{"id":93,"date":"2021-01-25T00:58:01","date_gmt":"2021-01-25T00:58:01","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/suny-hccc-generalscience\/?post_type=chapter&p=93"},"modified":"2021-01-25T00:58:01","modified_gmt":"2021-01-25T00:58:01","slug":"8-data-using-graphs-and-visual-data","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/suny-hccc-generalscience\/chapter\/8-data-using-graphs-and-visual-data\/","title":{"raw":"8. Data: Using Graphs and Visual Data","rendered":"8. Data: Using Graphs and Visual Data"},"content":{"raw":"
\r\n\r\nFlip through any scientific journal or textbook and you'll notice quickly that the text is interspersed with graphs and figures. In some journals, as much as 30% of the space is taken up by graphs (Cleveland, 1984), perhaps surpassing the adage that \"a picture is worth a thousand words.\" Although many magazines and newspapers also include graphs, the visual depiction of data<\/a> is fundamental to science and represents something very different from the photographs and illustrations published in magazines and newspapers. Although numerical data are initially compiled in tables or databases, they are often displayed in a graphic form to help scientists visualize and interpret the variation, patterns, and trends within the data.\r\n\r\nData lie at the heart of any scientific endeavor. Scientists in different fields collect data<\/a> in many different forms, from the magnitude<\/a> and location of earthquakes<\/a>, to the length of finch beaks, to the concentration<\/a> of carbon dioxide in the atmosphere<\/a> and so on. Visual representations of scientific data have been used for centuries \u2013 in the 1500s, for example, Copernicus drew schematic sketches of planetary orbits around the sun \u2013 but the visual presentation of numerical data in the form of graphs is a more recent development.\r\n\r\n<\/div>\r\n
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Using graphs to present numerical data<\/h2>\r\nIn 1786, William Playfair, a Scottish economist, published The Commercial and Political Atlas<\/em>, which contained a variety of economic statistics<\/a> presented in graphs. Among these was the image shown in Figure 1, a graph comparing exports from England with imports into England from Denmark and Norway from 1708 to 1780 (Playfair, 1786). (Incidentally, William Playfair was the brother of John Playfair, the geologist who elucidated James Hutton<\/a>'s fundamental work on geological processes to the broader public. To learn more, see our module The Rock Cycle: Uniformitarianism and Recycling<\/a>.)\r\n
\"William <\/a>
Figure 1: William Playfair's graph was one of the first examples of the visual representation of numerical data.<\/figcaption><\/figure>\r\nPlayfair's graph displayed a powerful message very succinctly. The graph shows time on the horizontal (x) axis and money in English pounds on the vertical (y) axis. The yellow line shows the monetary value<\/a> of imports to England from Denmark and Norway; the red line shows the monetary value of exports to Denmark and Norway from England. Although a table of numerical data<\/a> would show the same information, it would not be immediately apparent that something important happened in about 1753: England began exporting more than it imported, placing the \"balance in favour of England.\" This simple visualization of a large numerical dataset<\/a> made it easy to comprehend quickly.\r\n\r\nGraphs and figures quickly became standard components of science and scientific communication, and the use of graphs has increased dramatically in scientific journals in recent years, almost doubling from an average<\/a> of 35 graphs per journal issue to more than 60 between 1985 and 1994 (Zacks et al., 2002). This increase has been attributed to a number of causes, including the use of computer software programs that make producing graphs easy, as well as the production of increasingly large and complex datasets<\/a> that require visualization to be interpreted.\r\n\r\nGraphs are not the only form of visualized data<\/a>, however \u2013 maps, satellite imagery, animations, and more specialized images like atomic orbital depictions are also composed of data, and have also become more common. Creating, using, and reading visual forms of data is just one type of data analysis<\/a> and interpretation<\/a> (see our Data Analysis and Interpretation<\/a> module), but it is ubiquitous throughout all fields and methods<\/a> of scientific investigation.\r\n
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Comprehension Checkpoint<\/p>\r\n

Representing data graphically<\/p>\r\n\r\n

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