The appropriate employ of multiple regression depends upon being capable to make four basic assumptions about the data being used to develop the regression model:
that variables are normally distributed;
that the relationship between an independent variable and the dependent variable is linear
that the variance of errors is homoscedastic; and
that there is no multicollinearity among independent variables.
Describe how you would check these assumptions about a dataset that you want to use to build a regression model.