Analyzing the Setup
Imagine you are standing before a mathematical machine. You feed it a number x from the domain [0,∞), and it spits out a value defined by the function:
Our goal is to understand the nature of this machine: is it one-one? Is it onto? Let's embark on this journey.
The One-One Investigation
To determine if a function is one-one, we need to know if it ever repeats itself. If the machine is always moving in one direction—either strictly increasing or strictly decreasing—it will never return to a previous output.
This is where the power of calculus shines. We calculate the derivative f′(x) using the quotient rule:
f′(x)=(1+x)2(1+x)⋅dxd(x)−x⋅dxd(1+x)
Simplifying this expression, we obtain:
f′(x)=(1+x)21+x−x=(1+x)21
Since (1+x)2 is always positive for x∈[0,∞), our derivative f′(x) is strictly greater than zero. This tells us the function is strictly increasing.
Because it is always climbing, it can never hit the same y-value twice. Thus, we have rigorously proven that the function is one-one.
The Onto Investigation
Now, we turn our attention to the second property: surjectivity, or being "onto." A function is onto if its range—the set of all outputs it actually produces—perfectly matches its codomain.
We are given the codomain [0,∞). Let's find the range. Since the function is strictly increasing, its minimum value occurs at the start of the domain, x=0.
Plugging this in, we find:
So, the range starts at 0. But what is the upper limit? We look at the behavior as x grows infinitely large:
x→∞lim1+xx=x→∞limx1+11=1
The function approaches 1 but never reaches it. Therefore, the range is the interval [0,1).
The Final Verdict
We have discovered that the range is [0,1), while the codomain is [0,∞). Since the range is a proper subset of the codomain, the function fails to be onto.
It covers only a small slice of the target space. We have successfully navigated the problem: the function is one-one because it is strictly increasing, but it is not onto because its range is restricted.
It is a beautiful example of how calculus allows us to map the behavior of functions with absolute precision.