A recent audit indicated that shipping costs were out of control. J. Peter Trooper, who is the CEO of JPB, has asked your team to analyze a shipping cost dataset (in the accompanying spreadsheet) to see if the significant cost factors can be identified and to determine if the cost of a shipment can be reasonably forecast. Data UPB's operations staff maintains a database of operating data for all long-haul trips. Operating data for a recent year is included in the accompanying spreadsheet. The table below contains a description of the various columns in the spreadsheet. Column Description Departure Date Calendar date that shipment leaves the plant Truck Truck model FCST120 Indicator variable for FCST120 truck type (1 if yes, 0 if no) KWT2000 Indicator variable for KWT2000 truck type (1 if yes, 0 if no) Total Operating Cost Total cost of diesel fuel and DEF Miles Miles traveled (round trip) Driver Experience Years of service (less than a year is 0) Daylight If trip was in at least 50% daylight hours, 1. Otherwise 0. Percent Mountains Percentage of trip that is through mountainous terrain Significant Weather Significant precipitation/thunderstorms/snow Significant Wind High winds Avg Temp Average temperature Avg Speed Average speed maintained by the driver Requirements J. Peter Trooper, JPB's CEO is concerned about shipping costs. In a recent meeting, he asked you to provide information on the following. Use Microsoft Excel for this assignment. 1. What is the problem that JPB is trying to solve? Your problem definition will serve as an introduction to your report. 2. Compute descriptive statistics and a correlation matrix for all of the variables on the spreadsheet (include date and the indicators in the correlation analysis but not the descriptives). Highlight the interesting statistics. What do they tell us about shipping cost? Justify your answers. 3. Find the best one variable regression model to predict total operating cost. Include this model in your report along with a discussion of its quality. 4. Use the trip data in Table 1 below and your one-variable model to predict total operating cost. Include this prediction in your report. Is this prediction reliable? Could you base a decision on this prediction? Use the statistics generated by Excel to support your answer.