Alternating series test
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In mathematical analysis, the alternating series test is the method used to show that an alternating series is convergent when its terms (1) decrease in absolute value, and (2) approach zero in the limit. The test was used by Gottfried Leibniz and is sometimes known as Leibniz's test, Leibniz's rule, or the Leibniz criterion. The test is only sufficient, not necessary, so some convergent alternating series may fail the first part of the test.
Alternating series test
A series of the form
where either all an are positive or all an are negative, is called an alternating series.
The alternating series test guarantees that an alternating series converges if the following two conditions are met:
Alternating series estimation theorem
Moreover, let L denote the sum of the series, then the partial sum
approximates L with error bounded by the next omitted term:
Suppose we are given a series of the form , where and for all natural numbers n. (The case follows by taking the negative.)
Proof of the alternating series test
We will prove that both the partial sums with odd number of terms, and with even number of terms, converge to the same number L. Thus the usual partial sum also converges to L.
The odd partial sums decrease monotonically:
while the even partial sums increase monotonically:
both because an decreases monotonically with n.
Moreover, since an are positive, . Thus we can collect these facts to form the following suggestive inequality:
Now, note that a1 − a2 is a lower bound of the monotonically decreasing sequence S2m+1, the monotone convergence theorem then implies that this sequence converges as m approaches infinity. Similarly, the sequence of even partial sum converges too.
Finally, they must converge to the same number because
Call the limit L, then the monotone convergence theorem also tells us extra information that
for any m. This means the partial sums of an alternating series also "alternates" above and below the final limit. More precisely, when there is an odd (even) number of terms, i.e. the last term is a plus (minus) term, then the partial sum is above (below) the final limit.
This understanding leads immediately to an error bound of partial sums, shown below.
Proof of the alternating series estimation theorem
We would like to show by splitting into two cases.
When k = 2m+1, i.e. odd, then
When k = 2m, i.e. even, then
Both cases rely essentially on the last inequality derived in the previous proof.
For a generalization, see Dirichlet's test.
A typical example
An example to show monotonicity is needed
All of the conditions in the test, namely convergence to zero and monotonicity, should be met in order for the conclusion to be true. For example, take the series
The signs are alternating and the terms tend to zero. However, monotonicity is not present and we cannot apply the test. Actually the series is divergent. Indeed, for the partial sum we have which is twice the partial sum of the harmonic series, which is divergent. Hence the original series is divergent.
The test is only sufficient, not necessary
Leibniz test's monotonicity is not a necessary condition, thus the test itself is only sufficient, but not necessary. (The second part of the test is well known necessary condition of convergence for all series.) Examples of nonmonotonic series that converge are and
- ^ In practice, the first few terms may increase. What is important is that for all after some point, because the first finite amount of terms would not change a series' convergence/divergence.
- Konrad Knopp (1956) Infinite Sequences and Series, § 3.4, Dover Publications ISBN 0-486-60153-6
- Konrad Knopp (1990) Theory and Application of Infinite Series, § 15, Dover Publications ISBN 0-486-66165-2
- James Stewart, Daniel Clegg, Saleem Watson (2016) Single Variable Calculus: Early Transcendentals (Instructor's Edition) 9E, Cengage ISBN 978-0-357-02228-9
- E. T. Whittaker & G. N. Watson (1963) A Course in Modern Analysis, 4th edition, §2.3, Cambridge University Press ISBN 0-521-58807-3