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Two variables, $x$ and $y$, were taken on $10$ subjects and two separate regression models were fit to the data.

Regression I yielded the following equation and residual plot:

predicted log y = ax + b

...where $a$ and $b$ are constants.

Regression II yielded the following equation and residual plot:

predicted log y = d + log cx

...where $c$ and $d$ are constants.

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Which of the following conclusions is correct?

A

Regression I is appropriate since the relationship between $x$ and $y$ is linear.

B

Regression II is appropriate since the relationship between $x$ and $y$ is linear.

C

Regression I is appropriate since the relationship between $x$ and $\log y$ is linear.

D

Regression II is appropriate since the relationship between $x$ and $\log y$ is linear.

E

Regression II is appropriate since the relationship between $\log x$ and $\log y$ is linear.

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