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.

answer: the two figures are congruent.

step-by-step explanation: they're congruent because figure efgh is reflected across the x and y axis but it was also rotated.

hope it !

66.666666667%

step-by-step explanation:

divide 150 by 100

divide 100 by 1.5

there you go!

decreased by 33.333333334%