Based on the descriptions provided, here are the appropriate interpretations and the predicted outcomes for both parts (a) and (b):
(a) A local store is keeping track of service times. The table below shows the number of customers served and the time it took.
Description:
- It does not always take the same amount of time to serve each customer.
Predicted number of customers served in 30 minutes:
- You would need to analyze the service times for the given number of customers to make a prediction. If the data shows variability in service times, we could assume an average or consider the best case to find an estimate.
(b) Customers of a certain credit card earn points for using the card. The table below shows the number of points earned for the amount spent.
Description:
- Each dollar spent appears to earn the same number of points.
Predicted number of points for spending:
- If there is a consistent earning rate (like 1 point per dollar), then for a specific amount spent, you can predict the points by multiplying the points per dollar by the total dollars spent.
Given the structure of how to fill in the blanks, the specifics of the predictions rely on the data you have. If you need further details based on the actual data values, please provide those for more tailored predictions.
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