10. Nonlinear Models
A. Classes and Methods: Object-oriented Programming in S
B. S Functions and Classes
References
Index

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Statistical Models in S extends the S language to fit and analyze a variety of statistical models, including analysis of variance, generalized linearmodels, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the statistics research department at AT&T Bell Laboratories-represent results of research in both the computational and statistical aspects of modeling data.

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Relating Statistics and Experimental Design : An Introduction (Quantitative Applications in the Social Sciences) Review

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(More customer reviews)I bought this book with high expectations becasue of the very focused title. But the book turned out to be really disappointing. It is written like an academic article - theory and more theory. It is not an easy read, it does not engage the reader and it lacks good examples. Finally, the book is kept short at the expense of elaborate explanation of many a experimental design.
The book was so poorly written and clumsy that I returned it to Amazon with a couple of days. I do not recommend this book. There are many other good experiemental design books out there in the market. The one written by Jamec C. Goodwin is a much better alternative.
Bottom line - Pass this title and avoid the disappointment.

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This handy guide gives the novice researcher a clear description of the standard tools of the trade. Unlike some texts which focus on either design or statistics, this book covers the fundamentals of design, together with experiments and observational methods. There is an exposition of major tests of significance with formulas plus easy verbal interpretations, and "boxes" embedded in the text contain prototypic applications.

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Fundamentals of Marketing Research Review

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(More customer reviews)I was introduced to this book while taking a market research course during my MBA. As a product marketing manager at a software firm, I have found this text indispensible for our in-house research efforts.
While likely targeted toward those with some market research or statistics backgrounds, this book actually provides the information a capable beginner would need to take a market research project from the planning and research design stages, to appropriate techniques for collecting and measuring research data, and ultimately to data analysis and reporting on findings.
While daunting in page count, one should consider this their market research 'bible.' Plan on tossing your book shelf of market research texts and pick up this all in one resource.

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Fundamentals of Marketing Research covers all facets of marketing research including method, technique, and analysis at all levels. The methodological scope regarding research design, data collection techniques, and measurement is broad with three chapters devoted to the critical area of measurement and scaling.The presentation is from primarily a pragmatic and user-oriented perspective which aides the student to evaluate the research presented to them. This text explores cutting-edge technologies and new horizons while ensuring students have a thorough grasp of research fundamentals.

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Ergonomic Design for Organizational Effectiveness Review

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(More customer reviews)O'Neill's book does a wonderful job of providing examples on work teams and their issues of space and environmental control. Data and results from his research (case studies, field studies, and experiments) are very helpful. Sometimes the book is difficult to follow because of the way the chapters are organized.

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Creating alignment between the office environment, and the business objectives and mission of the organization, this new book provides a framework for the manager to develop strategies and tactics to leverage the work environment as a tool to enhance organizational effectiveness.Drawing from the author's own published research, consulting work, and previously unpublished case studies, each section addresses current research findings that build upon a new framework for thinking about work and the work environment.Ergonomic Design for Organizational Effectiveness grapples with problems such as:

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