Visualizing Data Review

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(More customer reviews)This book was recommended highly to me by a former university professor (and now consultant). It exceeds my expectations. The figures and acompanying explanations are very clear, as is the language throughout. Visualizing Data discusses several tools with which I was not familiar, and clarifies tools that I thought I understood (including box plots). I have taken several university statistics classes, but I believe this book would help anyone involved in displaying or interpreting data. A picture may be worth a thousand words, but when your business depends on it, a well-defined plot or graph can be worth much more. Visualizing Data enables you to produce well-defined plots and graphs with confidence.

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Visualizing Data is about visualizationtools that provide deep insight into thestructure of data. There are graphicaltools such as coplots, multiway dot plots,and the equal count algorithm. There arefitting tools such as loess and bisquarethat fit equations, nonparametric curves,and nonparametric surfaces to data.But the book is much more than just acompendium of useful tools. It conveys astrategy for data analysis that stressesthe use of visualization to thoroughlystudy the structure of data and to checkthe validity of statistical models fittedto data. The result of the tools and thestrategy is a vast increase in what you canlearn from your data. The book demonstratesthis by reanalyzing many data sets from thescientific literature, revealing missedeffects and inappropriate models fitted to data.

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Interactive Data Visualization: Foundations, Techniques, and Applications Review

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(More customer reviews)Had to get this overpriced book for an Info Viz class. Be aware that this book is much more of a technical book than a design book. There's a ton of information contained in here, but I also found a surprising amount of quality issues.
First, the flow of the book seems completely off, diving into highly technical material in the second chapter, then pulling back into high level concepts in later chapters. Also, many of the images are not of the quality I would expect from a text book. Many are blurry or scaled inappropriately, given the amount of detail they contain. Finally, there are some glaring mistakes in the copy. For instance, at the end of one section of the book, placeholder notes from the authors of what should be written is included instead of the actual final copy! Where's the editor? Was it rushed to print?
Given the price, I expected a much higher level of quality. Despite the problems listed above, the text could be useful resource for anyone interested in the nuts and bolts of data visualization.

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This book provides the theory, practical details, and tools necessary for building visualizations or systems involving the visualization of data. The authors cover the spectrum of data visualizations, including mathematical and statistical graphs, cartography for displaying geographic information, two- and three-dimensional scientific displays, integrated analysis and visualization tools, and general information visualization techniques. Practitioners, developers, teachers and students as well as those interested in gaining some exposure to the field will get an in-depth understanding of visualization techniques and are provided with sufficient information, often with full source code, to complete an implementation; those with more modest aspirations can focus on the concepts, theory and high-level algorithm details.

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Applied Regression Modeling: A Business Approach Review

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(More customer reviews)There are so many great things about this book on applied regression that it is hard to know where to start. I'll mention six areas. First, the text teaches from the standpoint of someone learning rather than just presenting topics. The text goes carefully through examples that draw attention to what works and what does not work. Second, I like the chapter on extensions of regression. Third, I like the detailed steps of each hypothesis test along with the meaning of each step. Fourth, I like the thorough review of transformations of predictors and transformations of the dependent variable. Fifth, great treatment of categorical values. Sixth: good use of graphs to study whether the four assumptions of regression are met. Bottom line: if you study this book carefully and work through the examples, you will have a useful tool box to apply to a wide variety of business problems. If you are interested in this topic, I highly recommend this text. It's well worth the investment.

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An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression analysis to make informed decisions. Applied Regression Modeling: A Business Approach offers a practical, workable introduction to regression analysis for upper-level undergraduate business students, MBA students, and business managers, including auditors, financial analysts, retailers, economists, production managers, and professionals in manufacturing firms.The book's overall approach is strongly based on an abundant use of illustrations and graphics and uses major statistical software packages, including SPSS(r), Minitab(r), SAS(r), and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided, although Excel does not have a built-in capability to carry out all the techniques discussed.Applied Regression Modeling: A Business Approach offers special user features, including:* A companion Web site with all the datasets used in the book, classroom presentation slides for instructors, additional problems and ideas for organizing class time around the material in the book, and supplementary instructions for popular statistical software packages. An Instructor's Solutions Manual is also available.* A generous selection of problems-many requiring computer work-in each chapter with fullyworked-out solutions* Two real-life dataset applications used repeatedly in examples throughout the book to familiarize the reader with these applications and the techniques they illustrate* A chapter containing two extended case studies to show the direct applicability of the material* A chapter on modeling extensions illustrating more advanced regression techniques through the use of real-life examples and covering topics not normally seen in a textbook of this nature* More than 100 figures to aid understanding of the materialApplied Regression Modeling: A Business Approach fully prepares professionals and students to apply statistical methods in their decision-making, using primarily regression analysis and modeling. To help readers understand, analyze, and interpret business data and make informed decisions in uncertain settings, many of the examples and problems use real-life data with a business focus, such as production costs, sales figures, stock prices, economic indicators, and salaries. A calculus background is not required to understand and apply the methods in the book.

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