Posts Tagged ‘ Miscellaneous Statistics ’

What hypothesis testing is all about. (Hint: It’s not what you think.)

March 2, 2015
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What hypothesis testing is all about.  (Hint:  It’s not what you think.)

I’ve said it before but it’s worth saying again. The conventional view: Hyp testing is all about rejection. The idea is that if you reject the null hyp at the 5% level, you have a win, you have learned that a certain null model is false and science has progressed, either in the glamorous “scientific […] The post What hypothesis testing is all about. (Hint: It’s not what you think.)…

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“Precise Answers to the Wrong Questions”

March 1, 2015
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Our friend K? (not to be confused with X) seeks pre-feedback on this talk: Can we get a mathematical framework for applying statistics that better facilitates communication with non-statisticians as well as helps statisticians avoid getting “precise answers to the wrong questions*”? Applying statistics involves communicating with non-statisticians so that we grasp their applied problems […] The post “Precise Answers to the Wrong Questions” appeared first on Statistical Modeling, Causal…

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“The harm done by tests of significance” (article from 1994 in the journal, “Accident Analysis and Prevention”)

February 27, 2015
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Ezra Hauer writes: In your January 2013 Commentary (Epidemiology) you say that “…misunderstanding persists even in high-stakes settings.” Attached is an older paper illustrating some such. “It is like trying to sink a battleship by...

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“A small but growing collection of studies suggest X” . . . huh?

February 24, 2015
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Lee Beck writes: I’m curious if you have any thoughts on the statistical meaning of sentences like “a small but growing collection of studies suggest [X].” That exact wording comes from this piece in the New Yorker, but I think it’s the sort of expression you often see in science journalism (“small but mounting”, “small […] The post “A small but growing collection of studies suggest X” . . .…

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“Unbiasedness”: You keep using that word. I do not think it means what you think it means. [My talk tomorrow in the Princeton economics department]

February 23, 2015
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“Unbiasedness”:  You keep using that word. I do not think it means what you think it means. [My talk tomorrow in the Princeton economics department]

The talk is tomorrow, Tues 24 Feb, 2:40-4:00pm in 200 Fisher Hall: “Unbiasedness”: You keep using that word. I do not think it means what you think it means. Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University Minimizing bias is the traditional first goal of econometrics. In many cases, though, the […] The post “Unbiasedness”: You keep using that word. I do not think it means…

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Statistical Significance – Significant Problem?

February 20, 2015
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John Carlin, who’s collaborated on some of my recent work on Type S and Type M errors, prepared this presentation for a clinical audience. It might be of interest to some of you. The ideas and some of the examples should be familiar to regular readers of this blog, but it could be useful to […] The post Statistical Significance – Significant Problem? appeared first on Statistical Modeling, Causal Inference,…

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Another example of why centering predictors can be good idea

February 19, 2015
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Another example of why centering predictors can be good idea

Andrew Dolman writes: Just in case you need another example of why it is important to consider what the intercepts in a model represent, here is a short comment I [Dolman] just got published correcting a misinterpretation of a simple linear model, that would not have happened if they had centered their predictor around a […] The post Another example of why centering predictors can be good idea appeared first…

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Two Unrecognized Hall Of Fame Statisticians

February 14, 2015
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To follow up on a recent post, I thought it would be amusing to consider the most important unrecognized statisticians. That is, those statisticians of the past who made important contributions which have been largely forgotten. Any suggestions? Dead...

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“When Do Stories Work? Evidence and Illustration in the Social Sciences”: My talk in the Harvard sociology dept this Thurs noon

February 10, 2015
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Stories are central to social science. It might be pleasant to consider stories as mere adornments and explications of theories that we develop and evaluate via formal data collection, but it seems that all of us—including statisticians!—rely on stories to develop our understanding of the social world. And therein lies a paradox: stories are valued […] The post “When Do Stories Work? Evidence and Illustration in the Social Sciences”: My…

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Statistical analysis recapitulates the development of statistical methods

February 6, 2015
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Statistical analysis recapitulates the development of statistical methods

There’s a old saying in biology that the development of the organism recapitulates the development of the species: thus in utero each of us starts as a single-celled creature and then develops into an embryo that successively looks like a simple organism, then like a fish, an amphibian, etc., until we reach our human form […] The post Statistical analysis recapitulates the development of statistical methods appeared first on Statistical…

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