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Initial post question:
Provide an example based on your professional experience of a situation in which using a multiple regression model or nonlinear regression model may have helped your organization make a better decision.
Re:Topic 4 DQ 1
I worked as the club manager in Germany when I was stationed there in the military. When I took over, the club was making an insane profit. The previous club manager had been allowed to do almost anything he wanted since he was running a very successful operation. Shortly after I took over, I found out that a large portion of our sales were thanks to a rather lenient customs policy. The main bulk of our funds were from the German soldiers at our base purchasing cigarettes from us at a fraction of the cost on the economy.
Not long after I took over, the customs began cracking down, which prevented us from selling to the locals. Before long, the huge surplus we had was gone. Had our leadership run a basic multiple regression, they could have learned where our money was coming from and taken steps to improve the other cash generating programs. Instead, I was left with no money for operation and a lot of broken programs to fix. It took a significant amount of time to get the club operating the way it should have.
â€œTo determine which of the independent variables in a multiple regression model is significant, a significance test on the coefficient for each variable is performedâ€ (Render et al., 2015, p. 130). If we had run the multiple regression on the areas of our clubâ€™s sales, we would have seen a very significant RÂ², while the other areas would have been extremely low. That would have given us the opportunity to improve the operation while we still had a steady influx of cash from the sale of the cigarettes.