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01.08.2019-420 views -Try out Problem Collection ECSE 443- introduction to Numerical Methods in EE

Practice Problem Arranged – Part 4

(Note: This problem collection is for extra practice. It is not for credit, and not to become handed in) Question 1: Suppose that within a study, a number of measurements were created to determine a certain quantity several values of. The accumulated data are summarized inside the following stand: 1 . 0000 5. 8823 1 . 5000 2 . 0000 2 . 5000 3. 0000 3. 5000 4. 0000 4. 5000 5. 0000 5. 5000 6. 0000 8. 8823 17. 8821 11. 8822 14. 8826 26. 8825 24. 8822 28. 8822 45. 8826 50. 8821 59. 8829

a) Intended for the

beliefs, determine the measures of central propensity: (a)- Math mean, (b)- Median, (c)- Mode plus the measures of spread: (d)- Range, (e)- Standard change, (f)-Variance (g)- Coefficient of variation. Solution: (a)- 21. 9733, (b)- 24. 8822, (c)- Simply no Mode (d)- 54. 0006, (e)- 18. 0248, (f)- 324. 8950, (g)- 66. 8248

b) Apply the least-square regression and in shape a first-order line towards the given factors. Determine the standard error of estimate as well as the coefficient of determination. Compare the fitting accuracy of this linear model with the model in part (a) that only uses the arithmetic mean of the variable. Solution: < zero. 8964, c) Apply the least-square regression and in shape a second-order curve towards the given items. Determine the normal error of estimate as well as the coefficient of determination. Assess the reliability of this polynomial fit with the linear style in part (b). Answer: < 0. 9567, > 324. 8950

d) Apply the overall linear least-square to fit the model, wherever, and are 3 basis features as follow:,, Compute the corresponding matrix system by employing the method of typical equation. Decide the standard problem of approximate and the pourcentage of willpower. Compare the fitting precision with component (c). Solution: < zero. 9998, >

ECSE 443- introduction to Numerical Methods in EE

Practice Problem Set – Part 4

Problem 2: The goal of a two dimensional quadratic regression should be to find the best principles for the coefficients...