I honestly don't know but I think it would come out to be 4/5
 
        
             
        
        
        
Answer:
72 degrees
Step-by-step explanation:
Referencing off of line t being a straight line, a straight line is 180 degrees. If you subtract 108 from 180, you would get 72. Since this intersecting line is going through 2 paralel lines, the 2 groupings of angles reflect each other. 
 
        
             
        
        
        
I don’t know why the word “million” is there, but the incremental cost per unit of the secon hundred units is $30 per unit.
        
             
        
        
        
Answer:
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56
Step-by-step explanation:
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Answer:
A), B) and D) are true
Step-by-step explanation:
A) We can prove it as follows:

B) When you compute the product Ax, the i-th component is the matrix of the i-th column of A with x, denote this by Ai x. Then, we have that  . Now, the colums of A are orthonormal so we have that (Ai x)^2=x_i^2. Then
. Now, the colums of A are orthonormal so we have that (Ai x)^2=x_i^2. Then  .
.
C) Consider  . This set is orthogonal because
. This set is orthogonal because  , but S is not orthonormal because the norm of (0,2) is 2≠1.
, but S is not orthonormal because the norm of (0,2) is 2≠1.
D) Let A be an orthogonal matrix in  . Then the columns of A form an orthonormal set. We have that
. Then the columns of A form an orthonormal set. We have that  . To see this, note than the component
. To see this, note than the component  of the product
 of the product  is the dot product of the i-th row of
 is the dot product of the i-th row of  and the jth row of
 and the jth row of  . But the i-th row of
. But the i-th row of  is equal to the i-th column of
 is equal to the i-th column of  . If i≠j, this product is equal to 0 (orthogonality) and if i=j this product is equal to 1 (the columns are unit vectors), then
. If i≠j, this product is equal to 0 (orthogonality) and if i=j this product is equal to 1 (the columns are unit vectors), then  
    
E) Consider S={e_1,0}. S is orthogonal but is not linearly independent, because 0∈S.
In fact, every orthogonal set in R^n without zero vectors is linearly independent. Take a orthogonal set  and suppose that there are coefficients a_i such that
 and suppose that there are coefficients a_i such that  . For any i, take the dot product with u_i in both sides of the equation. All product are zero except u_i·u_i=||u_i||. Then
. For any i, take the dot product with u_i in both sides of the equation. All product are zero except u_i·u_i=||u_i||. Then  then
 then  .
.