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  2. Second normal form - Wikipedia

    en.wikipedia.org/wiki/Second_normal_form

    Second normal form (2NF), in database normalization, is a normal form. A relation is in the second normal form if it fulfills the following two requirements: A relation is in the second normal form if it fulfills the following two requirements:

  3. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Codd introduced the concept of normalization and what is now known as the first normal form (1NF) in 1970. [4] Codd went on to define the second normal form (2NF) and third normal form (3NF) in 1971, [5] and Codd and Raymond F. Boyce defined the Boyce–Codd normal form (BCNF) in 1974. [6]

  4. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    However, the first form keeps better numerical accuracy for large values of x, because squares of differences between x and x leads to less round-off than the differences between the much larger numbers Σ(x 2) and (Σx) 2. The built-in Excel function STDEVP, however, uses the less accurate formulation because it is faster computationally. [5]

  5. First normal form - Wikipedia

    en.wikipedia.org/wiki/First_normal_form

    First normal form (1NF) is a property of a relation in a relational database. A relation is in first normal form if and only if no attribute domain has relations as elements. [ 1 ] Or more informally, that no table column can have tables as values.

  6. Normalization (statistics) - Wikipedia

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

    This can be generalized to restrict the range of values in the dataset between any arbitrary points and , using for example ′ = + (). Note that some other ratios, such as the variance-to-mean ratio ( σ 2 μ ) {\textstyle \left({\frac {\sigma ^{2}}{\mu }}\right)} , are also done for normalization, but are not nondimensional: the units do not ...

  7. Wald–Wolfowitz runs test - Wikipedia

    en.wikipedia.org/wiki/Wald–Wolfowitz_runs_test

    If we sample longer and longer sequences, with + / = for some fixed (,), then (/) converges in distribution to the normal distribution with mean 0 and variance 1. Proof sketch. It suffices to prove the asymptotic normality of the sequence ∑ i = 1 N − 1 x i x i + 1 {\displaystyle \sum _{i=1}^{N-1}x_{i}x_{i+1}} , which can be proven by a ...

  8. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The moment generating function of a real random variable ⁠ ⁠ is the expected value of , as a function of the real parameter ⁠ ⁠. For a normal distribution with density ⁠ f {\displaystyle f} ⁠ , mean ⁠ μ {\displaystyle \mu } ⁠ and variance σ 2 {\textstyle \sigma ^{2}} , the moment generating function exists and is equal to

  9. Boyce–Codd normal form - Wikipedia

    en.wikipedia.org/wiki/Boyce–Codd_normal_form

    If a relational schema is in BCNF, then all redundancy based on functional dependency has been removed, [4] although other types of redundancy may still exist. A relational schema R is in Boyce–Codd normal form if and only if for every one of its functional dependencies X → Y, at least one of the following conditions hold: [5]