Answer:
a. A best-fit line is close to most of the data points.
Explanation:
Best-fit lines help show trends or correlations in data
Best-fit Lines
Best-fit lines attempt to create a line that is close to most data points. This line is a function that can be used to estimate data points that are not a part of the original data set. Additionally, best-fit lines will show the trend of the data. For example, if the slope of the best-fit line is constant, then the data points are directly proportional.
Common Misconceptions
Although best-fit lines can be extremely accurate and helpful, they are not perfect. A best-fit line will attempt to minimize the distance between the line and data points, but it will rarely be perfect. In most cases, there is no way to write a line that will perfectly describe the exact coordinates of each data point.
Additionally, data sets can have any type of correlation. It does not need to be proportional or positive. This means that the slope of a best-fit line can be anything.
Finally, as aforementioned, best-fit lines try to fit the data as much as possible. However, this does not mean that the line has to go through any data points. It is possible for best-fit lines to not go through any data points at all.