To determine the type of function model that represents the given dataset, we can analyze the pattern in the y-values corresponding to the x-values.
The provided y-values are:
- For x = 0, y = 5
- For x = 1, y = 35
- For x = 2, y = 245
- For x = 3, y = 1715
- For x = 4, y = 12005
- For x = 5, y = 84035
To check if this relationship is linear, exponential, or quadratic, we can analyze the growth pattern of the y-values.
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Linear Function: A linear function would show a constant rate of change between the y-values as x increases. In this case, the differences between consecutive y-values are increasing rapidly.
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Quadratic Function: A quadratic function typically has a parabolic shape and can be represented as \(ax^2 + bx + c\). The change in differences is not constant, indicating it is not quadratic.
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Exponential Function: Exponential functions have a form of \(y = a \cdot b^x\) where the ratio of consecutive y-values tends to remain constant. Looking at the dataset, the growth between values seems to follow a multiplicative pattern, which suggests it might be exponential.
We can calculate the ratios of consecutive values:
- \( \frac{35}{5} = 7 \)
- \( \frac{245}{35} = 7 \)
- \( \frac{1715}{245} = 7 \)
- \( \frac{12005}{1715} = 7 \)
- \( \frac{84035}{12005} = 7 \)
Since the ratio of successive terms is constant indeed (approx. 7), this indicates an exponential relationship.
Given this information, we conclude that the function model can be represented as: \( f(x) = 5 \cdot 7^x \) which confirms the exponential function.
The correct response is:
- f(x)=5(7^x) and exponential function