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  2. Matrix difference equation - Wikipedia

    en.wikipedia.org/wiki/Matrix_difference_equation

    The first-order matrix difference equation [x t − x*] = A[x t−1x*] is stable—that is, x t converges asymptotically to the steady state x* —if and only if all eigenvalues of the transition matrix A (whether real or complex) have an absolute value which is less than 1.

  3. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    (The notation | x | means the absolute value of x; the magnitude of x with the sign set to +, regardless of the original sign of x.) This q s test statistic can then be compared to a q value for the chosen significance level α from a table of the studentized range distribution .

  4. Small-angle approximation - Wikipedia

    en.wikipedia.org/wiki/Small-angle_approximation

    The red section on the right, d, is the difference between the lengths of the hypotenuse, H, and the adjacent side, A. As is shown, H and A are almost the same length, meaning cos θ is close to 1 and ⁠ θ 2 / 2 ⁠ helps trim the red away.

  5. Exponentiation - Wikipedia

    en.wikipedia.org/wiki/Exponentiation

    The binary number system expresses any number as a sum of powers of 2, and denotes it as a sequence of 0 and 1, separated by a binary point, where 1 indicates a power of 2 that appears in the sum; the exponent is determined by the place of this 1: the nonnegative exponents are the rank of the 1 on the left of the point (starting from 0), and ...

  6. Change of variables - Wikipedia

    en.wikipedia.org/wiki/Change_of_variables

    Difficult integrals may also be solved by simplifying the integral using a change of variables given by the corresponding Jacobian matrix and determinant. [1] Using the Jacobian determinant and the corresponding change of variable that it gives is the basis of coordinate systems such as polar, cylindrical, and spherical coordinate systems.

  7. Experimental uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Experimental_uncertainty...

    (1) The Type I bias equations 1.1 and 1.2 are not affected by the sample size n. (2) Eq(1.4) is a re-arrangement of the second term in Eq(1.3). (3) The Type II bias and the variance and standard deviation all decrease with increasing sample size, and they also decrease, for a given sample size, when x's standard deviation σ becomes small ...

  8. Finite difference - Wikipedia

    en.wikipedia.org/wiki/Finite_difference

    In an analogous way, one can obtain finite difference approximations to higher order derivatives and differential operators. For example, by using the above central difference formula for f ′(x + ⁠ h / 2 ⁠) and f ′(x − ⁠ h / 2 ⁠) and applying a central difference formula for the derivative of f ′ at x, we obtain the central difference approximation of the second derivative of f:

  9. Exponential integral - Wikipedia

    en.wikipedia.org/wiki/Exponential_integral

    For real non-zero values of x, the exponential integral Ei(x) is defined as ⁡ = =. The Risch algorithm shows that Ei is not an elementary function.The definition above can be used for positive values of x, but the integral has to be understood in terms of the Cauchy principal value due to the singularity of the integrand at zero.

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