Explain why a variable might be significantly associated by itself, but not in the presence of other variables.

A. Partial variance is used to measure the strength and direction of a linear relationship when taking into account other variables,that is why it does not explain the dependent variable significantly.

B. When present with other variables, the error variance decreases, the total variance stay the same. Thus, the variable is explaining more of the total variance in the outcome variables on it own.

C. The predictors are all weak to moderately correlated with each other. Thus, they are explaining much of the same variance and so explain relatively little unique variance in the outcome variables on their own.