{"id":278,"date":"2010-02-18T20:43:21","date_gmt":"2010-02-18T18:43:21","guid":{"rendered":"http:\/\/www.theusrus.de\/blog\/?p=278"},"modified":"2010-02-18T21:56:10","modified_gmt":"2010-02-18T19:56:10","slug":"fundamentals-learning-to-cook","status":"publish","type":"post","link":"https:\/\/www.theusrus.de\/blog\/fundamentals-learning-to-cook\/","title":{"rendered":"Fundamentals: Learning to Cook"},"content":{"rendered":"<p>For those who are used to work with graphics on a regular basis, it is usually not a question, what plot (or combination of plots) to use when looking at particular data problems. Nevertheless, many statistically trained researcher and practitioners have a hard time to translate data problems into reasonable graphics (not to mention their correct interpretation). To help selecting the &#8220;right&#8221; graphics to start with, the following table might be of some help:<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter\" title=\"Cook\" src=\"http:\/\/www.theusRus.de\/Blog-files\/Cook.png\" alt=\"Cook\" width=\"532\" height=\"310\" \/><\/p>\n<p style=\"text-align: left;\">This is certainly only a default orientation &#8211; the &#8220;killer graphics&#8221; will usually take more effort to create. Maybe this &#8220;cookbook for graphics starters&#8221; should be read along the discussion of Andrew Gelman&#8217;s <a href=\"http:\/\/www.stat.columbia.edu\/~cook\/movabletype\/archives\/2010\/02\/exploratory_and.html\" target=\"_blank\">post<\/a>.<\/p>\n<p style=\"text-align: left;\">Those who use graphics effectively often are inclined to think they are doing something &#8220;low-status&#8221;, and think that the guys who come along with the next nifty model for datasets which have never been observed so far are doing &#8220;serious work&#8221;. That thinking definitely is wrong, and good and useful graphics are not at all easy for most statisticians!<\/p>\n<p style=\"text-align: left;\">PS: Combinations of graphics are of course most useful if linked highlighting can be used!<\/p>\n<p style=\"text-align: left;\">\n","protected":false},"excerpt":{"rendered":"<p>For those who are used to work with graphics on a regular basis, it is usually not a question, what plot (or combination of plots) to use when looking at particular data problems. Nevertheless, many statistically trained researcher and practitioners have a hard time to translate data problems into reasonable graphics (not to mention their [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,1],"tags":[],"class_list":["post-278","post","type-post","status-publish","format-standard","hentry","category-fundamentals-of-graphical-data-analysis","category-general"],"_links":{"self":[{"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/posts\/278","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/comments?post=278"}],"version-history":[{"count":18,"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/posts\/278\/revisions"}],"predecessor-version":[{"id":342,"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/posts\/278\/revisions\/342"}],"wp:attachment":[{"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/media?parent=278"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/categories?post=278"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.theusrus.de\/blog\/wp-json\/wp\/v2\/tags?post=278"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}