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MAE 284 Final exam 2022 with complete solution

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MAE 284 Final exam 2022 with complete solution The parabolic interpolation method is based on fitting a parabola to three points on the function. -Answer- True The golden section method helps to minimize computational costs in finding a maximum/minimum. -Answer- True The key benefit to the golden section method is that we do not have to calculate both x1 and x2 at each iteration. -Answer- True The parabolic interpolation method is usually faster than the golden section method. -Answer- True Adaptive Quadrature adjusts to use a smaller step size in areas where the function changes rapidly, and a larger step size where the function changes slowly. -Answer- True Romberg's method is a Newton-Cotes method. -Answer- True The error for the "normal" accuracy versions of the forward, backward, and centered finite difference approximations is O(h). -Answer- False Numerical differentiation is not particularly susceptible to errors in data. -Answer- False Simpson's 1/3 Rule approximates the function by a ______ -order polynomial. -Answer- Second Romberg's method is NOT a Newton-Cotes method. -Answer- False The only way to increase the accuracy of a numerical approximation of a derivative is to add more terms in the Taylor Series used to derive the approximation. -Answer- False The error for the "normal" accuracy versions of the forward, backward, and centered finite difference approximations is O(h2). -Answer- False The determinant of a matrix is a scalar. -Answer- True If two rows of a matrix are interchanged, the determinant changes sign. -Answer- True At the start of Gauss Elimination, the first equation is known as the pivot equation and the a11 element is known as the pivot element. -Answer- True A student wants to skip the next three MAE 284 labs, and is writing some MATLAB code to see what that will do to their GPA. They need to name a variable, but for some reason can't remember which names are valid. Of the four potential variable names below, which one is valid? -Answer- GPA_no_skipping

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