Depth, h(m) Temperature, T (◦C) 0 19.1 −1 19.1 −2 19 −3 18.8 −4 18.7 −5 18.3 −6 18.2 −7 17.6 −8 11.7 −9 9.9 −10 9.1   We can write temperature as a function of the depth: T(h).   Use appropriate data and divided difference algorithm to construct Newton’s interpolating polynomials of degree one (name it by T1(h)) to approximate the value of the temperature at h = −5 m.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
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  1. To maximize a catch of bass in lake, it is suggested to throw the fishing line to the depth of the The characteristic feature of this area is the sudden change in temperature. The depth vs. temperature data for a lake is given in the table.

 

Depth, h(m)

Temperature, T (C)

0

19.1

1

19.1

2

19

3

18.8

4

18.7

5

18.3

6

18.2

7

17.6

8

11.7

9

9.9

10

9.1

 

We can write temperature as a function of the depth: T(h).

 

  1. Use appropriate data and divided difference algorithm to construct Newton’s interpolating polynomials of degree one (name it by T1(h)) to approximate the value of the temperature at h = 5 m.

 

  1. Use appropriate data and divided difference algorithm to construct Newton’s interpolating polynomials of degree two (name it by T2(h)) to approximate the value of the temperature at h = 8.5

 

  1. Use appropriate data and divided difference algorithm to construct Newton’s interpolating polynomials of degree three (name it by T3(h)) to approximate the value of the temperature at h = 8.5
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