To compare Linear Function 1 and Linear Function 2, let's list their outputs based on the x-values provided in the tables:
Linear Function 1:
- When \( x = 1 \), \( f(1) = 1 \)
- When \( x = 2 \), \( f(2) = 3 \)
- When \( x = 3 \), \( f(3) = 3 \)
Linear Function 2:
- When \( x = 1 \), \( f(1) = 6 \)
- When \( x = 2 \), \( f(2) = 7 \)
- When \( x = 3 \), \( f(3) = 0 \)
Now let's calculate the differences in outputs for corresponding x-values:
-
For \( x = 1 \):
- Linear Function 1: \( 1 \)
- Linear Function 2: \( 6 \)
- Difference: \( 6 - 1 = 5 \)
-
For \( x = 2 \):
- Linear Function 1: \( 3 \)
- Linear Function 2: \( 7 \)
- Difference: \( 7 - 3 = 4 \)
-
For \( x = 3 \):
- Linear Function 1: \( 3 \)
- Linear Function 2: \( 0 \)
- Difference: \( 0 - 3 = -3 \)
In summary:
- The outputs from Linear Function 2 are increased by 5 units when \( x = 1 \), by 4 units when \( x = 2 \), and decreased by 3 units when \( x = 3 \).
Thus, while the outputs are increased by a varying number of units, the specific increase for generalization isn't uniform. The overall trend shows an increase for the first two x-values and a decrease for the last.
Based on the consistently observed changes for \( x = 1 \) and \( x = 2 \):
The outputs from Linear Function 2 are increased by 5 and 4 units, respectively, for \( x = 1\) and \( x = 2\).
Therefore, we can summarize that the outputs from Linear Function 2 are increased by 5 units for \(x = 1\), by 4 units for \(x = 2\), and decreased by 3 units for \(x = 3\).