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Solving a Ticket Mixture Problem with Full-Fare and Reduced-Fare Passengers
Apply the seven-step problem-solving strategy, the total-value model, and the known-total technique to a ticket mixture problem involving a given total number of tickets sold at two distinct price points.
Problem: A whale-watching ship had paying passengers on board. The total revenue collected from tickets was $. Full-fare passengers paid $ each and reduced-fare passengers paid $ each. How many full-fare passengers and how many reduced-fare passengers were on the ship?
- Read the problem and identify the types involved: full-fare passengers (worth $ each) and reduced-fare passengers (worth $ each). The total number of passengers is and the total revenue is $.
- Identify what to find: the number of full-fare passengers and the number of reduced-fare passengers.
- Name the unknowns using a single variable and the known-total technique. Let = the number of full-fare passengers. Since the total number of passengers is , the number of reduced-fare passengers is . Organize in a table:
| Type | Number | Value ($) | Total Value ($) |
|---|---|---|---|
| Full-fare | |||
| Reduced-fare | |||
| Total |
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Translate into an equation. The value of full-fare tickets plus the value of reduced-fare tickets equals the total value:
-
Solve the equation:
- Distribute :
- Combine like terms:
- Subtract from both sides:
- Divide both sides by :
Find the number of reduced-fare passengers: .
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Check the mathematical result against the stated scenario: There were full-fare passengers who paid $ each and reduced-fare passengers who paid $ each. Combining these yields:
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Answer: There were full-fare passengers and reduced-fare passengers.
This core example demonstrates the typical ticket mixture problem setup. By recognizing the known total ( passengers) and assigning expressions like and , we seamlessly create expressions for the total value without needing multiple variables.
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Solving a Ticket Mixture Problem with Full-Fare and Reduced-Fare Passengers
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Identifying Expressions in the Known-Total Technique