An interview question

a) How would you construct a small data set (less than 50 data points) with 2 explanatory variables, such that both explanatory variables and the response variable are Gaussian, but the residual of the linear regression is not Gaussian?
b) How would you construct a small data set (less than 50 data points) with 2 explanatory variables, such that neither the explanatory variables nor the response variable is Gaussian, but the residual of the linear regression is Gaussian?
c) For small sample linear regression, do you think it is necessary to assume normality on any of the following - i) response variable; ii) explanatory variable(s); iii) regression residual? Please explain your answer.
d) Would your answer to the previous question change if we have a large sample data set?