{"id":760,"date":"2015-11-19T17:25:09","date_gmt":"2015-11-19T22:25:09","guid":{"rendered":"http:\/\/arlduc.org\/senseandscale\/?p=760"},"modified":"2015-11-19T17:25:09","modified_gmt":"2015-11-19T22:25:09","slug":"follow-up-notes-on-r-tutorial","status":"publish","type":"post","link":"https:\/\/arlduc.org\/senseandscale\/?p=760","title":{"rendered":"Follow-up Notes on R Tutorial"},"content":{"rendered":"

From our R expert (R-xpert?) Kevin Miklasz. Thanks Kevin!<\/p>\n

Here is a link to an expanded sample file<\/a>\u00a0that shows some common functions I use, and is mostly focused on some graphing parameters I use a lot (at the bottom of the script). None of the graphing functions will work as they use data sets that I can’t share, but students can at least see some common graphing parameters that can be adjusted and reuse bits of the code in their own visualizations. Also including a list of preloaded R colors<\/a>, and this image<\/a> shows how the pch values in plots corresponds to different shapes.<\/div>\n
<\/div>\n
I might have\u00a0come down a little too hard on p values yesterday. They are still useful, and you should definitely test for p-values. But your process should look a bit like this:<\/div>\n
    \n
  1. Is there a significant p-value? If yes, go on<\/li>\n
  2. Do you have a large sample size? If no, you’re good with the p value! If yes, go on.<\/li>\n
  3. So the difference is significant, but is it meaningful? Is there an external measure for meaningfulness that you can use? Or can you shift to a data mining approach that can use cross-validation? It’s definitely ok to explore your data initially with correlation tests and t-tests, but before making a strong claim that there’s some real pattern in your data, you probably want to do some analysis beyond just finding a significant p value. P values should sort of be “necessary but not sufficient” kind of thing.<\/li>\n<\/ol>\n
    <\/div>\n","protected":false},"excerpt":{"rendered":"

    From our R expert (R-xpert?) Kevin Miklasz. Thanks Kevin! Here is a link to an expanded sample file\u00a0that shows some common functions I use, and is mostly focused on some graphing parameters I use a lot (at the bottom of the script). None of the graphing functions will work as they use data sets that […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,4,8],"tags":[],"class_list":["post-760","post","type-post","status-publish","format-standard","hentry","category-nyu-datavis","category-nyu","category-tutorials"],"_links":{"self":[{"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=\/wp\/v2\/posts\/760","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=760"}],"version-history":[{"count":1,"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=\/wp\/v2\/posts\/760\/revisions"}],"predecessor-version":[{"id":761,"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=\/wp\/v2\/posts\/760\/revisions\/761"}],"wp:attachment":[{"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=760"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=760"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/arlduc.org\/senseandscale\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=760"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}