It emphasizes the overall trend of the data
line of best fit.
A line of best fit is used to create an image of the overall correlation between two factors on a scatter graph (showing the general shape of the graph). As a line of best fit should be either a straight line or a smooth curve, the line visiting every point would be impossible to retain this shape (as the experimental results will likely not be identical to the theoretic ones). Also, a line of best fit can be used to highlight anomalous results, so the whole point of it would be destroyed if every point was visited anyway.
The line that reflects the general pattern of a graph is called a trend line.
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A best fit graph to some data is exactly that: it is a line which fits the data best according to some optimality criterion. There is a always a trade off in fitting a line to data: one can change the number of degrees of freedom of the underlying equation, which affects how close the line can get to the data points. With more degrees of freedom, the line can more closely approximate the data. This is not to say that more degrees of freedom are better: with too many degrees of freedom, one is merely fitting to the noise in the measurement of the data, and the line will predict subsequent data poorly, when both interpolating and extrapolating the existing data. This is an example of Occam's Razor: one must pick the simplest model which adequately fits the data.
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The line of best fit does not have to start from 0.
Yes but phrased differently
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 is the best possible answer you can get from raw data. They also can be used to make predictions.
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.
Check out the related links section below to see an example of a line of best fit.