Correlation/Regression

  • lyrics by Greg Crowther and Leila Zelnick
    may be sung to the tune of "You're the One That I Want" by John Farrar

    DZ: You’ve got data from a trial
    With a treatment and control;
    An ANOVA can determine
    If the treatment's workin'!

    SO: You better shape up --
    No ANOVA, man!
    Use a tool that’s more precise!
    You better shape up --
    Do ANCOVA, man!
    Make your error bars look nice!

    DZ: Make 'em nice!
    "Use ANCOVA" is my advice!

    BOTH: CHORUS:
    What's the method you want?
    (Method that you want, ooh, ooh, ooh!)
    It depends on the study you’ve got!
    (Study that you've got, ooh, ooh, ooh, Honey!)
    What's the method you want?
    Method that you want, ooh, ooh, ooh!)
    It just depends (just depends)!
    Be smart, my friends (yes, my friends)!

    SO: If your groups aren’t random,
    Different baselines may be seen.
    An ANCOVA will regress them
    To the mean.

    DZ: You better shape up,
    ’Cause you need to know...
    SO: ...You need to know
    How group changes should be scored.
    DZ: A question asked
    That is unconditional...
    SO: ...Unconditional,
    Needs ANOVA, nothing more.
    DZ: Nothing more...
    BOTH: ...As explained by Frederic Lord!

    BOTH: CHORUS

    [repeat and fade]

  • by Dane C. Joseph

    It began when an intercept
    directed some concepts—
    strength and direction—
    to capture covariance.

    A line mapped two variables,
    a plane modeled more.
    All seeking least-squares variance
    and following the law.

    But they ran into trouble
    when a categorical response
    tricked moderator and predictor
    into romantic nonchalance.

    By then it was too late
    as in hindsight you could see
    Linear r^2 was incapable
    to do a Nagelkerke.

    And I’m still not quite sure
    why the sigs from the F’s,
    were not up to snuff
    as the Wald difference tests.

    But in the courtroom we heard
    the lawyers and judge
    decry her dereliction...
    then subpoenaed probability and odds.

  • by Jules Nyquist

    when zero
    is a temperature
    it is an interval scale
    that dips below an imaginary
    line to go negative, as in a thermometer
    in a pandemic used as permission to measure

    our temperature, but how do we measure
    something that falls below zero
    like the weight of a bird—our thermometer
    won’t register an invisible temperature
    and we will disappear like the imaginary
    checkbook balance of youth, on a scale

    of probability, the chances of converting the Fahrenheit scale
    to Centigrade was remote, the U.S. still measured
    in Fahrenheit behind the rest of the imaginary
    world where a bank balance waits to zero-
    out and a raven pulls shiny coins from the sky in a temperature-
    controlled out-of-the ether mainframe thermometer

    six thousand feet above sea level, a thermometer
    measures the speed on a speedometer scale
    when the motorcycle driver hurls over a temperature-
    reduced mountain ridge to an almost measurable
    crash that soars into a stock-market zero-
    point of ratio scaling, a lie on an imaginary

    boundary where the motorcycle driver imagines
    they never hit the car and the thermometer
    never registered above human normal and zero
    meant nothing, it was only an innocent bathroom scale
    that we blamed added ten immeasurable
    pandemic pounds to our weight and the temperature

    of Earth rose only in the height of trees,
    a temperature that didn’t take into account the imaginary
    altitude sickness that turned out to be very measurable
    and tripled the effect of the beer stored in a thermal
    cooler, found by the side of the scaled
    curve of that mountain road where zero

    was just a measurement of temperature
    and the imaginary paper bank statement never showed zero
    due to there was nothing to scale on the erratic thermometer.

  • Lyric copyright Dennis K Pearl
    may sing to the tune of "My Bonnie Lies Over the Ocean" (Scottish folk song)

    My Data lies over the average
    Much higher than I’ve ever seen
    And if I take one more sample
    Oh, expect it back towards the mean

    My Data lies over the average
    Much higher than ever seen
    Well, give me one more sample
    Yeah, expect it back closer to mean

    Yeah bring back, ah bring back
    Oh bring data more towards the mean, the mean
    (Ah bring) Oh bring back, ah bring back
    Oh bring back my Data to mean.

    Well, my Data lies over the average
    My proportion’s well over the p
    Yeah, give me another proportion
    Oh, expect it back closer to p

    Yeah bring back, ah bring back
    Oh bring back the data to mean to mean (to mean)
    Oh bring back, ah bring back
    Oh bring back my Data to mean.

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