1) Assessing the goodness of fit of a regression line involves considering several things, and no single characteristic of data is sufficient for a good assessment. Consider the characteristics below. How does each contribute to an assessment of fit? That is, for each piece of information, what about it would indicate a "good" best-fit line?

A) the shape of the residual
B) the correlation coefficient

Question

1) Assessing the goodness of fit of a regression line involves considering several things, and no single characteristic of data is sufficient for a good assessment. Consider the characteristics below. How does each contribute to an assessment of fit? That is, for each piece of information, what about it would indicate a "good" best-fit line?

A) the shape of the residual
B) the correlation coefficient

anonymous · Answer

@Hasan-Koush

anonymous · Answer

what it is saying is "state what would indicate a 'good' best-fit line for both A and B"

anonymous · Answer

Ohh that's why lol. I'm stupid XD 
The shape of the residual assesses the decline rate of the regressing line
The correlation coefficient shows how accurate the shape and line both are plotted on a graph