Correlation is well explained as a number that describes the extent of the relationship between two figure normally known as variables.
Their relationship is described through a number (single value) which is normally referred to as a coefficient.
Correlation coefficient `r’ on the other hand is a number that represents the level of relationship on two standalone variables (Washington et al., 2010). In our case, the finance manager is using the correlation between car purchases and interest rates charged.
The finance manager is using interest rates relation to car sales to forecast on the future expected sales.
There are other factors that the finance manager ought to also consider when making his decision. He needs also to consider, time of the year, economy performance, economy employment rate, etc. In some way, these factors will also correlate with car sales. It is important to consider
interest rate charged but it should not be the only factor that a company considers. The interest rate charged could make it easier to access loans but at the same time buyer’s preference could be somewhere else.
The key reason why the finance manager uses the interest rates charged to forecast on sales is because many cars are bought on loan. This means that when interest rates come down, many customers will be able to qualify for a car loan.
The business could also be selling cars that are meant for middle and lower earning clients. This, therefore, means that most cars will be bought by loan applicants. The 7% prediction is most likely as a result of the low performing economy.
he more interest rates are charged, the lesser people are going to qualify for loans, and also there will be less money in the economy. This will eventually lead to more inflation and fewer sales for the business.
Washington, S. P., Karlaftis, M. G., & Mannering, F. (2010). Statistical and econometric methods for transportation data analysis. CRC press.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge.