Determining what variables to include in a multiple regression model can be very challenging. Consider a model with two nonsignificant variables and several significant variables. Removing either of the nonsignificant variables and rerunning the model causes the other nonsignificant variable to become significant. Why might this be happening? What factors would you consider when choosing what variable(s) to include in the final model?
Embed course material concepts, principles, and theories (require supporting citations) along with at least one scholarly, peer-reviewed reference in supporting your answer. Keep in mind that these scholarly references can be found in the Saudi Electronic Library by conducting an advanced search specific to scholarly references.