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savagedata

HN member
Joined
Tue, Feb 20, 2018, 4:58 AM UTC
HN karma
63
Public activity
15 items

About savagedata

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Recent public activity

  1. comment
    Comment #35347354

    Was PayPal trying to verify your identity or that you know your recipient's identity (who's coincidentally your mother)? I'm surprised if PayPal expected you to know your recipient…

  2. comment
    Comment #35200813

    I've found them at HEB and Randall's too!

  3. comment
    Comment #24461366

    One of my favorite data science factoids is how "regression" (to return to a former state) came to mean "prediction of a continuous variable". In the late 1800s, Sir Francis Galton…

  4. comment
    Comment #22762495

    Santa Clara County (South Bay Area) shares a dashboard with cases by age group and deaths by age group: https://www.sccgov.org/sites/phd/DiseaseInformation/novel-co...

  5. comment
    Comment #22151235

    They approximated income, education, and ethnicity at the neighborhood-level (400-600 people) based on census data. That doesn't seem granular enough to me if the poorest families …

  6. comment
    Comment #22020755

    The problem is with multiple-day recovery periods after the surgery. The later in the week your surgery is scheduled, the more likely you'll overlap with the weekend when care is h…

  7. comment
    Comment #22020647

    > Choosing Monday for a surgery increases your chance of success 2 times The title seems poorly worded. The researchers studied mortality rate, not success of procedures. Since the…

  8. comment
    Comment #21855336

    You're looking to test the difference in proportions. I entered 0.93 / 1000 / 0.91 / 650 into this online calculator [1] and got a p-value of 0.14 which means that the difference i…

  9. comment
    Comment #20833843

    When Irma was making landfall two years ago, I did an animation demonstrating this for r/DataIsBeautiful. [1] The real hurricane path is in red with the forecast at each timestamp …

  10. comment
    Comment #19790426

    There are always potential issues when a machine learning algorithm is applied over time. Example #1: Let's say that cancer rates are increasing over time and cameras are improving…

  11. comment
    Comment #19647321

    Thank you for the useful feedback! I'll have to look up GUIDE trees. > This is interesting. I hear it was sqroot(total number of predictors). I was probably looking at the randomFo…

  12. comment
    Comment #19636202

    I wrote this regression tree tutorial a few years back that might be a good complement to the tutorial above since it covers regression instead of classification and goes on to tal…

  13. comment
    Comment #16470329

    I wonder if this study takes into account that, because some professions are skewed toward women and others are skewed toward men, on average women will interact more with women th…

  14. comment
    Comment #16469407

    I couldn't find a more recent source (this is from 2013), but it claims that 12% of SF (San Francisco-San Mateo-Redwood City, CA) jobs are in "high tech" and 29% of San Jose-Sunnyv…

  15. comment
    Comment #16418016

    This is my favorite statistics factoid! Regression/reversion to the mean is the idea that if you observe an extreme value and remeasure it, it will tend toward the average value on…