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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><div><div style='border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0in 0in 0in'><p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> extropy-chat [mailto:extropy-chat-bounces@lists.extropy.org] <b>On Behalf Of </b>Anders Sandberg<br><b>Sent:</b> Saturday, July 11, 2015 11:13 AM<br><b>To:</b> ExI chat list<br><b>Subject:</b> Re: [ExI] Why so much published 'science' is wrong.<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><strong>Från: </strong>BillK <<a href="mailto:pharos@gmail.com">pharos@gmail.com</a>> <o:p></o:p></p><div><blockquote style='border:none;border-left:solid blue 1.5pt;padding:0in 0in 0in 6.0pt;margin-left:4.8pt;margin-right:0in'><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Science is heroic, with a tragic (statistical) flaw<br>Mindless use of statistical testing erodes confidence in research<o:p></o:p></p></blockquote></div><p class=MsoNormal><br><span style='color:#1F497D'>>…</span>I am reading Alex Reinharts "Statistics done wrong: the woefully complete guide" ( <a href="http://www.statisticsdonewrong.com/">http://www.statisticsdonewrong.com/</a> ) and enjoying it. <span style='color:#1F497D'>…</span>But if science has it rough, at least it is rather numerically literate and knows it has a problem. After three years of talking to insurance I realize that a lot of important business is made on far dodgier assumptions.<span style='color:#1F497D'> </span>Anders Sandberg, <o:p></o:p></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'>Ja. I see this primarily as a failure in the way statistics courses are taught. The textbooks may contain good explanations for the various calculations, but if the instructor has ten weeks to cover the topic, the little bit of time is spent teaching the students how to calculate the parameters. OK then, exam time, the students grind away, calculate means, standard deviation, variance, do a chi square test, Kruskal Wallis, factoral ANOVA, identify a few distributions, they run all the tests and get the numbers, hooray they pass. But they don’t really understand what the numbers are saying. They know how to get the numbers, but one quarter or one semester just isn’t enough time to really help students understand what they calculated. <o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'>Before the course, the students looked at the data and took their best guess. After the course, they look at the data, calculate some numbers, draw the wrong conclusion, walk away 95% confident they are correct. Then they go get jobs.<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'>I can think of a better way. Instead of the usual approach, if the engineering students took two quarters of calculus (where you use Wolfram’s magic act rather than learn twenty different ways to integrate the kinds of functions you never seen to get in real life) and take three quarters of statistics, where the students use Wolfram again (rather than spending the time on how to calculate all those parameters) then spend their time figuring out how to interpret what the computer gave them.<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'>I did some searching and found this whole discussion on reducing calculus education veered off in the wrong direction by about a radian. A faction took off with the idea of calculus reduction, but presented a weird justification: women and minority students are less likely to pass the calculus series (sheesh) and of course you can’t go on in the sciences without it, so that means fewer women and minorities in the sciences, all because of calculus. My notion is the reason for calculus reduction would be to make room for more statistics study. Perhaps the minority argument derailed the notion of statistical education or sent it down the wrong road, damn.<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'>spike<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p></div></body></html>