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Ratio, Root, and Alternating Series

The ratio and root tests compare a series to a geometric one through its own internal growth rate — perfect for factorials and powers. The alternating series test then handles signs that flip, certifying convergence even when the absolute series diverges.

The ratio test: comparing to a geometric series

The ratio test measures how fast a series shrinks by watching the ratio of consecutive terms. If |a_{n+1}/a_n| -> L, then sum a_n converges absolutely when L < 1 and diverges when L > 1; at L = 1 the test is inconclusive. The idea is that eventually each term is roughly L times the last, so the series behaves like a geometric series with ratio L.

Why L < 1 forces convergence (the geometric domination).

Suppose |a_(n+1)/a_n| -> L < 1. Pick r with L < r < 1.
Then there is an N so that for all n >= N:
   |a_(n+1)| <= r * |a_n|.
Iterating from N:
   |a_(N+k)| <= r^k * |a_N|.
So the tail sum_{k>=0} |a_(N+k)| <= |a_N| * sum_{k>=0} r^k
                                 = |a_N| / (1 - r)  < infinity.
The tail is dominated by a convergent geometric series,
hence sum |a_n| converges => sum a_n converges absolutely.  QED

Worked example: sum 1/n!  (the series for e minus... well, e).
   a_(n+1)/a_n = n!/(n+1)! = 1/(n+1) -> 0 = L < 1.
   Ratio test: CONVERGES (absolutely).
Pick r between L and 1; the tail is trapped under a geometric series of ratio r.

The root test and its sharper reach

The root test examines the n-th root of the size: if the n-th root of |a_n| has limit superior L, then sum a_n converges absolutely when L < 1 and diverges when L > 1. Using lim sup makes the root test slightly stronger than the ratio test — whenever the ratio test gives an answer, the root test gives the same one, but the root test sometimes works where the ratio test stalls.

Root test on sum n / 2^n.

nth root of |a_n| = (n / 2^n)^(1/n)
                  = n^(1/n) / 2.
Since n^(1/n) -> 1 as n -> infinity,
   lim sup = 1/2 < 1.
Therefore the series CONVERGES absolutely.

Where the root test beats the ratio test:
   a_n = 2^(-n) if n even,  a_n = 3^(-n) if n odd.
   The ratio a_(n+1)/a_n oscillates wildly (no limit) -> ratio test fails.
   But (|a_n|)^(1/n) is either 1/2 or 1/3, so lim sup = 1/2 < 1
   -> root test gives CONVERGES.
n^(1/n) -> 1 is the workhorse limit; lim sup lets the root test handle oscillating ratios.

Alternating signs: the Leibniz test

When the signs flip, cancellation can rescue a series that would diverge in absolute value. The alternating series test (Leibniz) says: if b_n is positive, decreasing, and b_n -> 0, then the alternating series sum (-1)^{n+1} b_n converges. The partial sums hop back and forth in ever-shorter steps, trapping the limit between them.

Alternating harmonic series sum_{n=1}^∞ (-1)^(n+1) / n  =  1 - 1/2 + 1/3 - 1/4 + ...

Check the three hypotheses with b_n = 1/n:
   (1) b_n = 1/n > 0.                            yes
   (2) b_n decreasing: 1/(n+1) < 1/n.            yes
   (3) b_n -> 0.                                 yes
=> the alternating series test gives CONVERGENCE.

Why it works (the nested-interval picture):
   Even partial sums increase:  s_2 < s_4 < s_6 < ...
   Odd partial sums decrease:   s_1 > s_3 > s_5 > ...
   and  s_(2k) < s_(2k+1),  with  s_(2k+1) - s_(2k) = b_(2k+1) -> 0.
   So both subsequences squeeze to one common limit = the sum.

Bonus error bound:  |s - s_N| <= b_(N+1).
   (the tail is no bigger than the first omitted term)
   For this series the sum is ln 2 = 0.6931...
Even and odd partial sums close in like nested intervals; their gap b_(N+1) is the error bound.