The slope of this line of best fit is given in the following
Step-by-step explanation:
- The line's slope equals the difference between points' y-coordinates divided by the difference between their x-coordinates. Select any two points on the line of best fit. These points may or may not be actual scatter points on the graph. Subtract the first point's y-coordinate from the second point's y-coordinate.
- A line of best fit (or "trend" line) is a straight line that best represents the data on a scatter plot. This line may pass through some of the points, none of the points, or all of the points.
- A line of best fit is a straight line that is the best approximation of the given set of data.
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It is used to study the nature of the relation between two variables. (We're only considering the two-dimensional case, here.)
- 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).
Calculation the line of best fit
- STAT → CALC #4 LinReg(ax+b)
- Include the parameters L₁, L₂, Y₁
- (Y₁comes from VARS → YVARS, #Function, Y₁)
A more accurate way of finding the line of best fit is the least square method .
You now have the values of a and b needed to write the equation of the line of best fit. See values at the right.
y = 11.73128088x + 193.8521475
