Numerical Methods for Engineers
Numerical Methods for Engineers
7th Edition
ISBN: 9780073397924
Author: Steven C. Chapra Dr., Raymond P. Canale
Publisher: McGraw-Hill Education
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Chapter 17, Problem 31P

In Prob. 17.11 we used transformations to linearize and fit the following model:

y = α 4 x e β 4 x

Use nonlinear regression to estimate α 4 and β 4 based on the following data. Develop a plot of your fit along with the data.

x 0.1 0.2 0.4 0.6 0.9 1.3 1.5 1.7 1.8
y 0.75 1.25 1.45 1.25 0.85 0.55 0.35 0.28 0.18
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Linearize the model ? = ? ? ?^(?? )and solve for the coefficients by hand using the following data   x 0.1 0.2 0.4 0.6 0.9 1.3 1.5 1.7 1.8 y 0.75 1.25 1.45 1.25 0.85 0.55 0.35 0.28 0.18
As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.
4. Develop a model using regression analysis for trip production using the following data. Zone Number Trip production Trip Vehicle Employment attraction ownership 1 200 1 1000 256 1.5 1250 345 2500 6. 451 2.8 3600 5 6.5 555 4200 6. 7 600 4 4500 3. 2. 3. 2. 3. 4.

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