The following table represents the prices of copper futures (in USD) from theperiod of time from XXXXXXXXXXto XXXXXXXXXX, where t is time since XXXXXXXXXXmeasured in weeks) and f(t) is the...


The following table represents the prices of copper futures (in USD) from theperiod of time from 14.06.2020 to 06.06.2021, where t is time since 14.06.2020 (measured in weeks) and f(t) is the corresponding price:














































































t


f(t)



0


2.6655



1


2.7120



2


2.7800



3


2.9255



4


2.9355



5


2.9220



6


2.9110



7


2.8445



8


2.9070



t


f(t)



9


2.9570



10


3.0365



11


3.0810



12


3.0590



13


3.1215



14


2.9785



15


2.9900



16


3.0800



17


3.0720



t


f(t)



18


3.1305



19


3.0565



20


3.1635



21


3.1890



22


3.3125



23


3.4210



24


3.5285



25


3.5340



26


3.6370



t


f(t)



27


3.5675



28


3.5240



29


3.6800



30


3.6070



31


3.6315



32


3.5565



33


3.6265



34


3.7885



35


4.0775



t


f(t)



36


4.0925



37


4.0755



38


4.1400



39


4.1130



40


4.0680



41


3.9905



42


4.0400



43


4.1680



44


4.3360



t


f(t)



45


4.4680



46


4.7485



47


4.6545



48


4.4810



49


4.6775



50


4.5290



51


4.5375







Let L(x) be the third Lagrange polynomial for the function f(x) with the nodes


X0 = 0,   x1 = 12, x2 = 42,  x3 = 50.


(i) Find the value L(22) of the Lagrange polynomial at x = 22 and the relative error in the approximation f(22) ≈ L(22):


(ii) Find the value L(51) of the Lagrange polynomial at x = 51 and the relative error in the approximation f(51) ≈ L(51):


All calculations are to be carried out in the FPA5,
and the computational results are to be presented in two standard output tables for themethod of the form






































xk



x0



x1





xn





yk= f(xk)



y0



y1





yn





Lk(x)



L0(x)



L1(x)





Ln(x)



Total, L(x)



ykLk(x)



y0L0(x)



y1L1(x)





ynLn(x)



kykLk(x)




Jun 05, 2022
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