To create a mathematical model of several data points, you identify the r2 values of different regression types. you find a linear regression r2 value of 0.997, a quadratic regression r2 value of 0.776, a power regression r2 value of 0.788, and an exponential regression r2 value of 0.834. which mathematical model would you use to best fit the data?

a.
power model

b.
exponential model

c.
quadratic model

d.
linear model

1

Option d) linear model

Step-by-step explanation:

Given that to create a mathematical model of several data points,  the R2 values of different regression types were identified

The different values of R square is given as follows:

LInear   ...   0.997

Quadratic ... 0.776

Power regression ...0.788

Exponential ... 0.834

R-squared is a statistical measure of closeness the data are to the fitted regression line. It is also named as the coefficient of determination, 100% indicates that the model explains all the variability of the response data around its mean.  And near 100% gives the nearly perfect model.

Here comparing all R square values we find that linear gives the highest R square almost near 1. Hence linear would be used to best fit the data.

D) linear model

answer: 230 miles ( vote ! )

step-by-step explanation:

180.39 minus 17.99 equals 162.4

then divide 162.4 by .80 to get 230