Regression and Correlation are two of the most often used and abused tools in re
ID: 3209309 • Letter: R
Question
Regression and Correlation are two of the most often used and abused tools in research. People are quick to jump to conclusions that if a relationship exists between two variables, then one must cause (causation) the other.
There are many reasons why two variables can be related without causality. Please respond to the following:
a. Comparing the amount of money people spend and the amount people save, your analysis revealed an R-squared=0.97. Should you use this for predictive purposes and why?
b. Comparing the number of cops on our streets and the number of reported crimes, your analysis revealed an R-squared=0.40. Should you use this for predictive purposes and why?
c. How could this apply in insurance industry?
Explanation / Answer
Answers to the question:
1. Yes, because a R squared of 97% means a near accurate prediction power of prediction of the predictor variable
2. No, because a R squared of 40% is weak in turn of accuracy in predicting the dependent variable.
3. Comparing cost of insurance vs. age of people going for insurance