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LU Decomposition breaks down a matrix into two components—Lower and Upper triangular matrices—making it easier and computationally efficient to solve systems of equations, including finding the inverse of a matrix. This method is widely used in numerical computing due to its stability and speed compared to direct methods like Gaussian elimination. Why Other Options are Wrong: a) Gaussian Elimination is more direct but less efficient than LU Decomposition. b) Newton-Raphson is used for finding roots of equations, not for matrix inversion. d) Monte Carlo is used for probabilistic simulations, not matrix computations. e) Gram-Schmidt is used for orthogonalization, not for matrix inversion.
(11.98% of 449.99) - 3.998 = √?
90.004% of 9500 + 362 = ?
25, 28, 26, 29, 27, ?
(√780 + 111.98) ÷ 6.95 + 39.95% of 179.98 = ?
104.27% of 1200.11 + 12.08% of 2360.81 = 22.23% of ? + 1430.99
`11(2/13)` + `5(2/11)` - `3(4/9)` = ?
(9116.89 – 8024.89 + 902.95) × 14 = 1800 × ?
(5.013 – 30.04) = ? + 11.98% of 4799.98
Find the approximate value of Question mark(?). No need to find the exact value.
(34.95 × 7.03) ÷ 5 + 27.98% of 249.88 – √(80.81) = ?
...11.69% of 499.78 + (2.89 × 39.76) = ?