Exercise

# Individual Tests of Predictors II

In your previous exercise you obtained the coefficient estimates for the two slopes (money and smiling), and your intercept from the "Estimate" column of `summary()`

.
R performs individual t-tests on these predictors. You can see the outcome of these tests next to the `Estimate`

column from the t-value (`t value`

) and p-value (`Pr(>|t|)`

) column.

Enter `summary(lm(liking ~ smile + money))`

into your console to look at the parameter and select which of the following statements is true.

Instructions

### Possible answers

When controling for smiling, liking is related to money. For every unit increase in money, liking increases by 0.8008.

The intercept is significantly different from 0, such that if we do not give someone money, and do not smile, they will like us 0.6162.

When controlling for money, liking is related to smiling. For every unit increase in liking, money increases by 1.4895.