Here's some analysis advice then: (shamelessly nicked from Tim Gowers, a very nice man who's far too clever for my own good)
Let's take f a function from R to R.
What does it mean for f to be continuous? Suppose you think of f as being some kind of measurement, such as velocity as a function of position. Suppose we have some allowable error term, e for the output. We will say f is continuous at x, if given this allowable error e in the ouput, we can find some d (d is a function of x and e, in the sense that it is allowed to depend on x and e) such that if we measure x with an error of at most d, then the error in measuring f will be no more than e.
Formally: given ANY e>0, we can find d(x,e) such that
|x-y| < d (ie measure y within d of x)
then |f(x)-f(y)|<e (f of y is no more than e away from f of x)
example, and good method for doing almost any example:
Suppose for ease we restrict to just the inteval [0,1] take f(x) = x^2
Let e be any positive number, PRETEND we've picked d.
What happens if |x-y| < d?
|x^2 - y^2| = |(x-y)(x+y)| < d |x+y|
now, we've restricted x and y to be in the inteval [0,1], so |x+y| is no more than 2 isn't it?
so |x-y| < d implies |x^2-y^2| < 2d
so if i can go back ab tweak it so that 2d<=e I've cracked it. So I just set d = e/2, and we're there.
This pattern almost always works. Ok, here I made it an easier example because I chose a smaller interval, and so d is just a function of e. Show that if we don't have this restriction it is still continuous. d will need to depend on x as well.
Not sure about the future. Am having midlife crisis about that as we speak.
Poor Juan Pablo, too.