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  2. Semi-log plot - Wikipedia

    en.wikipedia.org/wiki/Semi-log_plot

    On a log–linear plot (logarithmic scale on the y-axis), pick some fixed point (x 0, F 0), where F 0 is shorthand for F(x 0), somewhere on the straight line in the above graph, and further some other arbitrary point (x 1, F 1) on the same graph. The slope formula of the plot is:

  3. Bresenham's line algorithm - Wikipedia

    en.wikipedia.org/wiki/Bresenham's_line_algorithm

    The value of the line function at this midpoint is the sole determinant of which point should be chosen. The adjacent image shows the blue point (2,2) chosen to be on the line with two candidate points in green (3,2) and (3,3). The black point (3, 2.5) is the midpoint between the two candidate points.

  4. Linear function (calculus) - Wikipedia

    en.wikipedia.org/wiki/Linear_function_(calculus)

    The y-intercept point (,) = (,) corresponds to buying only 4 kg of sausage; while the x-intercept point (,) = (,) corresponds to buying only 2 kg of salami. Note that the graph includes points with negative values of x or y , which have no meaning in terms of the original variables (unless we imagine selling meat to the butcher).

  5. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    The above procedure now is reversed to find the form of the function F(x) using its (assumed) known log–log plot. To find the function F, pick some fixed point (x 0, F 0), where F 0 is shorthand for F(x 0), somewhere on the straight line in the above graph, and further some other arbitrary point (x 1, F 1) on the same graph.

  6. Analytic geometry - Wikipedia

    en.wikipedia.org/wiki/Analytic_geometry

    In two dimensions, the equation for non-vertical lines is often given in the slope-intercept form: = + where: m is the slope or gradient of the line. b is the y-intercept of the line. x is the independent variable of the function y = f(x).

  7. 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 ...

  8. Linear equation - Wikipedia

    en.wikipedia.org/wiki/Linear_equation

    Given two different points (x 1, y 1) and (x 2, y 2), there is exactly one line that passes through them. There are several ways to write a linear equation of this line. If x 1 ≠ x 2, the slope of the line is . Thus, a point-slope form is [3]

  9. Secant method - Wikipedia

    en.wikipedia.org/wiki/Secant_method

    Starting with initial values x 0 and x 1, we construct a line through the points (x 0, f(x 0)) and (x 1, f(x 1)), as shown in the picture above.In slopeintercept form, the equation of this line is

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