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In mathematics, summation is the addition of a sequence of numbers, called addends or summands; the result is their sum or total.Beside numbers, other types of values can be summed as well: functions, vectors, matrices, polynomials and, in general, elements of any type of mathematical objects on which an operation denoted "+" is defined.
This list of mathematical series contains formulae for finite and infinite sums. It can be used in conjunction with other tools for evaluating sums. Here, is taken to have the value
For example, consider the sum: 2 + 5 + 8 + 11 + 14 = 40 {\displaystyle 2+5+8+11+14=40} This sum can be found quickly by taking the number n of terms being added (here 5), multiplying by the sum of the first and last number in the progression (here 2 + 14 = 16), and dividing by 2:
If () = ([,]) (that is, the infimum of f over [,]), the method is the lower rule and gives a lower Riemann sum or lower Darboux sum. All these Riemann summation methods are among the most basic ways to accomplish numerical integration .
is used for the series, and, if it is convergent, to its sum. This convention is similar to that which is used for addition: a + b denotes the operation of adding a and b as well as the result of this addition, which is called the sum of a and b. Any series that is not convergent is said to be divergent or to diverge.
The formula for an integration by parts is () ′ = [() ()] ′ ().. Beside the boundary conditions, we notice that the first integral contains two multiplied functions, one which is integrated in the final integral (′ becomes ) and one which is differentiated (becomes ′).
The technique of the previous example may also be applied to other Dirichlet series. If a n = μ ( n ) {\displaystyle a_{n}=\mu (n)} is the Möbius function and ϕ ( x ) = x − s {\displaystyle \phi (x)=x^{-s}} , then A ( x ) = M ( x ) = ∑ n ≤ x μ ( n ) {\displaystyle A(x)=M(x)=\sum _{n\leq x}\mu (n)} is Mertens function and
For example, if the summands are uncorrelated random numbers with zero mean, the sum is a random walk, and the condition number will grow proportional to . On the other hand, for random inputs with nonzero mean the condition number asymptotes to a finite constant as n → ∞ {\displaystyle n\to \infty } .