Week 9 Reflection

I received a file that held 4 years of sales and promotional data within 5 regions. The data was sent to to have the sales of widgets be analyzed. The question I asked myself while analyzing was, "What region has the most sales due to promotional data". The promotional data that was being analyzed in particular were, Direct Mail, Email, SMS,and Advertising. The equation that was determined to be used to further look at the data was:

=a+(b1*DMAIL)+(b2*EMAIL)+(b3*SMS)+(b4*ADVERT)

This equation was used over all regions to try to predict future sales. The information found that the model predicts certain regions expect to sell way more widgets then others for the first quarter of 2019. This could be due to outside factors such as climate, weather, or location of the different regions from each other. Further, the fifth region was predicted to have the most unit sales while the first region was predicted to have the least. This is important because it must be noted that the fifth region spent $400 on direct mail, while the first region spent $175, and the fifth region also spent $25 more on SMS, and $100 more in Advertising. 

file:///Users/jeremymorris/Downloads/Widget%20Sales%20Spreadsheet.htm