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.

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

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.

a) 0.25x times 3. (could be wrong on equation.)

b) 2.25 pound of dark chocolate. (can i eat all the chocolate? plz? anyway, again, could be wrong, but i hope im right. all the chocolate together should be 5.25 pounds)

have a good day!

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