Help please !! The least squares regression equation for the data in the table is y= 13.5x + 56.4. The r^2 value is 0.997.

Why might you use a linearized model instead?

A. there is a pattern in the residual plot for the linearized data.

B. this is the best model. You don’t need to linearize the data.

C. The y-values are increasing.

D. The r^2- value of the linearized model is greater than 0.977.

the direct variation says that:

then the equation is of the form is given by:

            where k is the constant variation.

from the given table:

consider any value of x and m(x)=y

x = 2 and m(x)=y = 3

substitute these value in [1]; we have;

divide both sides by 2 we get;

⇒

check:

put x = -1 and m(x) = -1.5

substitute in the equation:

-1.5 = -1.5                   true

therefore, the function m(x) represents a direct variation

graph of this function as shown below:

shift 4 units up, and 1 unit left.

it will translate f(x) = 3^x to g(x) = 3^(x+1) + 4