No.
Usually yes.
If most of them lie below the line, then that line isn't the best fit. The exact layout depends on what definition you use for "best fit", but any definition will produce a line that has roughly the same number of data points on each side of it.
A line of best-fit.
Because the "best fit" line is usually required to be a straight line, but the data points are not all on one straight line. (If they were, then the best-fit line would be a real no-brainer.)
No.
No.
Usually yes.
It is called the line of best fit because it tends to satisfy all the possible points in consideration at the same time with minimal variation.
If most of them lie below the line, then that line isn't the best fit. The exact layout depends on what definition you use for "best fit", but any definition will produce a line that has roughly the same number of data points on each side of it.
The line that minimized the sum of the squares of the diffences of each point from the line is the line of best fit.
A line of best-fit.
Because the "best fit" line is usually required to be a straight line, but the data points are not all on one straight line. (If they were, then the best-fit line would be a real no-brainer.)
What is the difference between a trend line and a line of best fit
The line of best fit does not have to pass through the 0 (origin) and rarely does
Finding the line of best fit is called linear regression.
A best-fit line is the straight line which most accurately represents a set of data/points. It is defined as the line that is the smallest average distance from the data/points. Refer to the related links for an illustration of a best fit line.