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Testing

  • Statistics Scramble!

    Puzzle (PDF)

    Solution (PDF)

     

  • by Patricia McCann

    When it is clearly seen
    That the sample is extreme,
    Then p is small,
    Reject the null.

  • by Mariam Hermiz

    There's a hippopotamus.
    He's got a hypothesis.
    His null specifies a parameter,
    That he's still skinny, no change in his diameter.
    And if there is a change, that he's gotten fat from all those fries,
    Well that's his alternative, a deviation from his hypothesized size.
    Hoping for the best, he checks his p-value,
    The probability of having extreme data, if the null is true.
    Because his p-value is small, he comes to realize,
    He needs to reject his null, and start to exercise.
    But when he weighs himself, he soon comes to see,
    That there was a type 1 error and he really is skinny.
    His null was really true, but he had rejected it,
    Because his p-value was below threshold and therefore statistically significant.
    But was the change practically significant? He didn't think so.
    For a tonne-weighing hippopotamus, a 10 pound change is too low.
    So although weighing a tonne may not be skinny for me or you,
    The hippopotamus thought so and shouted "Yoohoo!"

     

  • by Nyaradzo Mvududu

    Chance explanation?
    The value is too extreme
    That's significant

  • by Nyaradzo Mvududu

    Dear Karl, thanks for correlation
    Even though it may not be causation
    Your one greatest hit
    Chi-square, that was it
    From "normal" we have liberation

  • By Christine Kohnen and Eric S. van Gyzen

    There was a young Student at Guinness
    Who studied a beer as his business
    His small sample sizes
    Were full of surprises
    With Fisher, the "t" he did finish

  • One day there was a fire in a wastebasket in the office of the Dean of Sciences. In rushed a physicist, a chemist, and a statistician. The physicist immediately starts to work on how much energy would have to be removed from the fire to stop the combustion. The chemist works on which reagent would have to be added to the fire to prevent oxidation. While they are doing this, the statistician is setting fires to all the other wastebaskets in the office. "What are you doing?" the others demand.
    The statistician replies, "Well, to solve the problem, you obviously need a larger sample size."

  • Why don't statisticians like to model clothes?

    Because they are concerned with lack of fit.

    Bruce White

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