Text

Tea Time Numerical Analysis

---

Numerical methods are designed to approximate one thing or another. Sometimes roots, sometimes derivatives or definite integrals, or curves, or solutions of differential equations. As numerical methods produce only approximations to these things, it is important to have some idea how accurate they are. Sometimes accuracy comes down to careful algebraic analysis—sometimes careful analysis of the calculus, and often careful analysis of Taylor polynomials. But before we can tackle those details, we should discuss just how error and, therefore, accuracy are measured. There are two basic measurements of accuracy: absolute error and relative error. Suppose that p is the value we are approximating, and p˜ is an approximation of p. Then p˜ misses the mark by exactly the quantity p˜− p, the so-called error. Of course, p˜ − p will be negative when p˜ misses low. That is, when the approximation p˜ is less than the exact value p. On the other hand, p˜ − p will be positive when p˜ misses high. But generally, we are not concerned with whether our approximation is too high or too low. We just want to know how far off it is. Thus, we most often talk about the absolute error, |p˜ − p|. You might recognize the expression |p˜ − p| as the distance between p˜ and p, and that’s not a bad way to think about absolute error.

---

Availability

No copy data

Detail Information

Series Title

-

Call Number

515 BRI t

Publisher

: Independent., 2016

Collation

-

Language

English

ISBN/ISSN

-

Classification

515

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

-

Subject(s)

Numerical Analysis

Specific Detail Info

-

Statement of Responsibility

Leon Brin

Other Information

Cataloger

Taufik

Source

-

Validator

maya

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment