To find the relationship between lines scanned (l) and errors found (e), we should first determine the proportional relationship from the values given in the table. We notice that as the number of lines scanned increases, the number of errors found increases proportionally.
From the table:
- For 59 lines scanned, there is 1 error found.
- For 1,180 lines scanned, there are 20 errors found.
- For 1,770 lines scanned, there are 30 errors found.
First, we can find the "errors per line" ratio based on the values already provided.
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For 59 lines and 1 error: \[ \text{Error Rate} = \frac{1}{59} \]
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For 1,180 lines and 20 errors: \[ \text{Error Rate} = \frac{20}{1180} = \frac{1}{59} \]
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For 1,770 lines and 30 errors: \[ \text{Error Rate} = \frac{30}{1770} = \frac{1}{59} \]
This consistent error rate suggests the relationship \( e = \frac{1}{59}l \) or equivalently \( e = \frac{l}{59} \).
Now, solving for the unknown \( l \) when given \( e = 5 \): \[ 5 = \frac{l}{59} \] Multiplying both sides by 59 gives: \[ l = 5 \times 59 = 295 \]
Based on this reasoning, the statement that accurately describes the solution would be:
The relationship between lines scanned and errors found can be represented by the equation \( e = \frac{1}{59}l \). Since \( l \) lines correspond with 5 errors, substitute 5 for \( e \) and solve. The unknown value, \( l \), is 295.
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