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Bezig met laden... Now You See It: Simple Visualization Techniques for Quantitative Analysis (editie 2009)door Stephen Few (Auteur)
Informatie over het werkNow You See It: Simple Visualization Techniques for Quantitative Analysis door Stephen Few
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Meld je aan bij LibraryThing om erachter te komen of je dit boek goed zult vinden. Op dit moment geen Discussie gesprekken over dit boek. Comprehensive analysis of visualization techniques. From the simple: use the right viz to reveal patterns rather than show a grid and let the user work it out, to the more complex: multivariate analysis - how to understand the data when there are many different data points to consider. I found the writing style and examples very clear. I will refer back to it as I develop in future. Highly recommended to anyone trying to find insights or making that task easier for someone else. A very careful introduction to elementary information visualization techniques for quantitative analysis, focusing on line diagrams, bar graphs, scatterplots and the like. The author writes for an audience with practical and basic needs in analyzing quantitative data (mainly business data), referring frequently to things like how certain graphs are constructed in Excel. The relevance for an interaction designer may be limited, but the book should work well in introducing the basics and it also provides a few hints as to where interactive visualization techniques would offer the greatest leverage in data analysis. geen besprekingen | voeg een bespreking toe
This companion to Show Me the Numbers teaches the fundamental principles and practices of quantitative data analysis. Employing a methodology that is primarily learning by example and "thinking with our eyes," this manual features graphs and practical analytical techniques that can be applied to a broad range of data analysis tools--including the most commonly used Microsoft Excel. This approach is particularly valuable to those who need to make sense of quantitative business data by discerning meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities, and hints about the future. It provides practical skills that are useful to managers at all levels and to those interested in keeping a keen eye on their business. Geen bibliotheekbeschrijvingen gevonden. |
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Google Books — Bezig met laden... GenresDewey Decimale Classificatie (DDC)650Technology Management and auxiliary services BusinessLC-classificatieWaarderingGemiddelde:
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Professionally, I write software for biomedical applications that use a lot of scientific visualizations for large datasets. Although I took several nuggets of knowledge from this book (e.g., q-q plots), it was not really written for an audience like me. It’s more geared towards the wider business community, for whom data collection is a way to manage engineered systems. Rigorous biomedical scrutiny of data through careful statistics is simply not covered in this book. While for most, this tendency is surely welcomed, I honestly missed the exacting statistical theory. Still, I suspect most readers will find this book very approachable with achievable aims… even when using a common spreadsheet program.
Situated in Silicon Valley, Few clearly addresses an audience of those developing software with visualization technologies. Many times, he explicitly suggests features for new products. For software geeks like me, this trait is welcomed, but I understand that many business users, more interested in interpretation, might find it a bit off-putting. Nonetheless, I suggest it unwise to discard this whole book solely for that trait. This is the second book I’ve read by Few, and he consistently teaches me how to visualize and think about data in new ways – even as a scientist who is not deeply involved with business’s “bottom line.”
Like many books on data visualization, this work is elegantly put together with color plates communicating graphs as models. It’s simply a well-produced, pretty book. Business readers, especially decision-makers, can and should take advantage of Few’s expert wisdom. Learning a handful of pearls can easily lead to increased performance. Those involved in visualization software and the still young field of data science can likewise gain insights from Few. Again, the statistics are light, so wider audiences can access this work without intimidation. I enjoy wrestling with an active, expressive mind like Few’s and am grateful for my experiences with his writing. ( )