Question

You are the buyer for your area's large fashion store (Think a Macy's or JCPennys). You have the authority to buy for your stores whatever quantities from the list of corporate approved brands and items for your stores. This is to accommodate for regional temperature and other differences (example - Miami and Pensacola are both in Florida, but they have different climates, different population demographics and so differences in what is purchased is warranted). Oftentimes, corporate will approve new vendors but not provide much information about them. You often get emails or calls from the vendor representatives pushing you to order their new products or brands.

You are leery of just ordering everything, as losses on merchandise from having to clearance it out affect your stores' (as well as your own) profitability and employee bonuses. Having seen the use of big data, you have decided to try to use the stores sales data to help you make predictions on what to buy, as well as how much to order, and how much profit your store should make off it.

• Required in your Submission:
  • Analyses that support the best predictive model, including a graph and summary of the model.
  • Calculations supporting your specific recommendations of which new products to order and how many of each item.

New Product 3
Item Type	Purchase Price from manufacturer/designer	number of colors	suggested retail price	Known Brand	previously purchased this brand	true sizing	multiple size options (tall, petite, plus, etc)
Jeans	15.75	3	69.99	no	no	unknown	yes
Shorts (denim)	7.89	5	25.99
Jacket (denim)	18.55	1	44
Jacket Mixed materials including Denim	14.45	1	50

Answer 1