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Unformatted text preview: • We should start with no transformation of the response, and then successively use a stronger transformation until the residuals reveal an acceptable situation • We know we have gone too far in transforming the data when the nonrandom pattern actually reverses itself (i.e., a bowtie pattern switches to become narrower at the ends than the middle) Transformation Sequence Type Formula Example Use None Square Root y’=sqrt (y) Counts Natural Log y’=ln(y+k) Growth data Base 10 Log y’=log10(y+k) Variance Reciprocal Sq Rt y’=1/sqrt(y) Inverse y’=1/y Rate data Power y’=(y+k) x Logit Bounded data ArcSin Sq Rt y’=arcsin(sqrt(y)) Binomial data _ ' ln( ) _ y lower lmt y upper lmt y=...
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 Spring '08
 Staff
 Normal Distribution, Logarithm, DI, Studentized residual

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