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  2. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    Along this small step, the slope does not change too much, so will be close to the curve. If we pretend that A 1 {\displaystyle A_{1}} is still on the curve, the same reasoning as for the point A 0 {\displaystyle A_{0}} above can be used.

  3. Slope field - Wikipedia

    en.wikipedia.org/wiki/Slope_field

    Solutions to a slope field are functions drawn as solid curves. A slope field shows the slope of a differential equation at certain vertical and horizontal intervals on the x-y plane, and can be used to determine the approximate tangent slope at a point on a curve, where the curve is some solution to the differential equation.

  4. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    A simple two-point estimation is to compute the slope of a nearby secant line through the points (x, f(x)) and (x + h, f(x + h)). [1] Choosing a small number h, h represents a small change in x, and it can be either positive or negative. The slope of this line is (+) ().

  5. Slope - Wikipedia

    en.wikipedia.org/wiki/Slope

    Slope illustrated for y = (3/2)x − 1.Click on to enlarge Slope of a line in coordinates system, from f(x) = −12x + 2 to f(x) = 12x + 2. The slope of a line in the plane containing the x and y axes is generally represented by the letter m, [5] and is defined as the change in the y coordinate divided by the corresponding change in the x coordinate, between two distinct points on the line.

  6. Linear interpolation - Wikipedia

    en.wikipedia.org/wiki/Linear_interpolation

    Linear interpolation on a set of data points (x 0, y 0), (x 1, y 1), ..., (x n, y n) is defined as piecewise linear, resulting from the concatenation of linear segment interpolants between each pair of data points. This results in a continuous curve, with a discontinuous derivative (in general), thus of differentiability class.

  7. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    This shows that r xy is the slope of the regression line of the standardized data points (and that this line passes through the origin). Since − 1 ≤ r x y ≤ 1 {\displaystyle -1\leq r_{xy}\leq 1} then we get that if x is some measurement and y is a followup measurement from the same item, then we expect that y (on average) will be closer ...

  8. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    In non-parametric statistics, the Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes of all lines through pairs of points. It has also been called Sen's slope estimator, [1] [2] slope selection, [3] [4] the single median method, [5] the ...

  9. Distance from a point to a line - Wikipedia

    en.wikipedia.org/wiki/Distance_from_a_point_to_a...

    The line with equation ax + by + c = 0 has slope -a/b, so any line perpendicular to it will have slope b/a (the negative reciprocal). Let (m, n) be the point of intersection of the line ax + by + c = 0 and the line perpendicular to it which passes through the point (x 0, y 0). The line through these two points is perpendicular to the original ...