ModernDive

@ModernDive

Statistical Inference via Data Science: A moderndive into R & the tidyverse. Print edition now available , online version at .

Joined January 2017

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  1. Pinned Tweet
    Jan 2

    The print editions of ModernDive have arrived! They're real and they're spectacular! 📘👀😍 Get your copy at or

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  2. Retweeted
    Aug 26

    (This simulation-based explanation of p-values comes from {infer} and is used throughout and I've found it's the absolute most intuitive way of teaching about p-values, btw. Once students get the intuition you can skip the simulations)

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  3. Retweeted
    Aug 15

    Our (by and ) book club also kicked off this week, led by ! Check out the first meeting here: the conversation!

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  4. Aug 5

    Hot tip! After teaching students simple linear regression 1. Ask "What's the 3D generalization of a regression line?" 2. Watch the gears grind in their heads ⚙️⚙️ 3. Have them play w/ this interactive 3D scatterplot + plane in Ch 6.2.1 4. Watch their 🤯

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  5. Jul 20

    Check out our newly revamped labs page at , where you'll find instructor resources like - Example problem sets - A term project template students can follow Shout out to for the assist on the update!

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  6. Jul 12

    Correction folks! is a rising *junior* not senior! Undergrads these days are learning that earlier and earlier than ever!

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  7. Jul 6

    Second, we fixed many typos & some unclear wordings. We also added a 🆕 data wrangling "Tips & Tricks" page by Jenny Smetzer! They're based on the 7 most common questions from our intro students while working w/ real data for their term projects

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  8. Jul 6

    Big news! 🆕v1.1.0 is now on & GitHub! First, our source code was cleaned, commented & clarified by rising senior 🧹📝💡😌 If you've ever wanted to build our book, now's the time!

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  9. Jun 29

    Sent in by a fan! While ModernDive is available free online, for deeper topics that require a lot of 🤔🤔🤔 like confidence intervals & hypothesis tests, sometimes a print copy goes a long way! Buy yours today at using promo code ASA18

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  10. Retweeted
    Jun 14

    infer v0.5.2 is now on CRAN!🎉 A grammar for statistical inference that aligns with tidy principles—in this release, new test statistics and vignettes, improved warnings/errors, and more.🙂

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  11. Retweeted
    Jun 15

    Here's my review of TL;DR: I'm convinced this is the future of statistics education and I think this should be everyone's first course in statistical inference. Other things I learned:

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  12. Retweeted
    Jun 5

    Refreshing and getting new ideas of data science approaches in with this book: . It's amazing. Looking forward to getting into afteron. Thank you for your the amazing learning resources!

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  13. May 27

    Video of 's May 19th talk at on how to "teach data science first, statistics second" using ModernDive now available on YouTube

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  14. May 25

    Found a typo in ModernDive? Want to learn about open-source collaboration on ? Then consider fixing the typo yourself via a GitHub Pull Request! Watch this screencast to learn how from the comfort of your browser!

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  15. Retweeted
    May 20
    Replying to

    You're received no shortage of suggestions, but ill add by . I ended up learning basics from a tutor on my sabbatical, but this was the best I saw, when trying to teach myself.

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  16. Retweeted
    May 20
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  17. Retweeted
    May 19

    Here are the slides for my Statistics Dept virtual talk on ways to teach "intro data science first, intro stats second" using Thanks for organizing! It’s an honour! 🇨🇦🍁🇨🇦

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  18. Apr 2

    Once students "know that they know" that ultimately "there is only one test", they have the framework to understand ANY confidence interval & ANY hypothesis test for the rest of their lives h/t 2/2

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  19. Apr 2

    What's the 🔑 to mastering statistical inference? Repetition! REPETITION! 🔊REPETITION!🔊 Students need to "climb the ladder" from sample to population over & over & over again ModernDive does this in five contexts using real data & tools 1/2

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  20. Apr 1
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  21. Apr 1

    ICYMI: Plot parallel slopes regression models using our custom geom layer (many intercepts, common slope) library(tidyverse) library(moderndive) ggplot(mtcars, aes(x = hp, y = mpg, col = factor(am))) + geom_point() + geom_parallel_slopes(se = FALSE)

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