Which is a Better Approximation: (1+x)^n or e^nx? How to Show?

In summary, the approximation (1+x)n is better than (1+x)n when x is close to 0, but worse when x is far from 0.
  • #1
Harrisonized
208
0
This isn't a coursework problem. I'm on winter break.

Homework Statement



A common approximation used in physics is:

(1+x)n ≈ 1+nx for small x

This implies that

lim(x→0) (1+x)n = lim(x→0) 1+nx

which is a true statement. However,

lim(x→0) (1+x)n
= lim(x→0) [(1+x)1/x]xn
= lim(x→0) exn

This leads to the fact that

(1+x)n ≈ exn for small x

The question is: which one is a better approximation, and how do I show it?

The Attempt at a Solution



Compute the error terms.

E1 = (1+x)n - (1+nx)
E2 = (1+x)n - exn

They intersect at E1 = E2, or at

1+nx = exn

I'm not sure how to go from here. I'm pretty sure that x can't be isolated. However, since exn is always positive, I think the only root is at x=0. Wolfram gives a funny answer though. If anyone would like to explain Wolfram's answer, please do.

http://www.wolframalpha.com/input/?i=1%2Bnx+%3D+e^%28nx%29

Assuming positive n, for a large x, exn is a worse approximation for the function. Since exn grows much faster than (1+nx), exn is always a worse approximation than (1+nx).

Assuming negative n, for a large x, exn is a worse approximation for the function. Since exn doesn't grow as quickly as (1+nx) (it levels off), exn is always a better approximation than (1+nx).

Or it may just be the case that 1+nx is always a better approximation, since it's more commonly used.
 
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  • #2
You can surely do something with

[tex](1+x)^n-(1+nx)[/tex]

Work it out with the binomial theorem.

As for

[tex]e^{nx}-(1+nx)[/tex]

consider the Taylor series of the exponential function.
 
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  • #3
(1+x)2 = 1+2x+x2
(1+x)3 = 1+3x+3x2+x3
(1+x)4 = 1+4x+6x2+4x3+x4

enx = 1+nx+(nx)2/2!+(nx)3/3!+...

So enx is always a worse approximation?
 
  • #4
Harrisonized said:
(1+x)2 = 1+2x+x2
(1+x)3 = 1+3x+3x2+x3
(1+x)4 = 1+4x+6x2+4x3+x4

Don't you know the formula for [itex](1+x)^n[/itex]. Search "binomial theorem".

enx = 1+nx+(nx)2/2!+(nx)3/3!+...

So enx is always a worse approximation?

How did you conclude this??
 
  • #5
micromass said:
Don't you know the formula for [itex](1+x)^n[/itex]. Search "binomial theorem".

I'm pretty sure I expanded those correctly.

micromass said:
How did you conclude this??

(1+x)n ends its series on a magnitude of xn, whereas the Taylor expansion of enx has an infinite series.
 
  • #6
Harrisonized said:
I'm pretty sure I expanded those correctly.

Yes, you did. But you only did it for n=2,3,4. Can't you did it generally.

(1+x)n ends its series on a magnitude of xn, whereas the Taylor expansion of enx has an infinite series.

That doesn't really imply anything.
 
  • #7
micromass said:
Yes, you did. But you only did it for n=2,3,4. Can't you did it generally.

I'm not used to working with nCr notations.

micromass said:
That doesn't really imply anything.

You're right. What kind of test would I use?
 
  • #8
Harrisonized said:
You're right. What kind of test would I use?

First, try to actually calculate

[tex](1+x)^n-(1+nx)[/tex]

and

[tex]e^{nx}-(1+nx)[/tex]

(take n=4 for example), what does that give you??
 
  • #9
(1+x)4-(1+4x) = 6x2+4x3+x4

e4x-(1+4x) = (4x)2/2!+(4x)3/3!+(4x)4/4!...
= 8x2 + 32/3 x3 + 32/3 x4+...

The coefficients of first three terms of e4x-(1+4x) are each greater than the respective the coefficients of (1+x)4-(1+4x).
 
  • #10
Harrisonized said:
(1+x)4-(1+4x) = 6x2+4x3+x4

e4x-(1+4x) = (4x)2/2!+(4x)3/3!+(4x)4/4!...
= 8x2 + 32/3 x3 + 32/3 x4+...

The coefficients of first three terms of e4x-(1+4x) are each greater than the respective the coefficients of (1+x)4-(1+4x).

Indeed. Actually, it is enough to look at the first coefficient. The intuiton is this: if x is close to 0, then [itex]x^3[/itex] will be many times smaller than [itex]x^2[/itex]. So the terms with [itex]x^3,x^4,...[/itex] will be negligible.

So indeed, since 6 is smaller than 8, we gave that the first approximation is better.
 
  • #11
So that means that nC2 < n2/2!, which means (1+nx) is always a better approximation? What if n isn't an integer?
 
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  • #12
Harrisonized said:
So that means that nC2 > n2/2!, which means (1+nx) is always a better approximation? What if n isn't an integer? Can nC2 ≤ n2/2! for some value n? Say, for example, choose n=1. Then 1C2 = 0 < 12/2! = 1/2.

If n is not an integer, then we can not apply the binomial theorem. However, (if |x|<1), we can always find a series representation of [itex](1+x)^n[/itex].

Eventually, it all comes down to

[tex]\frac{n(n-1)}{2}\leq \frac{n^2}{2}[/tex]

which holds always.

However, if n is very large, then the difference between the two is almost negligible.
 
  • #13
Sorry. I made a typo, leading me to bad conclusions. I edited it now. nC2 < n2/2! is always true for n>0. However, I'm not so sure for n<0 and for non-integer n.

How did you conclude that the formula nC2 = n(n-1)/2 generalizes nC2 to all real numbers? How do I show this? Sorry I've never taken an analysis class.
 
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Related to Which is a Better Approximation: (1+x)^n or e^nx? How to Show?

What is approximation comparison?

Approximation comparison is a method used to estimate the value of a quantity by comparing it with a known quantity or a similar quantity that is easier to calculate or measure.

Why is approximation comparison used?

Approximation comparison is used because it is a quick and efficient way to get an estimate of a value without having to perform complex calculations or measurements.

What are the advantages of approximation comparison?

The advantages of approximation comparison include its simplicity, speed, and ability to provide a useful estimate even when exact values are not known or difficult to obtain.

What are the limitations of approximation comparison?

Approximation comparison is limited by the accuracy and reliability of the known quantity or similar quantity used for comparison. It also may not work well for highly complex or non-linear relationships between the quantities being compared.

How is approximation comparison used in scientific research?

Approximation comparison is often used in scientific research to quickly estimate values and trends, identify patterns and relationships, and make predictions. It can also help guide further research by providing a starting point for more precise measurements or calculations.

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