APFIVE A researcher suspects nonlinearity in several data sets and considers using a logarithmic transformation on the dependent variable to achieve linearity. Rank the following data sets in order of increasing improvement in linearity from applying the transformation (from least improvement to greatest improvement).
TITLE: Data Sets and Potential Transformations: #000000
| Data Set | Characteristics |
|---|---|
| A | Bacterial growth with exponential increase |
| B | Free-fall distance (quadratic relationship with time) |
| C | Income over time exhibiting diminishing returns |
| D | Temperature fluctuations that are approximately linear |
Temperature fluctuations (D), Free-fall distance (B), Income with diminishing returns ©, Bacterial growth (A)
Bacterial growth (A), Income with diminishing returns ©, Free-fall distance (B), Temperature fluctuations (D)
Free-fall distance (B), Temperature fluctuations (D), Income with diminishing returns ©, Bacterial growth (A)
Income with diminishing returns ©, Bacterial growth (A), Temperature fluctuations (D), Free-fall distance (B) (this order does not align with the expected effect of a log transformation)
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