Taylor Polynomial for Square Root Function at x = 100

In summary, the Taylor Polynomial for f(x) = \sqrt(x) of degree 2 in x = 100 yields 10+50(1)-\frac{1}{8000}(1)^2=60-\frac{1}{8000}. The approximation in procent is 9.949875.
  • #1
Math_Frank
27
0
Hi Guys,

I have an assigment which I would very much appreciate if You would tell if I have done it correct :)

Use the Taylor Polynomial for [tex]f(x) = \sqrt(x)[/tex] of degree 2 in x = 100. To the the approximation for the value [tex]\sqrt(99)[/tex]

First I find the Taylor polynomial of degree 2.

[tex]T_2(x) = \sqrt(100) + \frac{\frac{1}{(2) \sqrt(100)}}{1!} (x-100) \frac{\frac{1}{(4) (100)^{3/2}}}{2!} (x-100)^2[/tex]
 
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  • #3
benorin said:
now plug-in x=99.

Hello Benorin,

I plugin x = 99 and get

[tex]T_2(99) = \frac{1599999}{160000}[/tex]
 
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  • #4
Only plug-in 99 where you see an x, i.e.

[tex]T_2(99) = \sqrt(100) + \frac{\frac{1}{(2) \sqrt(100)}}{1!} (99-100) -\frac{\frac{1}{(4) (100)^{3/2}}}{2!} (99-100)^2 = 10+50(1)-\frac{1}{8000}(1)^2=60-\frac{1}{8000}=59.999875[/tex]
 
  • #5
benorin said:
Only plug-in 99 where you see an x, i.e.

[tex]T_2(99) = \sqrt(100) + \frac{\frac{1}{(2) \sqrt(100)}}{1!} (99-100) -\frac{\frac{1}{(4) (100)^{3/2}}}{2!} (99-100)^2 = 10+50(1)-\frac{1}{8000}(1)^2=60-\frac{1}{8000}=59.999875[/tex]

The result You get there 59.999875 is that the approximation in procent?

/Frank
 
  • #6
59.99.. obviously cannot be correct. It's not anywhere close to root of 99.

From the formula above I see 10 - 1/20 - 1/8000 = 9.949875. Which squared equals about 99.0000125..., what is pretty close.
 
  • #7
Hello Again Benorin,

So the conclusion is that [tex]T_2(99)[/tex] cannot be used to find the approximation for 99?

If I insert 99 into the polymial I get [tex]T_2(99) = 9,999996875[/tex]

which squared gives 99,9999

Is that wrong?

/Frank
vladb said:
59.99.. obviously cannot be correct. It's not anywhere close to root of 99.

From the formula above I see 10 - 1/20 - 1/8000 = 9.949875. Which squared equals about 99.0000125..., what is pretty close.
 
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  • #8
benorin said:
Only plug-in 99 where you see an x, i.e.

[tex]T_2(99) = \sqrt(100) + \frac{\frac{1}{(2) \sqrt(100)}}{1!} (99-100) -\frac{\frac{1}{(4) (100)^{3/2}}}{2!} (99-100)^2 = 10+\frac{1}{20}(-1)-\frac{1}{8000}(1)^2=10-\frac{1}{20}-\frac{1}{8000}=9.949875[/tex]

My bad, my post should have read as above, and note that the actual value is closer to

[tex]\sqrt{99}\approx 9.9498743710661995473447982100121[/tex]
 
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  • #9
Note that your original formula is wrong, because instead of adding up the terms (with derivatives of various order) you multiply them.
The formula posted by Benorin (4th post) is the correct one, which will give 10 - 1/20 - 1/8000.

To Benorin: < deleted :) >
 
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FAQ: Taylor Polynomial for Square Root Function at x = 100

What is a Taylor Polynomial?

A Taylor Polynomial is a mathematical expression that approximates a function by using a finite number of terms from its Taylor series. This allows us to approximate functions that are difficult to calculate exactly.

How is a Taylor Polynomial calculated?

To calculate a Taylor Polynomial, we need to find the function's derivatives at a given point. These derivatives are then used to construct the polynomial by plugging them into the formula for the Taylor series.

What is the purpose of using a Taylor Polynomial?

The purpose of using a Taylor Polynomial is to approximate a function and make it easier to work with. It allows us to estimate values of the function at certain points, even if we cannot calculate the exact value of the function.

What is the difference between a Taylor Polynomial and a Taylor series?

A Taylor Polynomial is a finite sum of terms from a Taylor series, while a Taylor series is an infinite sum of terms. The Taylor Polynomial is a closer approximation to the function at a specific point, while the Taylor series gives an approximation for the function at every point.

Can a Taylor Polynomial perfectly represent a function?

No, a Taylor Polynomial can never perfectly represent a function since it is only an approximation. The accuracy of the approximation depends on the number of terms used in the polynomial, with more terms leading to a better approximation.

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