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4.5: Linear Approximations, Differentials and Newton’s Method

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1 4.5: Linear Approximations, Differentials and Newton’s Method
Greg Kelly, Hanford High School, Richland, Washington

2 For any function f (x), the tangent is a close approximation of the function for some small distance from the tangent point. We call the equation of the tangent the linearization of the function.

3 Start with the point/slope equation:
linearization of f at a is the standard linear approximation of f at a. The linearization is the equation of the tangent line, and you can use the old formulas if you like.

4 dy can be considered a very small change in y.
Differentials: When we first started to talk about derivatives, we said that becomes when the change in x and change in y become very small. dy can be considered a very small change in y. dx can be considered a very small change in x.

5 Let be a differentiable function.
The differential is an independent variable. The differential is:

6 Example: Consider a circle of radius 10. If the radius increases by 0
Example: Consider a circle of radius 10. If the radius increases by 0.1, approximately how much will the area change? dA = 2π r dr very small change in r very small change in A (approximate change in area)

7 (approximate change in area)
Compare to actual change: New area: Old area:

8 Newton’s Method Finding a root for:
We will use Newton’s Method to find the root between 2 and 3.

9 Guess: (not drawn to scale) (new guess)

10 Guess: (new guess)

11 Guess: (new guess)

12 Guess: Amazingly close to zero! This is Newton’s Method of finding roots. It is an example of an algorithm (a specific set of computational steps.) It is sometimes called the Newton-Raphson method This is a recursive algorithm because a set of steps are repeated with the previous answer put in the next repetition. Each repetition is called is called an iteration.

13 Guess: Newton’s Method: Amazingly close to zero! This is Newton’s Method of finding roots. It is an example of an algorithm (a specific set of computational steps.) It is sometimes called the Newton-Raphson method This is a recursive algorithm because a set of steps are repeated with the previous answer put in the next repetition. Each repetition is called is called an iteration.

14 Find where crosses

15 p There are some limitations to Newton’s method: Wrong root found
Looking for this root. Bad guess. Wrong root found Failure to converge p

16 George W. Bush visits Algeria
George W. Bush visits Algeria. As part of his program, he delivers a speech to the Algerian people: "You know, I regret that I have to give this speech in English. I would very much prefer to talk to you in your own language. But unfortunately, I was never good at algebra..."

17 Important linearizations for x near zero:


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