Fetch Your Copy Graphical Methods For Data Analysis Brought To You By John M. Chambers Conveyed In Pamphlet

full review:
Classic book on information visualization, Main strength: discusses many types of graphs developed for exploring the statistical properties of datasets encountered by the Bell Labs team in thes ands, Many of these types are no longer in use, but the design ideas behind them are still worth understanding,
Covers basic graph types and their statistical meaning, plus pitfalls in interpretation,
Some of the graph types now extinct: Q, xy graphs Section.,D scatterplots Section., notched box plots Section., sunflower plots a form of pixelation, Section,, and profile symbol plots and KleinerHartigan trees Section,. Some of the unfortunately not yet extinct: star symbol plots now known as spider charts or Kiviat diagrams, Section,.
Chaptercovers general principles and ideas about generating meaningful plots about quantitative data, Among the principles: iteration no data visualized in just one plot or even in just one go, interpretability relatively easy when data has meaning directly related to physical reality, but especially important for derived and combined plots that represent subtle effects that are more difficult to relate to immediately identifiable reality, flexibility of proposed graphing techniques, to accommodate a variety of situations, and true message avoiding to delude ourselves, and avoid to delude others guess the Soviet Russian Stats Office employees have not read this book, back in the days.

This book present graphical methods for analysing data, Some methods are new and some are old, some require a computer and others only paper and pencil but they are all powerful data analysis tools, In many situations, a set of

data even a large set can be adequately analysed through graphical methods alone, In most other situations, a few wellchosen graphical displays can significantly enhance numerical statistical analyses, .