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  2. Pitching moment - Wikipedia

    en.wikipedia.org/wiki/Pitching_moment

    Pitching moment coefficient is fundamental to the definition of aerodynamic center of an airfoil. The aerodynamic center is defined to be the point on the chord line of the airfoil at which the pitching moment coefficient does not vary with angle of attack, [ 1 ] : Section 5.10 or at least does not vary significantly over the operating range of ...

  3. Hilbert series and Hilbert polynomial - Wikipedia

    en.wikipedia.org/wiki/Hilbert_series_and_Hilbert...

    For +, the term of index i in this sum is a polynomial in n of degree with leading coefficient / ()!. This shows that there exists a unique polynomial H P S ( n ) {\displaystyle HP_{S}(n)} with rational coefficients which is equal to H F S ( n ) {\displaystyle HF_{S}(n)} for n large enough.

  4. NuCalc - Wikipedia

    en.wikipedia.org/wiki/NuCalc

    NuCalc, also known as Graphing Calculator, is a computer software tool made by Pacific Tech. It can graph inequalities and vector fields, and functions in two, three, or four dimensions. It supports several different coordinate systems, and can solve equations. It runs on OS X as Graphing Calculator, and on Windows.

  5. Desmos - Wikipedia

    en.wikipedia.org/wiki/Desmos

    In it, geometrical shapes can be made, as well as expressions from the normal graphing calculator, with extra features. [8] In September 2023, Desmos released a beta for a 3D calculator, which added features on top of the 2D calculator, including cross products, partial derivatives and double-variable parametric equations.

  6. Probability plot correlation coefficient plot - Wikipedia

    en.wikipedia.org/wiki/Probability_plot...

    These correlation coefficients are plotted against their corresponding shape parameters. The maximum correlation coefficient corresponds to the optimal value of the shape parameter. For better precision, two iterations of the PPCC plot can be generated; the first is for finding the right neighborhood and the second is for fine tuning the estimate.

  7. Polynomial greatest common divisor - Wikipedia

    en.wikipedia.org/wiki/Polynomial_greatest_common...

    Note: "lc" stands for the leading coefficient, the coefficient of the highest degree of the variable. This algorithm computes not only the greatest common divisor (the last non zero r i), but also all the subresultant polynomials: The remainder r i is the (deg(r i−1) − 1)-th subresultant polynomial.

  8. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    So if two leading coefficients are in the same column, then a row operation of type 3 could be used to make one of those coefficients zero. Then by using the row swapping operation, one can always order the rows so that for every non-zero row, the leading coefficient is to the right of the leading coefficient of the row above.

  9. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/.../Pearson_correlation_coefficient

    Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.