Section 2.4: The Precise Definition of a Limit

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Section 2.4: The Precise Definition of a Limit In the previous sections, we examined the idea of a it. However, the definitions we gave were me intuitive as opposed to precise. In mathematics, in der to prove results, we cannot base our findings on intuitive definitions, but rather fmal definitions. Therefe, we need to come up with a precise fmal definition of exactly what we mean by a it. 1. An Example Befe we try to fmalize the definition of a it, we start with an example. Example 1.1. Suppose that f(x) = x 2. Then we know that x2 = 4. With our previous definition of a it, this means that once x is close enough to 2 we can guarantee that f(x) is within a fixed distance of 4. Therefe, we can consider how close x needs to be to 2 in der to guarantee that f(x) is within 0.1 of 4. Specifically, we want to find the conditions on x which guarantee that This means: and x 2 4 < 0.1 0.1 < x 2 4 < 0.1 3.9 < x 2 < 4.1 1.975 < x < 2.025 This means f any x in the interval (1.975, 2.025), we can guarantee that f(x) 4 < 0.1. Alternatively, this means if then x 2 < 0.025 f(x) 4 < 0.1 ote that we could repeat this process f any choice of a distance of f(x) from 4. 2. The Fmal Definition We shall now attempt to fmalize the definition of a it. First, we recall again the previous definition we gave f a it: 1

2 Definition 2.1. We write f(x) = L and say the it of f(x) as x approaches a equals L if as we take x values closer and closer to a (from either side), the value of f(x) gets closer and closer to L without taking x = a. We need to make the terms as we take x values closer and closer to a (from either side) and the value of f(x) gets closer and closer to L me precise. To do this, we make a couple of observations: F a fixed a, to guarantee that a number x is within a distance δ of a (from either side), the inequality x a < δ must be satisfied. To say that the values of f(x) gets closer and closer to L means that once x is close enough to a, we can guarantee that f(x) is within a fixed distance of L. Specifically, f any fixed distance ε, once x is close enough to a, we can guarantee f(x) L < ε. Putting these two observations together, and noting our previous example, we get the following definition: Definition 2.2. We say that the it of f(x) approaches L as x approaches a and write f(x) = L if f any ε > 0, there exists a δ > 0 such that x a < δ guarantees that f(x) L < ε. Graphically, if f(x) = L then f any choice of interval around y = L on the x-axis of radius ε > 0, there exists an interval around x = a of radius δ > 0 such that on the window x = a δ, x = a + δ, y = L ε, y = L + ε, the graph of f(x) has the following properties: It enters and leaves the screen through the top bottom of the calculat It never leaves and reenters the screen E L 01 01 D a

We illustrate with me examples. Example 2.3. (i) We know that f(x) = 5 where f(x) = 2x + 1. Find the value of δ which guarantees that f(x) 5 < 0.2. We want f(x) 5 = (2x + 1) 5 = 2x 4 < 0.2. This means.2 < 2x 4 < 0.2 3.8 < 2x < 4.2, 1.9 < x < 2.1. Thus we have 0.1 < x 2 < 0.1 x 2 < 0.1. This means that if we choose δ = 0.1, then we can guarantee that f(x) 4 < 0.2. (ii) Prove that f(x) = 5. This is similar to the previous example, but instead of determining a specific value of δ f a fixed value of ε, we need to determine a value of δ f any value of ε. Specifically, we want the value of δ that f(x) 5 = (2x + 1) 5 = 2x 4 < ε f any chosen value of ε. This means ε < 2x 4 < ε 4 ε < 2x < 4 + ε, 2 ε 2 < x < 2 + ε 2. Thus we have ε 2 < x 2 < ε 2 x 2 < ε 2. This means that if we choose δ = ε/2, then we can guarantee that f(x) 4 < ε and thus f(x) = 5. 3

4 3. Left Hand Limits, Right Hand Limits and Infinite Limits Since we have a fmal definition f a it, we can modify it f other types of it. Specifically, we have the following generalized definitions f one-sided its. Definition 3.1. (i) We say that the it of f(x) approaches L as x approaches a from the righta hand side and write f(x) = L + if f any ε > 0, there exists a δ > 0 such that a x < δ guarantees that f(x) L < ε. (ii) We say that the it of f(x) approaches L as x approaches a from the righta hand side and write f(x) = L if f any ε > 0, there exists a δ > 0 such that x a < δ guarantees that f(x) L < ε. We al have the following generalized definitions f infinite its. Definition 3.2. (i) We say that the it of f(x) approaches as x approaches a and write f(x) = if f any number M > 0, there exists a δ > 0 such that x a < δ guarantees that f(x) > M. (ii) We say that the it of f(x) approaches as x approaches a and write f(x) = if f any number M < 0, there exists a δ > 0 such that x a < δ guarantees that f(x) < M. We consider an example to illustrate how to use these definitions. Example 3.3. Show that x 0 1 x 2 =. Let M be any negative number ( M = f me positive number ). Then implies 1 x 2 < M = < 1 x 2 x 2 < 1

5 which holds true provided 1 < x < 1. This means provided x < 1 then 1 x 2 < M. Since this wks f any value of M, it follows that x 0 1 x 2 =. Some additional problems to test your skills: Example 3.4. (i) Find the value of δ required to guarantee that f f(x) = 4x 4, x 3 < δ implies f(x) 16 < 0.01. (ii) Prove that (4x + 4) = 16. x 3