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  2. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Tangent line at (a, f(a)) In mathematics, a linear approximation is an approximation of a general function using a linear function (more precisely, an affine function). They are widely used in the method of finite differences to produce first order methods for solving or approximating solutions to equations.

  3. Second derivative - Wikipedia

    en.wikipedia.org/wiki/Second_derivative

    The second derivative of a function f can be used to determine the concavity of the graph of f. [2] A function whose second derivative is positive is said to be concave up (also referred to as convex), meaning that the tangent line near the point where it touches the function will lie below the graph of the function.

  4. List of limits - Wikipedia

    en.wikipedia.org/wiki/List_of_limits

    If is expressed in radians: ⁡ = ⁡ ⁡ = ⁡ These limits both follow from the continuity of sin and cos. ⁡ =. [7] [8] Or, in general, ⁡ =, for a not equal to 0. ⁡ = ⁡ =, for b not equal to 0.

  5. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    From any point on a curve, you can find an approximation of a nearby point on the curve by moving a short distance along a line tangent to the curve. Starting with the differential equation ( 1 ), we replace the derivative y ′ by the finite difference approximation

  6. Tangent - Wikipedia

    en.wikipedia.org/wiki/Tangent

    The tangent line to a point on a differentiable curve can also be thought of as a tangent line approximation, the graph of the affine function that best approximates the original function at the given point. [3] Similarly, the tangent plane to a surface at a given point is the plane that "just touches" the surface at that point.

  7. Partial derivative - Wikipedia

    en.wikipedia.org/wiki/Partial_derivative

    To find the slope of the line tangent to the function at P(1, 1) and parallel to the xz-plane, we treat y as a constant. The graph and this plane are shown on the right. Below, we see how the function looks on the plane y = 1. By finding the derivative of the equation while assuming that y is a constant, we find that the slope of f at the point ...

  8. Linearization - Wikipedia

    en.wikipedia.org/wiki/Linearization

    While the concept of local linearity applies the most to points arbitrarily close to =, those relatively close work relatively well for linear approximations. The slope should be, most accurately, the slope of the tangent line at =. An approximation of f(x) = x 2 at (x, f(x))

  9. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    By doing the above step, we have found the slope of the line that is tangent to the solution curve at the point (,). Recall that the slope is defined as the change in y {\displaystyle y} divided by the change in t {\displaystyle t} , or Δ y Δ t {\textstyle {\frac {\Delta y}{\Delta t}}} .