Question

Discuss the reasons and situations in which researchers would want to use linear regression. How would a researcher know whether linear regression would be the appropriate statistical technique to use? What are some of the benefits of fitting the relationship between two variables to an equation for a straight line?

Describe the error in the conclusion. Given: There is a linear correlation between the number of cigarettes smoked and the pulse rate. As the number of cigarettes increases the pulse rate increases. Conclusion: Cigarettes cause the pulse rate to increase. Discuss causation vs. relationships.

Answer 1

Answer:

1)

A researcher might be interested in using linear regression if he believes that there might be linear relationships between regressor and dependent variable. If there’s any indication of the linearity between regressor or a transformation of regressor then there should be incentive to use linear regression.

There are some benefits of using linear regression. Firstly, the equations are much simpler to understandable. Secondly, there are less number of parameter and hence it reduces the chance of over fitting.

2)

Since the number of cigarettes increases the pulse rate increases so relationship between the variables is positive. But it does not show cuase and effect relationship. So we cannot draw conclusion that Cigarettes cause the pulse rate to increase. Pluse rate can be increased due to bad heart conditions so fast walking etc.