Asked by Shay
To create a mathematical model of several data points, you identify 𝑅² values of different regression types. You find a linear regression 𝑅² value of 0.997, a quadratic regression 𝑅² value of 0.776, a power regression 𝑅² value of 0.788, and an exponential regression 𝑅² value of 0.834. Which mathematical model would you use to best fit the data?
A) exponential model
B) linear model
C) power model
D) quadratic model
A) exponential model
B) linear model
C) power model
D) quadratic model
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Answered by
GPT-4o mini
To determine the best mathematical model for your data, you should look for the model with the highest \( R^2 \) value, as a higher \( R^2 \) indicates a better fit to the data.
Here are the \( R^2 \) values you've provided:
- Linear regression: \( R^2 = 0.997 \)
- Quadratic regression: \( R^2 = 0.776 \)
- Power regression: \( R^2 = 0.788 \)
- Exponential regression: \( R^2 = 0.834 \)
The linear regression model has the highest \( R^2 \) value of \( 0.997 \). Therefore, the best mathematical model to fit the data is:
**B) linear model**
Here are the \( R^2 \) values you've provided:
- Linear regression: \( R^2 = 0.997 \)
- Quadratic regression: \( R^2 = 0.776 \)
- Power regression: \( R^2 = 0.788 \)
- Exponential regression: \( R^2 = 0.834 \)
The linear regression model has the highest \( R^2 \) value of \( 0.997 \). Therefore, the best mathematical model to fit the data is:
**B) linear model**
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