1. In regression analysis, interaction terms allow us to test whether the relationship between the dependent variable and one independent variable is different at various values of a second independent variable:

a) True

b) False

2. When a regression model leaves out relevant independent variables, the estimated coefficients can suffer from:

a) Omitted Variable Bias

b) Confirmation Bias

c) Selection Bias

3. In a linear regression, a statistically significant coefficient is always indicative of a causal relationship between the independent and dependent variable:

a) True

b) False