Compute the least-squares line for predicting ln y from t

Reference no: EM131162763

The article "Application of Genetic Algorithms to Optimum Design of Elasto-damping Elements of a Half-Car Model Under Random Road Excitations" (M. Mirzael and R. Hassannejad, Proceedings of the Institution of Mechanical Engineers, 2007:515-526) presents values of a coefficient (y), a unitless quantity that measures the road impact on an automobile suspension, and the time (t ) for the car to travel a distance equal to the length between the front and rear axles. The results are as follows:

t	y	t	y	t	y
0.0	1.000	0.5	0.995	1.0	0.987
0.1	0.999	0.6	0.993	1.1	0.985
0.2	0.998	0.7	0.992	1.2	0.983
0.3	0.997	0.8	0.990	1.3	0.981
0.4	0.996	0.9	0.988	1.4	0.979

a. Compute the least-squares line for predicting road impact (y) from time (t). Plot the residuals versus the fitted values.

b. Compute the least-squares line for predicting ln y from t . Plot the residuals versus the fitted values.

c. Compute the least-squares line for predicting y from t 1.5 . Plot the residuals versus the fitted values.

d. Which of the three models (a) through (c) fits best? Explain.

e. Using the best model, estimate the road impact for a time of 0.75.

Reference no: EM131162763

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