2. Consider the following data. 1 2 3 4 5 6 7 2 35 150 500 1250 2500 5000 X y Apply the whole modeling process: 1) Consider a modeling assumption and its linearized version Y = AX + B. You may assume that the model is a power function model or an exponential model. 2) Test the suitability of the model assumptions. 3) Develop a model on this basis by determining the model parameters. 4) Test the suitability of your model by comparing it with the original data. Calculate the relative error in % for each data point. Comment on the suitability of your model. 5) Consider the y value at x=2.5. At which x is this value y(x=2.5) increased by 150% according to the model?
2. Consider the following data. 1 2 3 4 5 6 7 2 35 150 500 1250 2500 5000 X y Apply the whole modeling process: 1) Consider a modeling assumption and its linearized version Y = AX + B. You may assume that the model is a power function model or an exponential model. 2) Test the suitability of the model assumptions. 3) Develop a model on this basis by determining the model parameters. 4) Test the suitability of your model by comparing it with the original data. Calculate the relative error in % for each data point. Comment on the suitability of your model. 5) Consider the y value at x=2.5. At which x is this value y(x=2.5) increased by 150% according to the model?
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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Transcribed Image Text:2.
Consider the following data.
1
2
3
4
5
6 7
2 35 150 500 1250 2500 5000
X
y
Apply the whole modeling process:
1) Consider a modeling assumption and its linearized version Y = AX + B. You
may assume that the model is a power function model or an exponential model.
2) Test the suitability of the model assumptions.
3) Develop a model on this basis by determining the model parameters.
4) Test the suitability of your model by comparing it with the original data.
Calculate the relative error in % for each data point. Comment on the suitability
of your model.
5) Consider the y value at x=2.5. At which x is this value y(x=2.5) increased by
150% according to the model?
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