Question 1182322
Let's break down this problem:

1.  **Population of Interest:** All the trucks in the fleet.

2.  **Parameter the Officer Needs:** The *average* propane mileage (in miles per gallon) for *all* the trucks in the fleet. This is a population parameter because it describes a characteristic of the entire group of trucks.

3.  **Sample:** The trucks for which the officer measured and recorded the propane mileage.  This is a subset of the entire fleet.

4.  **Statistic:** The *average* propane mileage (in miles per gallon) calculated from the sample of trucks. This is a sample statistic because it's calculated from the sample data.

5.  **How the Statistic Will Produce the Needed Information:**

The officer will use the sample statistic (the average propane mileage of the sampled trucks) as an *estimate* of the population parameter (the average propane mileage of *all* the trucks).  It's a reasonable assumption that the sample is representative of the whole fleet. The larger the sample, the more confident the officer can be that the sample average is a good estimate of the population average. She can then use this estimated average propane mileage, along with the estimated total distance and fuel cost per gallon, to calculate her projected fuel expenditure:

Projected Fuel Expenditure = (Estimated Total Distance / Estimated Average Propane Mileage) * Fuel Cost per Gallon