A Researcher Is Investigating Possible Explanations for Deaths in Traffic $\beta$

A researcher is investigating possible explanations for deaths in traffic accidents.He examined data from 1991 for each of the 50 states plus Washington,DC.The data included information on the following variables. As part of his investigation he ran the multiple regression model, Deaths = $\beta$ ₀ + $\beta$ ₁(Children) + $\beta$ ₂(Income) + $\varepsilon$ _i,
Where the deviations $\varepsilon$ _i were assumed to be independent and Normally distributed with a mean of 0 and a standard deviation of $\sigma$ .This model was fit to the data using the method of least squares.The following results were obtained from statistical software. The researcher also ran the simple linear regression model
Deaths = $\beta$ ₀ + $\beta$ ₂(Income) + $\varepsilon$ _i.
The following results were obtained from statistical software: Based on the analyses,what can we conclude?

A) The variable income is statistically significant at level 0.05 as a predictor of the variable deaths.
B) The variable income is statistically significant at level 0.05 as a predictor of the variable deaths in a multiple regression model that includes the variable children.
C) The variable income is not useful as a predictor of the variable deaths and should be omitted from the analysis.
D) The variable children is not useful as a predictor of the variable deaths,unless the variable income is also present in the multiple regression model.