If you plot data points on a graph the rarely will form a straight line. Least squares is a method of finding a line 'close' to all the data points instead of just guessing and drawing a line that looks… Full Answer
it is called best fit because it minimizes the sum of square of the distances of points from line. That is to say, if you add up the squares of the distance of the different data points from the line… Full Answer
A line of best fit is a technique used in statistics. It is a line that represents the relationship between data points showing two variables. It is "best" according to some user-specified criteria. The least squares regression line is the… Full Answer
There are many methods, though the most popular is the method of least squares. This method minimises the sum of the squares of the vertical distances between each point and the corresponding point on the line.
Whenever you are given a series of data points, you make a linear regression by estimating a line that comes as close to running through the points as possible. To maximize the accuracy of this line, it is constructed as… Full Answer
The graph and accompanying table shown here display 12 observations of a pair of variables (x, y). The variables x and y are positively correlated, with a correlation coefficient of r = 0.97. What is the slope, b, of the… Full Answer
a line has to have at least 2 points. a plane has to have at least 3 points. ______________ It takes two points to define a unique line in Euclidean space. But every line and every line segment contains infinitely… Full Answer
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… Full Answer
If the question is about a scatter plot, the the data points will be not be located on a straight line but will be displaced by a random element. Connecting the points will give a zigzag line which will fit… Full Answer
There can be a few reasons. One reason is that the line is wrong, either it has been placed wrong or it is the wrong type of line (linear when it should be exponential) there may even be no line… Full Answer
That will depend on how you have defined "best fit". -- If it means "maximizes the number of points that are right on", then you'll want to jockey the line around so that as many data points as possible fall… Full Answer
The method used to calculated the best straight line through a set of data is called linear regression. It is also called the least squares method. I've included two links. I know the wikipedia link is a bit complicated. The… Full Answer
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… Full Answer
Usually when there's 2 dots(data points), you can place a line. When there's more data points, there's way to calculate "best line" that reduces error to the minimum. So kind line best choice of approximate line that defines these dots.