Intermediate Calculus
§2 Remainders and Power Series
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Knowing that a series converges does not tell us its exact sum or how many terms are needed for a useful approximation. Occasionally an exact identity is known, while a similar-looking series may have no immediately useful formula:
Remainder estimates put a guaranteed bound on the part of a series we did not add, so a finite partial sum can still give a controlled approximation.
The same convergence tools also let us study power series, whose terms depend on a variable . A power series may converge for some values of and diverge for others.
Partial sums and remainders
Suppose the convergent series
has th partial sum
The remainder, also called the tail or error, is
The first omitted term is because already includes every term from through .
A useful remainder estimate answers a practical question:
How far can the approximation be from the true sum ?
Integral-test remainder estimate
Suppose is continuous, positive, and decreasing, and
If the corresponding improper integral—an integral whose interval extends to infinity—converges, then the remainder satisfies
The left integral is a lower bound and the right integral is an upper bound.
Why do the bounds begin at different places?
Because is decreasing, its value across a unit interval can be compared with a rectangle whose height is one of the sequence terms.
For the lower bound, pair with the interval immediately to its right:
The remainder begins with , so the first interval is . Adding all those inequalities gives
For the upper bound, pair with the interval immediately to its left:
The interval paired with begins at , so
The shift by is not arbitrary. It comes from aligning the first omitted term with a whole unit interval. Starting at would require extra assumptions; positivity and monotonic decrease alone do not guarantee that comparison.
Using an upper bound to choose
If we want an error smaller than a tolerance , it is enough to choose so that
Then
For a positive series, is positive, so absolute values are optional. They become essential for alternating series.
Alternating-series remainder estimate
Consider an alternating series
where
These are the hypotheses of the Alternating Series Test, abbreviated AST. They guarantee convergence. They also give the stronger error estimate
In words: the approximation error is no larger than the magnitude of the first omitted term.
Example: enough accuracy to round correctly
Consider
Here
The terms are positive, decrease, and approach zero, so the AST and its remainder estimate apply.
Using terms through gives
The first omitted magnitude is
Therefore,
Even after adding or subtracting the maximum possible error, the result still rounds to
to two decimal places.
Stopping at would not be enough. The allowed error interval would contain values that round to and values that round to . A decimal approximation is useful only when the error bound is small enough to settle the requested rounding.
Power series
A power series centered at is an infinite series of the form
Here:
- is the variable;
- is a fixed real number called the center;
- is the coefficient of the th power.
When , this becomes
A power series resembles a polynomial, but a polynomial has only finitely many nonzero terms. A power series may have infinitely many.
Radius and interval of convergence
For a power series
exactly one of the following occurs:
- It converges only at .
- It converges for every real .
- There is a number such that it converges when and diverges when .
The number is the radius of convergence. By convention:
- in the first case;
- in the second case.
If , then
The points and are the endpoints. The radius theorem says nothing about them, so they must be checked separately.
The interval of convergence is the complete set of real -values where the series converges, including whichever endpoints pass their individual tests.
Example: the endpoints behave differently
Find the interval of convergence of
Let
First handle : every term is zero, so the series converges. For , the ratio test gives
The series therefore converges absolutely, meaning that the series of absolute values also converges, when
which means
Now check the endpoints.
At ,
is an alternating harmonic series, so it converges conditionally: it converges, but the corresponding series of absolute values does not.
At ,
is the harmonic series, so it diverges.
Thus the center is , the radius is , and the interval of convergence is
In set-builder notation,
A power series defines a function
Inside its interval of convergence, a power series defines a function:
Sometimes the same function has a simpler formula. The geometric-series identity says
The restriction belongs to the series representation. The formula may be defined at points where the series diverges.
Example: build a representation from a geometric series
Find a power-series representation centered at for
Rewrite the denominator to match :
Use
Then
This converges when
so
At , the resulting terms do not approach zero. Therefore the interval of convergence is
Only even powers appear. For example, the term occurs when
so it comes from , not .
Differentiating and integrating power series
Suppose
has radius of convergence . Inside the open interval
we may differentiate and integrate term by term.
Differentiation
The final line is the same series after reindexing, meaning that the summation label is changed so the exponent is again .
Integration
The differentiated and integrated series have the same radius of convergence . Their behavior at the endpoints may change, so endpoint convergence must still be checked separately.
Example: differentiating the geometric series
Starting from
differentiate both sides:
Example: the exponential series
Define
Term-by-term differentiation gives
Also . The function with
is . Therefore,
for every real .
A practical power-series workflow
To find an interval of convergence:
- Identify the center .
- Apply the ratio or root test to find the condition .
- Convert that inequality into an open interval.
- Test the two endpoints separately.
- Use brackets only for endpoints that actually converge.
To approximate a convergent numerical series:
- Decide which remainder estimate applies.
- Express the bound in terms of .
- Choose so the bound is small enough for the requested accuracy.
- Compute .
- Report the approximation together with its guaranteed error.
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