By Olczak, Anatole Olczak
Paperback: forty two pages writer: Asp Inc; 1 variation (June 1995) Language: English ISBN-10: 093573922X ISBN-13: 978-0935739220 Product Dimensions: 8.3 x 5.2 x 0.3 inches transport Weight: 2.4 oz commonplace consumer overview: 4.8 out of five stars See all studies (4 purchaser reports) Amazon most sensible dealers Rank: #3,618,900 in Books (See best a hundred in Books)
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Extra resources for Bourne Shell quick reference guide
N Overlap plotting symbols only if they are visually distinguishable. n Superpose data sets only when they can be readily discriminated. n Preserve visual clarity under reduction and reproduction. In an earlier book, Graphical Methods for Data Analysis, (Chambers et al. 1983), Cleveland and his colleagues at AT&T Bell Laboratories present an excellent, nontechnical description of many of the methods of graphical data analysis covered here. Because they do not have the task of explaining how these methods are implemented in software, their treatment of the statistical ideas and interpretation of data can be more extensive than is possible here.
2 proposes that human visual information processing can be divided into the three stages shown. Each stage is governed by processes that place constraints on the design of graphical display. 2 can affect graphical perception and their implications for display design. The discussion below illustrates how the analysis of one of these processes, discrimination, can be applied to designing more effective graphs. Discrimination refers to our ability to resolve separate graphic symbols. To be clearly seen, plotting symbols and labels must be a certain minimal size, allowing for possible photo-reduction in printing.
15 as a bar chart in the left panel and as a connected line graph in the right panel. 15 Matching Graphic Form to the Question If you want to compare the response to TYPE A and B for particular levels and see which is greater or judge their ratio, this information is more readily extracted from the bar chart because the heights of adjacent bars are easier to compare than points on different curves. 6 Strategies for Graphical Data Analysis n Chapter 1 graph than in the bar chart. This is because the connected points on each curve in the line graph have simple descriptions (for example, "straight line" for TYPE B and "positively accelerated" for TYPE A) we can apprehend as one conceptual unit.
Bourne Shell quick reference guide by Olczak, Anatole Olczak