First of all I would justify to myself that
y=n.3n is a monotonically increasing function of n. In
other words, as n increases, so does y.
That should allow you to convince yourself that there is exactly
one solution to the equation [because if we try n=0, y is too
small, and if n=10, y is too big].
How do we find n? Well you can just guess, but alternatively, you
can rearrange your equation to:
n=[ln(324)-ln(n)]/ln(3)
We can regard this as an algorithm - the n in the right hand side
is our current estimate, giving the n on the left hand side as
our next estimate.
Starting with n=1 gives our next estimate as 5.26. Repeating with
5.26 gives 3.75 as the third estimate. Repeating a few more times
gives 4.0.
Substituting 4 into the original equation justifies that it is
indeed the solution.
Andre
Andre, why does it work, why would 'n' on the LHS and RHS
would finally be the same?
Can you be sure they finally will?
Yatir
Yatir, the reason it works is because you're clearly just
finding the coordinates of intersection of the line y1
=x and the curve y2 =[ln(324)-ln(x)]/ln(3), we know
that they intersect when their x and y values are equal, here
x=n, so:
n=[ln(324)-ln(n)]/ln(3)
Using the "intersecting graph" analogy, if you set n=1 on the
left hand side, then sub n=1 into the RHS you are finding the y
value (on the curve y2 ) at the point x=1. Crucial
Step: If we now sub this value back into y1 we are
finding the x coordinate in y1 for which y1
= y2 , repeating these two steps of finding
corresponding y and x values are you see that the space bounded
by each iteration pair decreases to zero, and at that point you
have their intersection, because at that point the
corresponding x value is itself, and the corresponding y value is
itself, so no change ensues.
I know the above was a bit muddled, but it'll all become clear
looking at this diagram, the black line shows how the formula
converges on the value.

Note: Not all iterations of this sort converge, we know that this
must, because ln(n) is only real for n> 1, so starting at n=1
ensures we must find the converging value.
Julian
Yatir, I take it you are asking about why this iteration
schema converges.
We started with
n.(3n )=324
and rearranged to give:
[a] n=[ln(324)-ln(n)]/ln(3)
but we could equally have rearranged it to:
[b] n=eln(324)-n.ln(3)
As iteration strategies, [a] converges, but [b] does not. Try
starting with an initial guess of 4.1 and you will see what I
mean. Indeed, the second iteration gives n as 4.005 and 6.318
respectively.
What did I actually do? I guessed that [a] was the way to go,
plugged numbers in a spreadsheet, saw convergence to 4, verified
that it was indeed the solution.
But the real question is, "what distinguishes [a] from [b] such
that one converges and the other does not?"
Thanks Andre, I'm starting to get it, but not yet...
I guess you used taylor's expansion, why did you disregard the
rest of the series?
Yatir
Yatir,
I did indeed use the Taylor expansion. I ignored the rest of the
series because I was only looking at 'sufficiently good initial
guesses' (see last but one para above), i.e. where the distance
from n0 is small.
Indeed, if you put formulae [a] and [b] on a spreadsheet, even
with a starting guess of exactly 4 you find that n diverges for
[b], as machine rounding errors start to build up.
This does nothing to help us prove convergence for [a] when the
initial guesses are a finite distance from n0 . There
may be a more general approach, but the way I would go about it
is to consider
n0 +y=f(f(n0 +x))
for x> 0 and try to show that 0 < y < x (and that y is
diminishing at a sufficiently fast rate that it must converge to
0).
For example, approximate f(n) by g(n)=2 straight lines,
intersecting at (4,4). For n> n0 we require g(n)
< f(n) so a gradient of -0.227 is fine. For n <
n0 we require g(n)> f(n) so a gradient of something
less than 1/-0.227 is fine.
Let me know if you want me to go through the formulae.
Andre