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Forrest Diamond
@forrestwastaken
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@mariners analytics, previously @newbalance and @trackmanbb and boston 🇨🇦🇺🇸
Seattle, WA
Joined May 2015
RT @DAAAYANKEESLOSE: Game 1 to the good guys! Dodgers 6 Yankees 3 DAAAAAAAAAA YANKEES LOSE!!
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@Sky_Kalkman MA or MS in Data Science is a very common choice, and bootcamps will give you a similar results if you want to compress it further (though harder to work while completing a bootcamp). Not sure I'd recommend either over taking an intro DS course a la carte + public work...
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@krishnanrohit @MadSubrahmanyam @mbateman I found this review pretty helpful on grade skipping impact:
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@MichelleBakels @tweetsbycolin @KevinKusch1 Nor sure what type of tooling you're interested in, but here are some standard data/analytics providers that most MLB teams use: @TrackManBB
@Hawkeye_view
@sportsinfo_sis Some other names of interest: @ZelusAnalytics
@StatsPerform
@catapultsports
@SportLogicInc etc etc
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@kbr0o Feels medium sized when there are parks like discovery, magnussen, Seward, etc, but sure.
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RT @PtDefianceZoo: Meet Nigel our adorable prehensile-tailed porcupine for World Porcupine Day! Our prickly pal loves his scratches from hi…
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@jeffwzimmerman I'm not sure, I can't think of any public resources with current MLS. I think there are some weird technicalities that would make it difficult for a public site to track, but that's not my area of expertise.
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@rileydascience So you can see y *actually equals* 1.1x + N(0, 10000), so the lm() model specification is the same as the data generating function and we know the effect is "real"
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@firstkaransingh @PhDemetri @robertsd @kareem_carr ``` library("tidyverse") x <- 1:10000 y <- 1.1*x + rnorm(length(x), mean = 0, sd = 10000) summary(lm(y~x, data.frame(x, y))) ``` Multiple R-squared: 0.09801 x Pr(>|t|): <2e-16 *** If the noise is large R^2 can be small while still having an effect
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