I recently came across the following computational trick: to estimate , use
,
where is the closest perfect square to
. For example,
.
I had not seen this trick before — at least stated in these terms — and I’m definitely not a fan of computational tricks without an explanation. In this case, the approximation is a straightforward consequence of a technique we teach in calculus. If , then
, so that
. Since
, the equation of the tangent line to
at
is
.
The key observation is that, for , the graph of
will be very close indeed to the graph of
. In Calculus I, this is sometimes called the linearization of
at
. In Calculus II, we observe that these are the first two terms in the Taylor series expansion of
about
.
For the problem at hand, if , then
if is close to zero. Therefore, if
is a perfect square close to
so that the relative difference
is small, then
.
One more thought: All of the above might be a bit much to swallow for a talented but young student who has not yet learned calculus. So here’s another heuristic explanation that does not require calculus: if , then the geometric mean
will be approximately equal to the arithmetic mean
. That is,
,
so that
.