Question

• Many times, multiple variables can be correlated, affecting the outcome of the dependent variable. Describe, in detail, the process for determining if more than one variable contributes to the outcome of a single dependent variable.
• How accurate is a regression analysis and how do you know? What attributes of the analysis will determine whether the analysis is accurate and to what extent? Can inaccurate regression analyses be used to an analyzer’s benefit? Explain in detail

Answer 1

Answer:

Many times, multiple variables can be correlated, affecting the outcome of the dependent variable. Describe, in detail, the process for determining if more than one variable contributes to the outcome of a single dependent variable.

This relates to Multiple Linear Regression. Multiple variables affecting the dependent variable can be correlated. This is known by multi-collinearity.

One can use stepwise regression to conclude that if more than one variable contributes to outcome of a single dependent variable or not. In stepwise regression (both direction), we start with no variable in the model. Then fit the regression model on each independent variable and see which one is most significant. And again carry on the procedure. This will give the significant variables affecting the dependent variable and problem of multi-collinearity will also get reduced