Is this linear regression equation a good fit for the data? Why or why not? A. r = - .7622 , so this is a good negative correlation fit for the data . B. r = - .9919 , so this is a very good negative correlation fit for the data C. r = .9919 , so this is a very good positive correlation fit for the data . D. r = .7622 so this is a good positive correlation fit for the data .

 Is this linear regression equation a good fit for the data? Why or why not? A. r = - .7622 , so this is a good negative correlation fit for the data . B. r = - .9919 , so this is a very good negative correlation fit for the data C. r = .9919 , so this is a very good positive correlation fit for the data . D. r = .7622 so this is a good positive correlation fit for the data .

Step-by-step explanation:

answer

a,b, and d

explanation

a reflection angle is more than

but less than;

an angle that measures

is a reflex angle.(true)

an angle that measures less than

is acute.(true)

provided we are considering angles greater or equal to zero.

an acute angle lies in the range.

an obtuse angle is less than 180° but more than 90°

an angle that measures 300° is obtuse (false)

an angle that measures 65° is an acute angle.(true)

option a is correct.

step-by-step explanation:

scale factor: it is used to find proportional measurements.

proportions means having the same ratio.

scale factor is the ratio of the model measurement to the actual measurement in a simplest form.

or we can say that the ratio of any two corresponding lengths in two similar geometric figures

if the scale factor is more than 1, then it is an enlargement,

if the scale factor less than 1, then it is a reduction.

given the two geometric figure:

by definition of proportions, we have