- A relation is a function only if each input maps to exactly one output.
- In the provided table, the input \(x=2\) is associated with two different outputs: \(0\) and \(2\).
- Because a single input maps to multiple outputs, the relation is not a function.
- The correct option is \(\boxed{b}\).
Explanation
- Analyzing the Definition of a Function
A relation is defined as a function if each input (the \(x\)-value) corresponds to exactly one output (the \(f(x)\)-value). To determine if the given table represents a function, we must examine the input \(x\)-values and ensure that no single \(x\)-value is mapped to more than one distinct \(f(x)\)-value. The table provided is as follows:
\[ @@TABLE_TOKEN_0@@ \]
- Evaluating the Table Data
By examining the table, we identify the domain of the relation as \(\{0, 1, 2, 3, 4\}\). We check the mapping for each input value:
- For \(x=0\), \(f(0) = -5\)
- For \(x=1\), \(f(1) = -2\)
- For \(x=2\), we see two entries: one where \(f(2) = 0\) and another where \(f(2) = 2\)
- For \(x=3\), \(f(3) = 4\)
- For \(x=4\), \(f(4) = 7\)
The input \(x=2\) is associated with two different outputs, \(0\) and \(2\). Since a function must assign exactly one unique output value for every input in its domain, the presence of multiple outputs for a single input confirms that this relationship fails the vertical line test and the formal definition of a function.
- Conclusion
Based on the analysis, the relation is not a function because the input \(x=2\) corresponds to two distinct values, \(0\) and \(2\). Therefore, the correct answer is b. no. The final result is \(\boxed{b}\).
Examples
Imagine you are looking at a vending machine menu where each button represents an input (x). If pressing a single button, like button 'A2', sometimes dispensed a soda and other times dispensed a candy bar, you would be very confused because there is no consistency. Just like that, a mathematical function must be predictable—every input must lead to exactly one specific output. In data sets, identifying these inconsistencies is vital for ensuring your models, schedules, or algorithms work reliably.