andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-2144 knowledge-graph by maker-knowledge-mining
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Introduction: Aki pointed me to this article . I’m too exhausted to argue all this in detail yet one more time, but let me just say that I hate this stuff for the reasons given in Section 5 of this paper from 1998 (based on classroom activities from 1994). I’ve hated this stuff for a long time. And I don’t think Yitzhak likes it either; see this discussion from 2005 and this from 2009.
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1 I’m too exhausted to argue all this in detail yet one more time, but let me just say that I hate this stuff for the reasons given in Section 5 of this paper from 1998 (based on classroom activities from 1994). [sent-2, score-2.415]
2 And I don’t think Yitzhak likes it either; see this discussion from 2005 and this from 2009. [sent-4, score-0.454]
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same-blog 1 1.0 2144 andrew gelman stats-2013-12-23-I hate this stuff
Introduction: Aki pointed me to this article . I’m too exhausted to argue all this in detail yet one more time, but let me just say that I hate this stuff for the reasons given in Section 5 of this paper from 1998 (based on classroom activities from 1994). I’ve hated this stuff for a long time. And I don’t think Yitzhak likes it either; see this discussion from 2005 and this from 2009.
2 0.27149546 6 andrew gelman stats-2010-04-27-Jelte Wicherts lays down the stats on IQ
Introduction: Good stuff.
3 0.20388752 436 andrew gelman stats-2010-11-29-Quality control problems at the New York Times
Introduction: I guess there’s a reason they put this stuff in the Opinion section and not in the Science section, huh? P.S. More here .
Introduction: Xian pointed me to this recycling of a classic probability error. It’s too bad it was in the New York Times, but at least it was in the Opinion Pages, so I guess that’s not so bad. And, on the plus side, several of the blog commenters got the point. What I was wondering, though, was who was this “Yitzhak Melechson, a statistics professor at the University of Tel Aviv”? This is such a standard problem, I’m surprised to find a statistics professor making this mistake. I was curious what his area of research is and where he was trained. I started by googling Yitzhak Melechson but all I could find was this news story, over and over and over and over again. Then I found Tel Aviv University and navigated to its statistics department but couldn’t find any Melechson in the faculty list. Next stop: entering Melechson in the search engine at the Tel Aviv University website. It came up blank. One last try: I entered the Yitzhak Melechson into Google Scholar. Here’s what came up:
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Introduction: (Click for bigger image.) The above is Aki’s decomposition of the birthdays data (the number of babies born each day in the United States, from 1968 through 1988) using a Gaussian process model, as described in more detail in our book .
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same-blog 1 0.96177113 2144 andrew gelman stats-2013-12-23-I hate this stuff
Introduction: Aki pointed me to this article . I’m too exhausted to argue all this in detail yet one more time, but let me just say that I hate this stuff for the reasons given in Section 5 of this paper from 1998 (based on classroom activities from 1994). I’ve hated this stuff for a long time. And I don’t think Yitzhak likes it either; see this discussion from 2005 and this from 2009.
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Introduction: Good stuff.
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Introduction: Good stuff , as always, from Laura Wattenberg.
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Introduction: I guess there’s a reason they put this stuff in the Opinion section and not in the Science section, huh? P.S. More here .
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Introduction: See here . Cool–it looks like they’re doing interesting stuff, and it’s great to see this sort of support for applied research.
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Introduction: Aki pointed me to this article . I’m too exhausted to argue all this in detail yet one more time, but let me just say that I hate this stuff for the reasons given in Section 5 of this paper from 1998 (based on classroom activities from 1994). I’ve hated this stuff for a long time. And I don’t think Yitzhak likes it either; see this discussion from 2005 and this from 2009.
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Introduction: Completely non-gay historian Niall Ferguson, a man who we can be sure would never be caught at a ballet or a poetry reading, informs us that the British decision to enter the first world war on the side of France and Belgium was “the biggest error in modern history.” Ummm, here are a few bigger errors: The German decision to invade Russia in 1941. The Japanese decision to attack America in 1941. Oh yeah , the German decision to invade Belgium in 1914. The Russian decision to invade Afghanistan in 1981 doesn’t look like such a great decision either. And it wasn’t so smart for Saddam Hussein to invade Kuwait, but maybe the countries involved were too small for this to count as “the biggest error in modern history.” It’s striking that, in considering the biggest error in modern history, Ferguson omits all these notorious acts of aggression (bombing Pearl Harbor, leading to the destruction of much of your country, that was pretty bad, huh?), and decides that the worst
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Introduction: Mark Palko asks what I think of this article by Francisco Louca, who writes about “‘hybridization’, a synthesis between Fisherian and Neyman-Pearsonian precepts, defined as a number of practical proceedings for statistical testing and inference that were developed notwithstanding the original authors, as an eventual convergence between what they considered to be radically irreconcilable.” To me, the statistical ideas in this paper are too old-fashioned. The issue is not that the Neyman-Pearson and Fisher approaches are “irreconcilable” but rather that neither does the job in the sort of hard problems that face statistical science today. I’m thinking of technically difficult models such as hierarchical Gaussian processes and also challenges that arise with small sample size and multiple testing. Neyman, Pearson, and Fisher all were brilliant, and they all developed statistical methods that remain useful today, but I think their foundations are out of date. Yes, we currently use m
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Introduction: Mark Palko asks : What are the worst examples of curriculum dead wood? Here’s the background: One of the first things that hit me [Palko] when I started teaching high school math was how much material there was to cover. . . . The most annoying part, though, was the number of topics that could easily have been cut, thus giving the students the time to master the important skills and concepts. The example that really stuck with me was synthetic division, a more concise but less intuitive way of performing polynomial long division. Both of these topics are pretty much useless in daily life but polynomial long division does, at least, give the student some insight into the relationship between polynomials and familiar base-ten numbers. Synthetic division has no such value; it’s just a faster but less interesting way of doing something you’ll never have to do. I started asking hardcore math people — mathematicians, statisticians, physicists, rocket scientists — if they.’d ever u
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