Use the inner product u, v = 2u1v1 + u2v2 in R2 and the Gram-Schmidt orthonormalization process to transform {(2, 1), (−2, −10)} into an orthonormal basis. (Use the vectors in the order in which they are given.)

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Step-by-step explanation:

In numerical analysis and  linear algebra, the Gram–Schmidt process is a technique for orthonormalising an array of vectors in an inner product space, while an orthonormal basis that is a finite dimension with inner product space V is a basis for V whose vectors can be classified as orthonormal, that is, they are all unit vectors as well as being orthogonal to each other.

Kindly check the attached image below to get the explanation to the question above.

$25

step-by-step explanation:

25 - 4.50 = 20.5

20.5 / 2 = 10.25

10.25 + 10 = 20.25

20.25 - 12.50 = 7.75

therefore the answer is $25 as shown as the first number.