Estimation

  • Lyrics ©2013 by Lawrence Mark Lesser
    May be sung to the tune of "Call Me Maybe" (Carly Rae Jepsen, Tavish Crowe, and Josh Ramsay)

    I went to find people's heights, I measured each person thrice:
    The numbers didn't match nice - and I said "Oy vey!"
    When I was asked for the mean, I knew I had to come clean:
    I said it's something between - and I gave a range.

    Climb: That's variation: There is correlation
    with stat education, knowin' what's exact or maybe.

    CHORUS: Hey, I don't know mu - and that's not crazy,
    But here's my window: call it maybe.
    I can't say I'm right; I'm not laaaaazy:
    There's always error, so call it maybe.
    Hey, life's uncertain, and that's not crazy,
    But here's my window: call it maybe.
    No way to know mu - quite exaaaaactly,
    But here's my window: call it maybe.

    I give my best argument - so I can feel confident
    At ninety-five percent - for what I portray.
    I need a sense of how far - from my sample's x-bar
    My true parameters are: that's just the way.

    (Repeat Climb, Repeat Chorus)

    Bridge: Before I took a class in stats, I reasoned so bad,
    I reasoned so bad, I reasoned so, so bad!
    Before I took a class in stats, I reasoned so bad,
    And you should know that - I reasoned so, so bad!

    (Repeat Chorus, omitting vocals over first quarter;
    Repeat Bridge, except last 6 words)

    So call it maybe!

  • Lyrics copyright by Kyle White and Bradley Turnbull
    May be sung to the tune of "Jerk It Out" (Caesars)

    Theta one, theta two, which estimator do I choose?
    Both of them unbiased, what now? I'm still so confused.
    I need a better measure than just looking at means. Calculating variance is smart, it seems.
    So here we go!

    'Cause it's easy when you know how it's done.
    Invert the information when the bias is none.
    Can't beat it, bounded from below!
    C-R lower bound!

    Too bad my stat is lacking some efficiency.
    Why can't someone out there tell how to fix this please?
    Sufficient estimators will do the trick --
    condition on them, that will be my fix!
    So thank you Rao!

    'Cause it's easy when you know how it's done.
    Improve an estimator with a sufficient one.
    Just try it, you've got nothing to lose!
    Rao-Blackwell improves!

    'Cause it's easy when you know how it's done.
    Invert the information when the bias is none.
    Can't beat it, bounded from below!
    C-R lower bound

    Watch the video

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