Question
Which type of function best models the data in the table?
Type of Function
This table shows the relationship between x and y.
x y
2 0.5
5 −1.75
8 −4
(1 point)
Responses
linear
linear
quadratic
quadratic
exponential
exponential
cubic
Type of Function
This table shows the relationship between x and y.
x y
2 0.5
5 −1.75
8 −4
(1 point)
Responses
linear
linear
quadratic
quadratic
exponential
exponential
cubic
Answers
GPT-4o mini
To determine which type of function best models the data in the table, we can analyze the change in \(y\) values as \(x\) changes. The data points are:
- \( (2, 0.5) \)
- \( (5, -1.75) \)
- \( (8, -4) \)
First, let's check for a linear relationship. In a linear function, the change in \(y\) should be proportional to the change in \(x\):
1. From \(x = 2\) to \(x = 5\):
- Change in \(x\) = \(5 - 2 = 3\)
- Change in \(y\) = \(-1.75 - 0.5 = -2.25\)
- Slope = \(\frac{-2.25}{3} = -0.75\)
2. From \(x = 5\) to \(x = 8\):
- Change in \(x\) = \(8 - 5 = 3\)
- Change in \(y\) = \(-4 - (-1.75) = -2.25\)
- Slope = \(\frac{-2.25}{3} = -0.75\)
The slope remains constant, indicating a linear relationship.
Now let's consider other options such as quadratic or higher degree functions. However, since the slope is consistent, it suggests that the data can be modeled by a linear function.
Given this analysis, the best fitting model for the data is:
**Response: linear**
- \( (2, 0.5) \)
- \( (5, -1.75) \)
- \( (8, -4) \)
First, let's check for a linear relationship. In a linear function, the change in \(y\) should be proportional to the change in \(x\):
1. From \(x = 2\) to \(x = 5\):
- Change in \(x\) = \(5 - 2 = 3\)
- Change in \(y\) = \(-1.75 - 0.5 = -2.25\)
- Slope = \(\frac{-2.25}{3} = -0.75\)
2. From \(x = 5\) to \(x = 8\):
- Change in \(x\) = \(8 - 5 = 3\)
- Change in \(y\) = \(-4 - (-1.75) = -2.25\)
- Slope = \(\frac{-2.25}{3} = -0.75\)
The slope remains constant, indicating a linear relationship.
Now let's consider other options such as quadratic or higher degree functions. However, since the slope is consistent, it suggests that the data can be modeled by a linear function.
Given this analysis, the best fitting model for the data is:
**Response: linear**