The position of a particle x(t) on an axis has been monitored. The results are shown in the following table.t x(t)0 41 114 129 12 By the least squares method, fit the data to a quadratic model: Report x(10) Se ha monitoreado la posición de una partícula x(t) sobre un eje. Losresultados se muestran en la siguiente tabla.t0149x(t)4111212Por el método de mínimos cuadrados, ajuste los datos a un modelocuadrático: x(t) = a + bt+ct²Reporte x(10)

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Se ha monitoreado la posición de una partícula x(t) sobre un eje. Los resultados se muestran en la siguiente tabla. t 0 1 4 9 x(t) 4 11 12 12 Por el método de mínimos cuadrados, ajuste los datos a un modelo cuadrático: (t) = a +bt+ct²

Se ha monitoreado la posición de una partícula x(t) sobre un eje. Los resultados se muestran en la siguiente tabla. t 0 1 4 9 x(t) 4 11 12 12 Por el método de mínimos cuadrados, ajuste los datos a un modelo cuadrático: (t) = a +bt+ct²

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Question

The position of a particle x(t) on an axis has been monitored. The results are shown in the following table.

t x(t)
0 4
1 11
4 12
9 12

By the least squares method, fit the data to a quadratic model:

Report x(10)

Se ha monitoreado la posición de una partícula x(t) sobre un eje. Los
resultados se muestran en la siguiente tabla.
t
0
1
4
9
x(t)
4
11
12
12
Por el método de mínimos cuadrados, ajuste los datos a un modelo
cuadrático: x(t) = a + bt+ct²
Reporte x(10)

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