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Assessing Residual Plots for Linearity

APSTAT-UKKLIP

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:

$$\text{predicted log:} \quad y = ax + b$$

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

Regression $II$ yielded the following equation and residual plot:

$$\text{predicted log:}\quad y = d + log cx$$

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

Albert.io. Copyright 2016

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.