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  2. Mathematics - Wikipedia

    en.wikipedia.org/wiki/Mathematics

    Variables allow mathematicians to describe the operations that have to be done on the numbers represented using mathematical formulas. [ 44 ] Until the 19th century, algebra consisted mainly of the study of linear equations (presently linear algebra ), and polynomial equations in a single unknown , which were called algebraic equations (a term ...

  3. Pi - Wikipedia

    en.wikipedia.org/wiki/Pi

    t. e. The number π (/ paɪ /; spelled out as " pi ") is a mathematical constant that is the ratio of a circle 's circumference to its diameter, approximately equal to 3.14159. The number π appears in many formulae across mathematics and physics.

  4. SymPy - Wikipedia

    en.wikipedia.org/wiki/SymPy

    The SymPy library is split into a core with many optional modules. Currently, the core of SymPy has around 260,000 lines of code [8] (it also includes a comprehensive set of self-tests: over 100,000 lines in 350 files as of version 0.7.5), and its capabilities include: [4] [5] [9] [10] [11]

  5. Product (mathematics) - Wikipedia

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

    Product (mathematics) In mathematics, a product is the result of multiplication, or an expression that identifies objects (numbers or variables) to be multiplied, called factors. For example, 21 is the product of 3 and 7 (the result of multiplication), and is the product of and (indicating that the two factors should be multiplied together).

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    Therefore, it may not be an appropriate model when one expects a significant fraction of outliers—values that lie many standard deviations away from the mean—and least squares and other statistical inference methods that are optimal for normally distributed variables often become highly unreliable when applied to such data.

  7. Binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Binomial_distribution

    A Binomial distributed random variable X ~ B(n, p) can be considered as the sum of n Bernoulli distributed random variables. So the sum of two Binomial distributed random variable X ~ B(n, p) and Y ~ B(m, p) is equivalent to the sum of n + m Bernoulli distributed random variables, which means Z=X+Y ~ B(n+m, p). This can also be proven directly ...

  8. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    Using the Leibniz formula for determinants, the left-hand side of equation is a polynomial function of the variable λ and the degree of this polynomial is n, the order of the matrix A. Its coefficients depend on the entries of A, except that its term of degree n is always (−1) n λ n. This polynomial is called the characteristic polynomial of A.

  9. Generating function - Wikipedia

    en.wikipedia.org/wiki/Generating_function

    Generating function. In mathematics, a generating function is a representation of an infinite sequence of numbers as the coefficients of a formal power series. Generating functions are often expressed in closed form (rather than as a series), by some expression involving operations on the formal series. There are various types of generating ...