{"id":868,"date":"2015-01-05T09:00:14","date_gmt":"2015-01-05T15:00:14","guid":{"rendered":"http:\/\/blogs.ams.org\/blogonmathblogs\/?p=868"},"modified":"2015-01-05T16:04:54","modified_gmt":"2015-01-05T22:04:54","slug":"return-of-the-statistics-blogs","status":"publish","type":"post","link":"https:\/\/blogs.ams.org\/blogonmathblogs\/2015\/01\/05\/return-of-the-statistics-blogs\/","title":{"rendered":"Return of the Statistics Blogs"},"content":{"rendered":"

When I shared a few of my favorite statistics blogs<\/a> over a year ago, Thomas Lumley self-promoted his blogs in the comments<\/a>, and I\u2019m so glad he did! He is the ringleader and a contributor to the University of Auckland statistics department blog StatsChat<\/a>, and his personal blog, Biased and Inefficient<\/a>, has some not-quite-Stats-Chattable posts that can be a lot of fun<\/a>. Last time I wrote about statistics blogs, I found a great one to follow. Will lightning strike twice?<\/p>\n

\"Image:<\/a>

Image: xkcd.<\/p><\/div>\n

Lumley is particularly interested in the way the media reports medical statistics. Recently, he wrote about<\/a>\u00a0the cancer study that has been going around with headlines like \u201cMost Cancers May Simply Be Due to Bad Luck<\/a>.\u201d He also expands on some of the data in a supplemental post<\/a> on Biased and Inefficient. Overall, he is critical of the hype but says that the study itself was important.<\/p>\n

In contrast, some of the articles he discusses are quite silly:\u00a0using lipstick during pregnancy<\/a>, charging your cellphone in your bedroom<\/a> (if you are a rat and the cell phone is the absence of melatonin), and\u00a0eating chocolate to help your memory<\/a>. It’s a bit depressing to see the same errors over and over, but the critiques can be enlightening and funny.\u00a0I also appreciate his interesting comments <\/a>about data visualization<\/a>. Caution: last link includes objects\u00a0that look like 3-d pie charts (but aren’t) adorning a tree for no apparent reason. Click at your own risk.<\/p>\n

Another statistics blog I\u2019ve been reading lately is A Little Stats<\/a>, written by statistics teacher Amy Hogan. I particularly enjoyed her recent post<\/a> about a few of the words she thinks can be stumbling blocks to people who are trying to \u201ctranslate\u201d statistics back into their normal vocabulary. She highlighted percent, which was timely for me, having just been annoyed by someone using \u201cpercent\u201d for numbers smaller than 100<\/a>, a practice I find unhelpful and somewhat deceptive. Hogan doesn\u2019t mention that issue specifically, but I think her comments about some of the other potential pitfalls of percentages are helpful. In the wrong hands, percentages\u00a0can be very misleading.<\/p>\n

It never would have occurred to me to include age on a list of tricky statistics concepts. Age is pretty straightforward, right? Hogan writes, “If someone is 19 years old, for example, it can be confusing as to whether that means the person has finished their 19th year of life or is starting it. Sometimes people round ages, often if asked about the age of a relative. This is further complicated because in different languages how one says his\/her age varies. While I don’t think that the true definition of age varies too greatly, good surveys avoid this issue by asking people for their birth date.” It’s such an easy fix, but it’s one I wouldn’t have thought to do.<\/p>\n

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When I shared a few of my favorite statistics blogs over a year ago, Thomas Lumley self-promoted his blogs in the comments, and I\u2019m so glad he did! He is the ringleader and a contributor to the University of Auckland … Continue reading →<\/span><\/a><\/p>\n

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