andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-1015 knowledge-graph by maker-knowledge-mining
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Introduction: Rama Ganesan writes: I have been using many of your demos from the Teaching Stats book . . . Do you by any chance have a nice easy dataset that I can use to show students how ‘lurking variables’ work using regression? For instance, in your book you talk about the relationship between height and salaries – where gender is the hidden variable. Any suggestions?
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1 Rama Ganesan writes: I have been using many of your demos from the Teaching Stats book . [sent-1, score-0.708]
2 Do you by any chance have a nice easy dataset that I can use to show students how ‘lurking variables’ work using regression? [sent-4, score-1.056]
3 For instance, in your book you talk about the relationship between height and salaries – where gender is the hidden variable. [sent-5, score-1.334]
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Introduction: Rama Ganesan writes: I have been using many of your demos from the Teaching Stats book . . . Do you by any chance have a nice easy dataset that I can use to show students how ‘lurking variables’ work using regression? For instance, in your book you talk about the relationship between height and salaries – where gender is the hidden variable. Any suggestions?
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Introduction: Rama Ganesan writes: I think I am having an existential crisis. I used to work with animals (rats, mice, gerbils etc.) Then I started to work in marketing research where we did have some kind of random sampling procedure. So up until a few years ago, I was sort of okay. Now I am teaching marketing research, and I feel like there is no real random sampling anymore. I take pains to get students to understand what random means, and then the whole lot of inferential statistics. Then almost anything they do – the sample is not random. They think I am contradicting myself. They use convenience samples at every turn – for their school work, and the enormous amount on online surveying that gets done. Do you have any suggestions for me? Other than say, something like this . My reply: Statistics does not require randomness. The three essential elements of statistics are measurement, comparison, and variation. Randomness is one way to supply variation, and it’s one way to model
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Introduction: Rama Ganesan writes: I have been using many of your demos from the Teaching Stats book . . . Do you by any chance have a nice easy dataset that I can use to show students how ‘lurking variables’ work using regression? For instance, in your book you talk about the relationship between height and salaries – where gender is the hidden variable. Any suggestions?
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Introduction: A student I’m working with writes: I was planning on getting a applied stat text as a desk reference, and for that I’m assuming you’d recommend your own book. Also, being an economics student, I was initially planning on doing my analysis in STATA, but I noticed on your blog that you use R, and apparently so does the rest of the statistics profession. Would you rather I do my programming in R this summer, or does it not matter? It doesn’t look too hard to learn, so just let me know what’s most convenient for you. My reply: Yes, I recommend my book with Jennifer Hill. Also the book by John Fox, An R and S-plus Companion to Applied Regression, is a good way to get into R. I recommend you use both Stata and R. If you’re already familiar with Stata, then stick with it–it’s a great system for working with big datasets. You can grab your data in Stata, do some basic manipulations, then save a smaller dataset to read into R (using R’s read.dta() function). Once you want to make fu
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Introduction: Jenny writes : The Possessed made me [Jenny] think about an interesting workshop-style class I’d like to teach, which would be an undergraduate seminar for students who wanted to find out non-academic ways of writing seriously about literature. The syllabus would include some essays from this book, Geoff Dyer’s Out of Sheer Rage, Jonathan Coe’s Like a Fiery Elephant – and what else? I agree with the commenters that this would be a great class, but . . . I’m confused on the premise. Isn’t there just a huge, huge amount of excellent serious non-academic writing about literature? George Orwell, Mark Twain, Bernard Shaw, T. S. Eliot (if you like that sort of thing), Anthony Burgess , Mary McCarthy (I think you’d call her nonacademic even though she taught the occasional college course), G. K. Chesterton , etc etc etc? Teaching a course about academic ways of writing seriously about literature would seem much tougher to me.
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Introduction: Ring Lardner, Jr.: [In 1936] I was already settled in Southern California, and it may have been that first exercise of the franchise that triggered the FBI surveillance of me that would last for decades. I had assumed, of course, that I was enjoying the vaunted American privilege of the secret ballot. On a wall outside my polling place on Wilshire Boulevard, however, was a compilation of the district’s registered voters: Democrats, a long list of names; Republicans, a somewhat lesser number; and “Declines to State,” one, “Ring W. Lardner, Jr.” The day after the election, alongside those lists were published the results: Roosevelt, so many; Landon, so many; Browder, one.
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Introduction: . . . and I decided to amuse myself by writing down all the management-speak words I heard: “grappling” “early prototypes” “technology platform” “building block” “machine learning” “your team” “workspace” “tagging” “data exhaust” “monitoring a particular population” “collective intelligence” “communities of practice” “hackathon” “human resources . . . technologies” Any one or two or three of these phrases might be fine, but put them all together and what you have is a festival of jargon. A hackathon, indeed.
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