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  2. Approximation error - Wikipedia

    en.wikipedia.org/wiki/Approximation_error

    For absolute errors, the opposite is true: are sensitive to multiplication by constants, but not to addition of constants. [ 5 ] : 34 Polynomial-time approximation of real numbers

  3. Fermi problem - Wikipedia

    en.wikipedia.org/wiki/Fermi_problem

    A Fermi problem (or Fermi question, Fermi quiz), also known as an order-of-magnitude problem, is an estimation problem in physics or engineering education, designed to teach dimensional analysis or approximation of extreme scientific calculations. Fermi problems are usually back-of-the-envelope calculations.

  4. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

    n = 1 that yield a minimax approximation or bound for the closely related Q-function: Q(x) ≈ Q̃(x), Q(x) ≤ Q̃(x), or Q(x) ≥ Q̃(x) for x ≥ 0. The coefficients {(a n,b n)} N n = 1 for many variations of the exponential approximations and bounds up to N = 25 have been released to open access as a comprehensive dataset. [16]

  5. Sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_analysis

    Figure 1. Schematic representation of uncertainty analysis and sensitivity analysis. In mathematical modeling, uncertainty arises from a variety of sources - errors in input data, parameter estimation and approximation procedure, underlying hypothesis, choice of model, alternative model structures and so on.

  6. Approximation theory - Wikipedia

    en.wikipedia.org/wiki/Approximation_theory

    In mathematics, approximation theory is concerned with how functions can best be approximated with simpler functions, and with quantitatively characterizing the errors introduced thereby. What is meant by best and simpler will depend on the application.

  7. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    When using approximation equations or algorithms, especially when using finitely many digits to represent real numbers (which in theory have infinitely many digits), one of the goals of numerical analysis is to estimate computation errors. [5] Computation errors, also called numerical errors, include both truncation errors and roundoff errors.