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Chapter 10: Re-expressing Data It’s easier than you think!
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Goals of Re-expression Goal 1: Make the distribution of a variable more symmetric. Easier to summarize the center, using mean and standard deviation. If distribution is unimodal, use the 68-95-99.7 Rule.
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Goals of Re-expression Goal 2: Make the spread of several groups mare alike, even if their centers differ. Goal 3: Make the form of the scatterplot more nearly linear. Goal 4: Make the scatter in the scatterplot spread out evenly rather than following a fan shape.
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The Ladder of Powers PowerNameComment 2y2y2 Unimodal, skewed left 1Raw data Data that takes on +/- values ½y 1/2 Counted data 0logarithm Measurements that cannot be - - ½1/ y 1/2 Preserves the direction of relationship -1/yRatios of two quantities
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Attack of the Logarithms Model Namex-axisy-axisComment Exponentialxlog(y)Useful with values that grow by % increase. Logarithmiclog(x)y Useful with wide range of x values or scatterplot descending rapidly then leveling off. Powerlog(x)log(y) When one of the ladder’s powers is too big and the other is too small.
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Let’s Try It! (Pg 192) Shutter speed and f/stop of the lens L1: shutter speed L2: f/stop Curved stat plot Try logarithms Take log of L1→L3 Take log of L2→L4
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Let’s Try It! Scatterplot #1: Xlist→L3, Ylist→L2 Scatterplot #2: Xlist→L1, Ylist→L4
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Let’s Try It! Use Scatterplot #3: LinReg L3, L4 LinReg L3, L4
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Multiple Benefits A single re-expression may improve each of our goals at the same time. Re-expression certainly simplifies efforts to analyze and understand relationships. Simpler explanations and simpler models tend to give a true picture of the relationship. (Occam’s Razor)
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TI Tips Regressions that automatically and appropriately re-express the data:
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Equivalent Models Type ofRe-expressionCalculator’sCurve ModelEquationCommandEquation Logarithmic LnReg Exponential ExpReg Power PwrReg
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What Can Go Wrong?!? Beware of multiple modes. Re-expression cannot pull separate modes together. Watch out for scatterplots that turn around. Watch out for negative data values. It is impossible to re-express negative values by any power that is not positive.
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What Can Go Wrong?!? Watch for data far from one. Re-expressing data with a range from 1 to 1000 is far more effective than re-expressing data with a range of 100,000 to 100,100. Don’t stray too far from the ladder. Stick to powers between -2 and 2. Stick to the simpler powers contained in the “ladder.”
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