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A line of best fit can be roughly determined using an eyeball method by drawing a straight line on a scatter plot so that the number of points above the line and below the line is about equal (and the line passes through as many points as possible).
A line of best fit can be roughly determined using an eyeball method by drawing a straight line on a scatter plot so that the number of points above the line and below the line is about equal (and the line passes through as many points as possible).
Such formulas can be rather messy. Here is the formula for a linear least squares line, or best fit straight line: (Remember that the equation of a line is y = MX + b, with m = slope and b = y-intercept.)
Mentor: A line of best fit is often useful to attempt to represent data with the equation of a straight line in order to predict values that may not be displayed on the plot. The line of best fit is determined by the correlation between the two variables on a scatter plot.
The equation y = 3x + 2 is the line of best fit for this data. Explanation: The solution is y = 3x. The y-intercept is 0 and the slope is approximately 3. Therefore, the line of best fit is y = 3x.
Mentor: Well, if the line is a good fit for the data then the residual plot will be random. However, if the line is a bad fit for the data then the plot of the residuals will have a pattern.
Linear Trend line The line is the line of best fit. A straight line that's a good approximation of the data.
The Line of Best Fit is used to express a relationship in a scatter plot of different data points. It is an output of regression analysis and can be used as a prediction tool for indicators and price movements.
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