The facility manager at a pharmaceutical company wants to build a regression model to forecast monthly electricity
Question:
The facility manager at a pharmaceutical company wants to build a regression model to forecast monthly electricity cost (Cost in $). Three main variables are thought to influence electricity cost:
(1) Average outdoor temperature (Temp in °F)
(2) Working days per month (Days)
(3) Tons of product produced (Tons). A portion of the past monthly data on 80 observations is shown in the accompanying table.
a. Estimate the linear model Cost = β0 + β1Temp + β2Days + β3Tons + ɛ. What is the predicted electricity cost in a month during which the average outdoor temperature is 65°, there are 23 working days, and 76 tons are produced?
b. Estimate the exponential model ln(Cost) = β0 + β1Temp + β2Days + β3Tons + ɛ. What is the predicted electricity cost in a month during which the average outdoor temperature is 65°, there are 23 working days, and 76 tons are produced?
c. Based on R2 , which model provides the better fit?
Step by Step Answer:
Business Analytics Communicating With Numbers
ISBN: 9781260785005
1st Edition
Authors: Sanjiv Jaggia, Alison Kelly, Kevin Lertwachara, Leida Chen