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  2. Like terms - Wikipedia

    en.wikipedia.org/wiki/Like_terms

    The known values assigned to the unlike part of two or more terms are called coefficients. As this example shows, when like terms exist in an expression, they may be combined by adding or subtracting (whatever the expression indicates) the coefficients, and maintaining the common factor of both terms.

  3. Multivalued function - Wikipedia

    en.wikipedia.org/wiki/Multivalued_function

    In mathematics, a multivalued function, [1] multiple-valued function, [2] many-valued function, [3] or multifunction, [4] is a function that has two or more values in its range for at least one point in its domain. [5]

  4. Valuation using multiples - Wikipedia

    en.wikipedia.org/wiki/Valuation_using_multiples

    A valuation multiple [1] is simply an expression of market value of an asset relative to a key statistic that is assumed to relate to that value. To be useful, that statistic – whether earnings, cash flow or some other measure – must bear a logical relationship to the market value observed; to be seen, in fact, as the driver of that market value.

  5. Like - Wikipedia

    en.wikipedia.org/wiki/Like

    Like can be used as a noun meaning "preference" or "kind". Examples: She had many likes and dislikes. We'll never see the like again. When used specifically on social media, it can refer to interactions with content posted by a user, commonly referred to as "likes" on websites such as Twitter or Instagram.

  6. Assignment (computer science) - Wikipedia

    en.wikipedia.org/wiki/Assignment_(computer_science)

    Functional programming languages that use single assignment include Clojure (for data structures, not vars), Erlang (it accepts multiple assignment if the values are equal, in contrast to Haskell), F#, Haskell, JavaScript (for constants), Lava, OCaml, Oz (for dataflow variables, not cells), Racket (for some data structures like lists, not ...

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  9. Omnibus test - Wikipedia

    en.wikipedia.org/wiki/Omnibus_test

    In multiple regression, the omnibus test is an ANOVA F test on all the coefficients, that is equivalent to the multiple correlations R Square F test. The omnibus F test is an overall test that examines model fit, thus failure to reject the null hypothesis implies that the suggested linear model is not significantly suitable to the data.