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  2. Maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Maximum_and_minimum

    If the domain X is a metric space, then f is said to have a local (or relative) maximum point at the point x ∗, if there exists some ε > 0 such that f(x ∗) ≥ f(x) for all x in X within distance ε of x ∗. Similarly, the function has a local minimum point at x ∗, if f(x ∗) ≤ f(x) for all x in X within distance ε of x ∗.

  3. Contrast (statistics) - Wikipedia

    en.wikipedia.org/wiki/Contrast_(statistics)

    A contrast is defined as the sum of each group mean multiplied by a coefficient for each group (i.e., a signed number, c j). [10] In equation form, = ¯ + ¯ + + ¯ ¯, where L is the weighted sum of group means, the c j coefficients represent the assigned weights of the means (these must sum to 0 for orthogonal contrasts), and ¯ j represents the group means. [8]

  4. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    Notice that the point estimator and the estimated variance are the same as those for a single pairwise comparison. The only difference between the confidence limits for simultaneous comparisons and those for a single comparison is the multiple of the estimated standard deviation.

  5. Critical point (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Critical_point_(mathematics)

    A critical point of a function of a single real variable, f (x), is a value x 0 in the domain of f where f is not differentiable or its derivative is 0 (i.e. ′ =). [2] A critical value is the image under f of a critical point.

  6. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Similarity between two data points. Image shows the path of calculation when using the Euclidean distance formula. There are many various options available when it comes to finding similarity between two data points, some of which are a combination of other similarity methods.

  7. Differential calculus - Wikipedia

    en.wikipedia.org/wiki/Differential_calculus

    In higher dimensions, a critical point of a scalar valued function is a point at which the gradient is zero. The second derivative test can still be used to analyse critical points by considering the eigenvalues of the Hessian matrix of second partial derivatives of the function at the critical point. If all of the eigenvalues are positive ...

  8. Duncan's new multiple range test - Wikipedia

    en.wikipedia.org/wiki/Duncan's_new_multiple_range...

    The new multiple range test proposed by Duncan makes use of special protection levels based upon degrees of freedom.Let , = be the protection level for testing the significance of a difference between two means; that is, the probability that a significant difference between two means will not be found if the population means are equal.

  9. Minimum distance - Wikipedia

    en.wikipedia.org/wiki/Minimum_distance

    Closest pair of points problem, the algorithmic problem of finding two points that have the minimum distance among a larger set of points; Euclidean distance, the minimum length of any curve between two points in the plane; Shortest path problem, the minimum length of a path between two points in a graph