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In the opening episode to Season 4, Greg and Patrick delve into ordinary least squares estimation: where it came from, what it attempts to achieve, and where it can take us from here. Along the way they also discuss Golden Retrievers who are neither golden nor retrieve, Olivia Newton-John, sub-conning out their own work, the meat sweats, sh*t you should know, being intolerably self-righteous, losing your camel, saying ham in French, Calvinball, Frank finding Gauss's corpse, crudely describing regression, and Sexy Hulk.
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In this, their 100th episode and Season 3 finale, Greg and Patrick talk about the challenges and joys of a career in academia. Helping to ensure that we don’t let the bastards grind us down are the voices of three insightful assistant professors and three wonderful graduate students. Along the way, we also mention lining up the napkin, hug free zones, margarita night in 2003, relying on the kindness of strangers, Strunk & White voodoo, a mile-high C, Mr. October, going beyond the veil, the Black Plague, messages in bottles, the gates of the citadel, turning the container ship, work-work balance, being the bad guy, the focus groups in my head, 50cc of sodium phenobarbital, that’ll do pig, front wheel drive/rear wheel drive, and attaboys.
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In this week's episode Patrick and Greg get to hang out with Noah Greifer from the Institute for Quantitative Social Sciences at Harvard University to delve into the fascinating world of propensity scores: what they are, how we obtain them, and how they can be thoughtfully used to strengthen our causal inferences. Along the way we also mention Popular Woodworking, fixing things on the back end, hiding your own Easter eggs, 18 hour warnings, easy undergrad majors, Meyers-Briggs career predictions, picking an ideal advisor, SASholes, demyelination, hearing asterisks, being an ANCOVist, the 11th Commandment, what keeps you up at night, answering the question you want to, and it's all BS.
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In this week's episode, Greg and Patrick talk about information theory: what it is, where it comes from, how it works, and how it can be used to make comparative model inferences. Along the way we also mention Pennsylvania 6-5000, the time lady, the Nobel Prize for Awesomeness, juggling and unicycles, enigma, imaginary friends, lemon juice code, red giants and white dwarves, bits, a level-11 paladin, Hungarian Forrest Gump, snake eyes and boxcar Willies, the Reaper Divergence Criterion, and getting inspirations on a train.
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In this week's episode Greg and Patrick discuss the sometimes terrifying issue of fungible weights in multiple regression and structural equation modeling in which selecting a trivially worse criterion of fit can often lead to radical changes in the corresponding parameter estimates. Along the way they also discuss competitive family Wordle, disambiguation, inflammability, perpitty, being nonplussed, running laps after practice, schmungible, audio eyerolls, Haystacks at Sunset, hyper eggs, the Spiderverse, mountain moonrises, tin cans and strings, and Earthquake Waller.
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In this week's episode Patrick and Greg explore Sewall Wright's path tracing rules as an alternative to covariance and matrix algebra, including how the rules work and the tremendous insights they can provide toward understanding a model. Along the way they also discuss the Unabomber, Crate & Barrel, grocery lane profiling, tedious as poop, throwing dead cats, senior animal husbandman, using your fingers, creepy guy in an alley, sweat pants vs. suits of armor, getaway car drivers, hold my Guinea pig, chalkboard contests, Western Kansas, and getting tased.
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In this week's episode Greg and Patrick continue their discussion from last week in The Mättrix Part Deux, exploring the magic of matrices including estimation, eigenvalues, and eigenvectors. Along the way they also mention flawed audio transcripts, 50 Shades of Greg, drunkenly shoving a matrix, drug mules, things you need, isomorphic interdigitation, plywood and tennis balls, heroin-filled condoms, talking to volleyballs, bawitdaba da bang a dang diggy diggy, meat grinders, not going to prom, vector bouquets, and The Wright Stuff.
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In this first of two episodes, Patrick and Greg lay the foundations of matrix algebra, mathematically and geometrically, and start connecting these important underlying ideas to statistics. Along the way, they also mention STDs, the 110 to the 10 to the 405, mystics, skin bags of water, vector Victor, Tac flashlights on misty nights, remembering mnemonics, Stephen Hawking, Bilbo Baggins, and Greg's sultry voice.
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In this week's episode Greg and Patrick discuss the critical distinction between sample distributions and sampling distributions, and explore all the different ways in which sampling distributions are foundational to how we conduct research. Along the way they also mention Starbucks jazz, one item tests, hot pockets, delusions of grandeur, Tetris and Pong, drawing inappropriate distributions, magical properties, texting pictures of kindle pages, Roman arches, 1970s graphics, never saying never, mumbling, Greenday, ignoring Roy Levy, real life bootstrap, and Goodnight Gracie.
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Patrick and Greg discuss the rise of machine learning in the social sciences with guest Doug Steinley, Professor in the Department of Psychology at the University of Missouri at Columbia and current editor of the APA journal Psychological Methods. Along the way they also mention funeral expenses, Swedish massage, Amy the Chatbot, irony versus coincidence, lavender bath bombs, varmint removal, Planet of the Apes, Voltron, the Cookie Monster, theory smoothies, Bugs Bunny and Yosemite Sam, ironing your Christmas paper, and meat grinders.
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