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1 a) Show that if A is nonsingular symmetric matrix, then A^-1 is also symmetric. Write your
justi cation in clear sentences.
b) An n x n matrix A is called skew-symmetric if A = -A^T . Show that if n is odd a skew-symmetric matrix is singular.
1.a) Prove that the product A = v(w^T) of a nonzero m x 1 column vector v by a nonzero 1 x n
row vector w^T is an m x n matrix of rank 1. [Hint: do a few small examples]
b) Now show that if A is an m x n matrix of rank 1, then there exist a nonzero m x 1 column
vector v and a nonzero 1 x n row vector w^T such that A = v(w^T).
Is orthogonality reflexive, symmetric, and transitive? If so, it is an equivalence relation. If not true, find a counter-example.
Which is easier to compute, the U in the LU decomposition or the R in the QR decomposition? Explain your reasoning?
Rate QR factorization with the LU and PLU factorizations. Which would you prefer when solving large systems of linear equations, and why?
Create a one page “cheat sheet” in flow-chart form which explains the Gram-Schmidt process.
Suppose u have the value of error sum of square is 9.1,so what would u comments on this value ?
data
X y
4 10
5 14
6 12
7 17
8 19
1. (2 Points) Explain clearly why the solution to the homogeneous system Ax = 0 with a nonsingular
coecient matrix is x = 0.

2. (2 Points) Under what conditions does a diagonal matrix D = diag(d1,d2,.....,dn) have an inverse
D^-1? What is the inverse D^-1 when these conditions are met? Justify your answers.

3. (3 Points) Let A be an mxn matrix and B be an nxm matrix where m > n. Show that the nxn matrix AB is not invertible.
1. (2 Points) Explain clearly why the solution to the homogeneous system Ax = 0 with a nonsingular
coecient matrix is x = 0.

2. (2 Points) Under what conditions does a diagonal matrix D = diag(d1,d2,.....,dn) have an inverse
D^-1? What is the inverse D^-1 when these conditions are met? Justify your answers.

3. (3 Points) Let A be an mxn matrix and B be an nxm matrix where m > n. Show that the nxn matrix AB is not invertible.
Show that, for any vector z in C^J, the member of H_i closest to z is x having the entries:
___
x_j = z_j + a_i^(-1)A_ij(b_i - (Az)_i),

where a_i = The sum from j=1 to J of |A_ij|^2.
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