I always enjoy finding new ways of doing things. I was reading Henle/Kleinberg's Infinitesimal Calculus, which is a great book. It has, throughout the book, a main text and a side-text. The side-text is infinitely more interesting than the main text.
Anyway, on pages 65-66, it gives a method for finding the slope of y = x^2 at a specific point, let's say its at (2,4). The way you do it is kind of strange, but it seems to work. You start by defining a line to intercept the equation:
y = mx + b
Now, we don't know what m and b are, but we *do* know what x and y are. Therefore,
4 = 2m + b
We don't really care about b in the long run, so we want to find an equation for b to remove it from the mix:
b = 4 - 2m
Now our equation for the line becomes:
y = mx + 4 - 2m
Interestingly, we actually have a value for y - y = x^2, so this becomes:
x^2 = mx + 4 -2m
We can rearrange this into quadratic form with:
x^2 - mx + (2m - 4) = 0
Using the quadratic formula, we can do:
x = (m +- sqrt(m^2 - 4(2m - 4))) / 2
x = (m +- sqrt(m^2 - 8m + 16)) / 2
x = (m +- sqrt((m - 4)^2)) / 2
x = (m +- (m - 4)) / 2
Now, we want to take the "+" side of the "+-" since we are solving for "m". Otherwise, we will lose "m". Therefore, this becomes:
x = (2m - 4) / 2
x = m - 2
So, at the point we are looking at, what is the value of x? At (2, 4), x is 2. Therefore
2 = m - 2
m = 4
Therefore, the slope at (2, 4) is 4.
Interestingly, we can also generalize this to get the full derivative for y = x^2. To do this, we will introduce the variables p and q to be the specific x and y values at a specific point. Therefore, the slope at (p, q) for y = x^2 is:
y = mx + b, therefore q = pm + b, therefore b = q - pm
q = p^2, therefore b = p^2 - pm
y = mx + p^2 - pm
y = x^2, therefore:
x^2 = mx + p^2 - pm
x^2 - mx + (pm - p^2) = 0
x = (m +- sqrt(m^2 - 4(pm - p^2)))/2
x = (m +- sqrt(m^2 - 4pm + 4p^2))/2
x = (m +- sqrt((m - 2p)^2))/2
x = (m +- (m - 2p))/2
x = (2m - 2p) / 2
x = m - p
m = x + p
Since p = x, this gives
m = x + x = 2x, which is the derivative of x^2
I don't know how many classes of functions you can do this successfully for, but I imagine it should cover quadratics at least.