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The 36 pages that link to Finite difference, each with the reason it gives.

• DerivativeCompared with: It estimates local change without taking the exact limiting process in the derivative definition.

• Binomial coefficientRelated: Binomial coefficients provide coefficients for repeated finite-difference formulas.

• Mathematical inductionRelated: Polynomial identities proved by induction often correspond to predictable changes between adjacent cases.

• Sensitivity analysisRelated: It estimates sensitivity when analytic derivatives are unavailable.

• GradientCompared with: It estimates gradient components when analytic derivatives are unavailable or impractical.

• Jacobian matrixCompared with: It estimates Jacobian entries without evaluating analytic derivatives directly.

• Partial derivativeCompared with: It estimates change without taking the limiting operation in the derivative definition.

• CalculusCompared with: Unlike derivatives, finite differences measure change over nonzero steps.

• Arithmetic progressionRelated: The first differences of an arithmetic progression are all equal.

• Definite integralCompared with: It is a discrete counterpart to infinitesimal accumulation, not an integral limit.

• Charles BabbageRelated: Finite differences supplied the arithmetic method behind the Difference Engine.

• Difference quotientRelated: Dividing a finite difference by its input step produces a difference quotient.

• Pascal's triangleRelated: Triangle entries also organize finite-difference patterns and polynomial coefficients.

• Secant lineRelated: A finite-difference quotient is the numerical counterpart of a secant slope.

• BackpropagationCompared with: Unlike backpropagation, it estimates gradients through repeated evaluations rather than exact chain-rule propagation.

• Differential calculusCompared with: Unlike a derivative, it uses a nonzero interval rather than an instantaneous limit.

• Marginal analysisRelated: Discrete choices use finite changes when actions cannot vary infinitesimally.

• History of calculusCompared with: It approximates derivatives while remaining distinct from continuous calculus.

• Taylor polynomialRelated: Taylor expansions derive the accuracy and error of finite-difference formulas.

• Difference equationRelated: Finite differences provide a discrete counterpart to derivatives in equations for sequences.

• Euler–Maclaurin formulaRelated: The formula grew from relations between finite differences and derivatives.

• Falling factorialRelated: Finite differences lower the order of falling factorials in a simple way.

• Integer sequenceRelated: Constant higher differences characterize sequences given by polynomial formulas.

• Lagrange interpolationCompared with: Finite-difference formulas can encode the same interpolant in a form suited to equally spaced data.

• Linear approximationCompared with: It estimates the slope from sampled values rather than evaluating the derivative directly.

• Difference engineNarrower topic: The engine advances a table by repeatedly adding stored finite differences.

• Summation by partsNarrower topic: The identity replaces one factor with its finite differences.

• Logarithmic differentiationCompared with: Unlike logarithmic differentiation, it estimates change numerically rather than differentiating symbolically.

• Pascal's ruleRelated: Binomial coefficients and their recurrences organize identities for finite differences.

• Time derivativeCompared with: It approximates a time derivative but measures change across a nonzero interval.

• Instantaneous velocityCompared with: It estimates velocity across a time span rather than exactly at an instant.

• Stolz–Cesàro theoremRelated: Successive differences play the role that derivatives play in continuous limit comparisons.

• Abel's inequalityRelated: The transformed sum contains differences of adjacent weights.

• Differentiation of trigonometric functionsCompared with: It approximates trigonometric derivatives numerically without being the derivative itself.

• Levinson's inequalityRelated: Paired values around a midpoint can be analyzed through differences that expose derivative constraints.

• Ono's inequalityRelated: Differences of partition numbers are natural candidates for quantitative bounds.