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  2. Null hypothesis - Wikipedia

    en.wikipedia.org/wiki/Null_hypothesis

    A statistical significance test starts with a random sample from a population. If the sample data are consistent with the null hypothesis, then you do not reject the null hypothesis; if the sample data are inconsistent with the null hypothesis, then you reject the null hypothesis and conclude that the alternative hypothesis is true. [3]

  3. Family-wise error rate - Wikipedia

    en.wikipedia.org/wiki/Family-wise_error_rate

    is the number of true null hypotheses, an unknown parameter; is the number of true alternative hypotheses; V is the number of false positives (Type I error) (also called "false discoveries") S is the number of true positives (also called "true discoveries") T is the number of false negatives (Type II error)

  4. Kernel (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(linear_algebra)

    By the above reasoning, the kernel of A is the orthogonal complement to the row space. That is, a vector x lies in the kernel of A, if and only if it is perpendicular to every vector in the row space of A. The dimension of the row space of A is called the rank of A, and the dimension of the kernel of A is called the nullity of A.

  5. Null distribution - Wikipedia

    en.wikipedia.org/wiki/Null_distribution

    Null distribution is a tool scientists often use when conducting experiments. The null distribution is the distribution of two sets of data under a null hypothesis. If the results of the two sets of data are not outside the parameters of the expected results, then the null hypothesis is said to be true. Null and alternative distribution

  6. Rank–nullity theorem - Wikipedia

    en.wikipedia.org/wiki/Rank–nullity_theorem

    Rank–nullity theorem. The rank–nullity theorem is a theorem in linear algebra, which asserts: the number of columns of a matrix M is the sum of the rank of M and the nullity of M; and; the dimension of the domain of a linear transformation f is the sum of the rank of f (the dimension of the image of f) and the nullity of f (the dimension of ...

  7. Referential integrity - Wikipedia

    en.wikipedia.org/wiki/Referential_integrity

    Referential integrity is a property of data stating that all its references are valid. In the context of relational databases , it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute (either in the same or a different relation), then the referenced value must exist.

  8. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    Once y is also eliminated from the third row, the result is a system of linear equations in triangular form, and so the first part of the algorithm is complete. From a computational point of view, it is faster to solve the variables in reverse order, a process known as back-substitution. One sees the solution is z = −1, y = 3, and x = 2. So ...

  9. Missing data - Wikipedia

    en.wikipedia.org/wiki/Missing_data

    In the mathematical field of numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points. In the comparison of two paired samples with missing data, a test statistic that uses all available data without the need for imputation is the partially overlapping samples t-test. [18]