Don't understand the taylor expansion?

In summary, the conversation is about trying to understand Taylor series and where it belongs in terms of math forums. The main point is that understanding calculus is necessary to understand Taylor series and it involves extrapolating derivatives to predict the behavior of a function at different points.
  • #1
Lengalicious
163
0
Not sure under which forum this should have gone under, anyway can someone who really understands it explain it to me in as simple terms as they can, from what I'm getting its approximates something for a function or something? No idea.
 
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  • #3
Lengalicious said:
Not sure under which forum this should have gone under, anyway can someone who really understands it explain it to me in as simple terms as they can, from what I'm getting its approximates something for a function or something? No idea.
It belongs in either general math or calculus. To understand Taylor series you need to understand calculus at least on an elementary level. It is very hard to explain otherwise.
 
  • #4
A Taylor series basically calculates a bunch of derivatives at some point in a parameter space and then extrapolates them to other points close to the initial point in the space.

The more derivatives you figure out the better you can predict what some function (of which said derivatives are taken) will be at some distance from the initial point.

Claude.
 
  • #5


Sure, I'd be happy to explain the concept of Taylor expansion to you. Taylor expansion, also known as Taylor series, is a mathematical tool used to approximate a function using a series of terms. It is named after the mathematician Brook Taylor who first described it in the 18th century.

In simple terms, Taylor expansion allows us to represent a complicated function as a sum of simpler functions, known as Taylor polynomials. These polynomials are built around a specific point, called the center, and the more terms we include in the expansion, the closer the approximation will be to the actual function.

This tool is particularly useful in situations where the function is too complicated to be easily evaluated or when we need to approximate a value that is not explicitly given. For example, if you want to know the value of a function at a certain point but only have information about the function at a nearby point, Taylor expansion can be used to approximate the value at the desired point.

I hope this explanation helps you understand the concept of Taylor expansion better. Please let me know if you have any further questions.
 

1. What is the taylor expansion and why is it important in science?

The taylor expansion is a mathematical technique used to approximate a function using a series of polynomial terms. It is important in science because it allows us to represent complex functions in a simpler form, making them easier to analyze and manipulate.

2. How is the taylor expansion calculated?

The taylor expansion is calculated using the function's derivatives at a specific point. Each derivative is multiplied by a corresponding term in the series, and the terms are added together to form the final approximation.

3. What is the purpose of using a taylor expansion instead of the original function?

The taylor expansion is often used to approximate a function at a specific point, especially when the original function is difficult to evaluate or integrate. It also allows us to estimate the behavior of a function near a specific point without having to evaluate the function at multiple points.

4. Can the taylor expansion be used for any function?

No, the taylor expansion can only be used for functions that are infinitely differentiable, meaning they have derivatives of all orders at every point in their domain.

5. What are some common applications of the taylor expansion in science?

The taylor expansion is commonly used in physics and engineering to approximate the motion of objects, in chemistry to model chemical reactions, and in economics to analyze financial data. It is also used in computer science to develop algorithms and in statistics to fit data to a model.

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