In a packaging operation, excessive use of adhesive has been a major problem with a new product assembly line. Not only is it wasteful and expensive, but it also led to several packaging issues. A multiple regression analysis is being used to help understand the source of the problem.

The daily adhesive usage ("Usage", grams) has been identified as the dependent variable to be predicted from the following independent variables that were likely causes of trouble: packaging machine average temperature ("Temp", degrees Celsius), age of packaging machine ("Age", months), time elapsed since last machine calibration ("Calibration", months), and whether the operator of the packaging machine has completed a new training program ("Training", Yes=1; No=0). Data set is available in the Excel template file.

Part A:Determine the estimated regression equation predicting daily adhesive usage from all independent variables described above.

Part B:Use all appropriate measures from your regression report to assess the fit and significance of your regression model.

Part C:Explain/interpret the slope coefficient for variable "Training" in the context of this analysis.

Part D:A conjecture has been made that the daily adhesive usage will drop as much as 7.5 grams, on average, if the operator of the equipment has completed a new training program (holding other independent variables constant). Based on your regression analysis, is this a reasonable conjecture? Why?

Part E:Based on your equation reported in Part A), what is the expected daily adhesive usage of a packaging machine that operates at an average temperature of 31 degrees Celsius, is 24-month-old, was last calibrated 1 year ago, and is operated by an operator who has completed a new training program.