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The graph shows the number of game systems sold since 2015. Based on this information, which function best models the number of...Asked by shmunklee
The graph shows the number of game systems sold since 2015. Based on this information, which function best models the number of game systems sold in millions `x` years since 2015? The graph is a slope that shows three points: (0, 30.5) (1, 21.35) (2, 14.95)
a. y=21.35\left(0.7\right)^{x}
b. y=30.5\left(21.35\right)^{x}
c. =30.5\left(1.3\right)^{x}
d. y=30.5\left(0.7\right)^{x}
answer with one of these responses
a. y=21.35\left(0.7\right)^{x}
b. y=30.5\left(21.35\right)^{x}
c. =30.5\left(1.3\right)^{x}
d. y=30.5\left(0.7\right)^{x}
answer with one of these responses
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Answered by
GPT-4o mini
To determine which function best models the number of game systems sold, we can analyze the points given: (0, 30.5), (1, 21.35), and (2, 14.95).
From the point (0, 30.5), we see that when \( x = 0 \), \( y \) is 30.5, which suggests that \( y \) starts from 30.5 millions when \( x = 0 \).
We also see that the values are decreasing over time, which suggests an exponential decay function.
Now let's examine the given options:
a. \( y = 21.35(0.7)^{x} \) - This starts at 21.35 when \( x = 0 \), which does not match the initial point.
b. \( y = 30.5(21.35)^{x} \) - This is not an exponential decay since \( 21.35 > 1 \), which means it increases.
c. \( y = 30.5(1.3)^{x} \) - This suggests growth, not decay, since \( 1.3 > 1 \).
d. \( y = 30.5(0.7)^{x} \) - This starts at 30.5 when \( x = 0 \) and indicates decay with a base less than 1.
Now, let's quickly confirm that option d fits with the subsequent points. If \( x=1 \):
\[
y = 30.5(0.7)^{1} = 30.5 \cdot 0.7 = 21.35
\]
For \( x=2 \):
\[
y = 30.5(0.7)^{2} = 30.5 \cdot 0.49 \approx 14.95
\]
Thus, the function that best models the data provided is:
**d. \( y = 30.5(0.7)^{x} \)**
From the point (0, 30.5), we see that when \( x = 0 \), \( y \) is 30.5, which suggests that \( y \) starts from 30.5 millions when \( x = 0 \).
We also see that the values are decreasing over time, which suggests an exponential decay function.
Now let's examine the given options:
a. \( y = 21.35(0.7)^{x} \) - This starts at 21.35 when \( x = 0 \), which does not match the initial point.
b. \( y = 30.5(21.35)^{x} \) - This is not an exponential decay since \( 21.35 > 1 \), which means it increases.
c. \( y = 30.5(1.3)^{x} \) - This suggests growth, not decay, since \( 1.3 > 1 \).
d. \( y = 30.5(0.7)^{x} \) - This starts at 30.5 when \( x = 0 \) and indicates decay with a base less than 1.
Now, let's quickly confirm that option d fits with the subsequent points. If \( x=1 \):
\[
y = 30.5(0.7)^{1} = 30.5 \cdot 0.7 = 21.35
\]
For \( x=2 \):
\[
y = 30.5(0.7)^{2} = 30.5 \cdot 0.49 \approx 14.95
\]
Thus, the function that best models the data provided is:
**d. \( y = 30.5(0.7)^{x} \)**
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