{"id":802,"date":"2017-02-13T06:51:50","date_gmt":"2017-02-13T06:51:50","guid":{"rendered":"https:\/\/blogs.scu.edu\/dataviz\/?p=802"},"modified":"2017-02-13T06:51:50","modified_gmt":"2017-02-13T06:51:50","slug":"spot-visualization-lie-part-i","status":"publish","type":"post","link":"https:\/\/blogs.scu.edu\/dataviz\/2017\/02\/13\/spot-visualization-lie-part-i\/","title":{"rendered":"Spot Visualization Lie &#8211; Part I"},"content":{"rendered":"<p>Lying with statistics has been a thing for a long time, but charts tend to spread far and wide theses days. Some don&#8217;t tell the truth. So it&#8217;s all the more important now to quickly decide if a graph is telling the truth. This is a guide to help you spot the visualization lies.<\/p>\n<p><strong>Truncated Axis<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-medium\" src=\"http:\/\/i0.wp.com\/flowingdata.com\/wp-content\/uploads\/2017\/02\/Truncated-axis.png?resize=768%2C479\" alt=\"\" width=\"768\" height=\"479\" \/>Bar charts use length as visual cue, so when make the length shorter using the same data by truncating the value axis, the chart dramatizes differences. Someone wants to show a bigger change than data actually tells.<\/p>\n<p><strong>Dual Axes<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium\" src=\"http:\/\/i1.wp.com\/flowingdata.com\/wp-content\/uploads\/2017\/02\/Dual-axes.png?resize=768%2C410\" alt=\"\" width=\"768\" height=\"410\" \/><\/p>\n<p>By using dual axes, the magnitude can shrink or expand for each metric. This is typically done to imply two events which actually independent with each other are correlation and causation.<\/p>\n<p><strong>It Does Not Add Up<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium\" src=\"http:\/\/i1.wp.com\/flowingdata.com\/wp-content\/uploads\/2017\/02\/Add-up.png?resize=768%2C383\" alt=\"\" width=\"768\" height=\"383\" \/><\/p>\n<p>Some charts specifically show parts of a whole. When the parts add up to more than the whole, this could be a problem.<\/p>\n<p><strong>Seeing Only In Absolutes<\/strong><\/p>\n<p><strong><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium\" src=\"http:\/\/i0.wp.com\/flowingdata.com\/wp-content\/uploads\/2017\/02\/Absolutes.png?resize=768%2C567\" alt=\"\" width=\"768\" height=\"567\" \/><\/strong><\/p>\n<p>Everything is relative. You can&#8217;t say a town is more dangerous than another because the first town had two robberies and the other only had one. What is the first town has 1,000 times the population that of the first? It is often more useful to think in terms of percentages and rates of relative factor rather than absolutes and totals.<\/p>\n<p><strong>Limited Scope<\/strong><\/p>\n<p><strong><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium\" src=\"http:\/\/i2.wp.com\/flowingdata.com\/wp-content\/uploads\/2017\/02\/Limited-scope.png?resize=768%2C428\" alt=\"\" width=\"768\" height=\"428\" \/><\/strong><\/p>\n<p>It&#8217;s easy to scope dates and time frames to fit a specific narrative. So consider history and proper baselines to compare against.<\/p>\n<p>Due to words limited, to be continued next week&#8230;<\/p>\n<p><a href=\"http:\/\/flowingdata.com\/2017\/02\/09\/how-to-spot-visualization-lies\/\">http:\/\/flowingdata.com\/2017\/02\/09\/how-to-spot-visualization-lies\/<\/a><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Lying with statistics has been a thing for a long time, but charts tend to spread far and wide theses days. Some don&#8217;t tell the truth. So it&#8217;s all the more important now to quickly decide if a graph is telling the truth. This is a guide to help you spot the visualization lies. Truncated &hellip; <a href=\"https:\/\/blogs.scu.edu\/dataviz\/2017\/02\/13\/spot-visualization-lie-part-i\/\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Spot Visualization Lie &#8211; Part I<\/span><\/a><\/p>\n","protected":false},"author":1849,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"qubely_global_settings":"","qubely_interactions":"","kk_blocks_editor_width":"","_kiokenblocks_attr":"","_kiokenblocks_dimensions":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-802","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"gutentor_comment":0,"qubely_featured_image_url":null,"qubely_author":{"display_name":"dixu","author_link":"https:\/\/blogs.scu.edu\/dataviz\/author\/dixu\/"},"qubely_comment":0,"qubely_category":"<a href=\"https:\/\/blogs.scu.edu\/dataviz\/category\/uncategorized\/\" rel=\"category tag\">Uncategorized<\/a>","qubely_excerpt":"Lying with statistics has been a thing for a long time, but charts tend to spread far and wide theses days. Some don&#8217;t tell the truth. So it&#8217;s all the more important now to quickly decide if a graph is telling the truth. This is a guide to help you spot the visualization lies. 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