Evaluate Model Fit with Residuals Practice Test

A meteorologist fit the linear model $\hat{y}=12+0.6x$ to predict afternoon temperature (y, in °C) from morning temperature (x, in °C). The residuals show this pattern:

For small x values, residuals are mostly positive; for medium x values, residuals are near 0; for large x values, residuals are mostly negative.

What does the residual pattern suggest about the model choice?

A city planner fit the model $\hat{y}=200+15x$ to predict daily subway riders (y, in thousands) from the number of downtown events (x). The residuals for x = 0 through 6 events were:

x: 0, 1, 2, 3, 4, 5, 6

residual: 2, -1, 1, -2, 0, 2, -2

Which statement best describes how well the model fits the data?