Small confusion about Taylor's remainder

In summary, we have shown that for the given domain, the remainder term Rn(2,x) approaches 0 as n approaches infinity. This means that the Taylor series for the given function will converge to the actual function value as n becomes larger.
  • #1
jegues
1,097
3

Homework Statement



Please assume that what I have for the remainder is correct, and we are on the domain 2 < x < 4 around 2.


Homework Equations





The Attempt at a Solution



[tex] 0 \leq |R_{n} (2,x)| = \frac{1}{n+1} |\frac{x-2}{z_{n}}|^{n+1}[/tex]

Since,

[tex]2 < x < 4[/tex] then, [tex] 0 < x-2 < 2[/tex] and [tex] 0 < \frac{x-2}{z_{n}} < \frac{2}{z_{n}}[/tex]

But, [tex] 2 < z_{n} < 4[/tex]

So we can see that, [tex]\frac{2}{z_{n}} < 1[/tex]

Therefore, [tex]\frac{x-2}{z_{n}} < 1[/tex].


Up to here makes perfect sense. Then he writes the following,

[tex] 0 \leq |R_{n}(2,x)| < \frac{1}{n+1} \cdot (1)^{n+1}[/tex]

I'm confused about the, [tex](1)^{n+1}[/tex] how does he get that term? We showed that,

[tex]\frac{x-2}{z_{n}} < 1[/tex], and if we take that and raise it to any power, say n+1, we will get 0. How does he get that 1 there?

Everything else makes perfect sense, it's just that one part.

Can someone please explain?
 
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  • #2
jegues said:
[tex]\frac{x-2}{z_{n}} < 1[/tex], and if we take that and raise it to any power, say n+1, we will get 0.

You can't raise anything to any power and get zero. When you say we take "that", what are you referring to? 1n+1=1 and [tex] \frac{x-2}{z_n}^{n+1}[/tex] is going to be some small positive number

if a<b then an<bn for any value of n (you can see this by noticing that the derivative of xn is positive so is an increasing function)
 
  • #3
Office_Shredder said:
You can't raise anything to any power and get zero. When you say we take "that", what are you referring to? 1n+1=1 and [tex] \frac{x-2}{z_n}^{n+1}[/tex] is going to be some small positive number

if a<b then an<bn for any value of n (you can see this by noticing that the derivative of xn is positive so is an increasing function)

The part in bold is what I was missing,

Since,

[tex]\frac{x-2}{z_{n}} < 1[/tex] then,

[tex]\left( \frac{x-2}{z_{n}} \right)^{n+1} < 1^{n+1}[/tex]

So we can see that,

[tex] 0 \leq |R_{n}(2,x)| < \frac{1}{n+1} \cdot (1)^{n+1}[/tex]

Applying squeeze theorem,

[tex]lim_{n \rightarrow \infty} 0 = lim_{n \rightarrow \infty} \frac{1}{n+1} = 0 [/tex]

Therefore,

[tex]lim_{n \rightarrow \infty} |R_{n}(2,x)| = 0[/tex]

So it follows that,

[tex]lim_{n \rightarrow \infty} R_{n}(2,x) = 0[/tex] for [tex]2 < x < 4[/tex]
 

FAQ: Small confusion about Taylor's remainder

What is Taylor's remainder?

Taylor's remainder is a mathematical concept used in calculus to estimate the error between a Taylor polynomial and its corresponding function. It is used to determine how accurate the approximation is and can be expressed as a function of the remaining terms in the Taylor series.

Why is Taylor's remainder important?

Taylor's remainder is important because it allows us to approximate a function with a polynomial, which can make complex functions easier to work with. It also helps us determine the accuracy of the approximation and make adjustments if necessary.

How is Taylor's remainder calculated?

Taylor's remainder is calculated using the Lagrange form of the remainder, which is given by the formula R_n(x) = f^(n+1)(c)(x-a)^(n+1)/(n+1)!, where n is the degree of the Taylor polynomial, x is the point at which the approximation is being evaluated, and c is a value between x and a. This formula can be derived using Taylor's theorem.

What is the role of the remainder in Taylor series?

The remainder in a Taylor series represents the error between the Taylor polynomial and the original function. As we include more terms in the series, the remainder decreases and the approximation becomes more accurate. The remainder also helps us determine the maximum error in the approximation.

How can Taylor's remainder be used in real-world applications?

Taylor's remainder can be used in many real-world applications, such as approximating the behavior of physical systems, predicting values of functions, and calculating derivatives and integrals. It is also used in engineering, physics, and economics to simplify complex problems and make calculations more manageable.

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