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The points on a scatterplot increase rapidly. You run a linear regression on

the data. The residual plot shows a pattern, and is low.

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

A. Run a quadratic regression on the data and then linearize the data.

B. Linearize the data by taking the log of the response variable, and

then run a linear regression.

C. Linearize the data by taking the logs of both variables, and then

run a linear regression.

D. Linearize the data by taking the log of the response variable, and

then run an exponential regression.

Answer :

batolisis

Answer:

B

Step-by-step explanation:

The method that would most likely result in a better model of the data is to :

Linearize the data by taking the log  of the response variable, and then run a linear regression.

A linear regression can be expressed as

[tex]log(y) = \beta _{0} + \beta _{1} x[/tex]

The linear regression is applied  to improve the model fitting and also helping to linearize the responses which causes an increase in the R-squared value.

Answer:

B

Step-by-step explanation:

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