The regression model $\hat y = x^T\beta +v$ predicts
the life span (age at death) of a person
in some population, where the feature vector $x$ encodes
various attributes of the person.
Assuming the model fits actual life span data reasonably well
(although of course not very accurately for any particular individual)
what would you guess about $\beta_3$, if $x_3=1$ means the person
is a smoker, and $x_3=0$ means the person is not a smoker?

you can't say without knowing what the other features are
Incorrect.

$\beta_3$ is likely positive
Incorrect.

$\beta_3$ is probably small
Incorrect.

$\beta_3$ is likely negative
Correct!

$\beta_3$ is larger in magnitude than the other $\beta_i$'s
Incorrect.