Data Advanced Problem:

Background:

-Dupree Sells heating oil to residential customers.

-Customers may run out of oil.

-Dupree wants to guarantee that the customer's oil tank will never run dry.

-Dupree pledges "50 free gallons" in case a tank runs dry

To estimate customers' oil usage , the home heating industry uses the concept of "degree days."

Degree day is equal to the difference between the average daily temperature and 68 degrees Fahrenheit.

for example: 68-50= 18 (if negative, it will be changed to "zero"). Using degree days and the tank size, the oil industry can estimate

when the customer is getting lo on fuel and when to resupply the customer.

The data gathered from customers is given in the Dupree_fuels.xlsx file:

-The number of gallons of OIL USAGE and the # of degree days since the last oil fill for 40 customers

-The Number of people residing in the homes of 40 customers (more hot water usage)

-Assessment by staff, of home type classification (1-5), is a composite index of the home size, age, exposure to wind, level of insulation, and furnace type. A low home_factor index implies a lower oil consumption per degree day.

Question:

Use data in the Dupree.xlsx file to see whether a statistically reliable oil consumption model can be estimated from the data.

-Use the automated variable selection procedures to find the best model

-Compare the above two models and propose your best possible model.

-Provide a summary of different models used and justify the best model.

-Define the parameters of the proposed model.

-Demonstrate the use of the model through examples

-Would you recommend any explanatory variables to be omitted?

-Would you recommend any other explanatory variables that could be added to the model?

Price: $14.55

Solution: The downloadable solution consists of 8 pages, 655 words and 2 charts.
Deliverable: Word Document