Question

Which of these methods would likely result in a better model of the data?

A. Linearize the data by taking the logs of both variables, and then run a linear regression.
B. Linearize the data by taking the log of the response variable, and then run a linear regression.
C. Run a quadratic regression on the data and then linearize the data.
D. Linearize the data by taking the log of the response variable, and then run an exponential regression.

Answer 1

Linearizing the data by taking the log of the response variable and then running a linear regression is likely to result in a better model of the data.

Step-by-step explanation:

The method that would likely result in a better model of the data is option B. Linearizing the data by taking the log of the response variable and then running a linear regression is a commonly used technique to transform data that exhibits exponential growth or decay into a straight line form, which is easier to analyze and interpret. By taking the log of the response variable, the relationship between the variables becomes linear, allowing for a more accurate model of the data.

To determine if a line is the best way to fit the data, you can also calculate the correlation coefficient. If the correlation coefficient is close to 1 or -1, it indicates a strong linear relationship between the variables, which further supports using a linear regression model.

Therefore, by linearizing the data using the logarithm of the response variable and running a linear regression, you are likely to obtain a better model of the data.