# Mathematics II - Unit Wise Questions

1. Define system of linear equations. When a system of equations is consistent? Determine if the system

-2x_{1}-3x_{2}+4x_{3} = 5

x_{2}-2x_{3} = 4

x_{1}+3x_{2}-x_{3} = 2

is consistent. [1+1+8]

1. What is pivot position? Apply elementary row operation to transform the following matrix first into echelon form and then into reduced echelon form:

1. Illustrate by an example that a system of linear equations has either equations has either exactly one solution or infinitely many solutions.

1. What is a system of linear equations? When the system is consistent and inconsistent?

1. Write down the conditions for consistent of non- homogenous system of linear equations.

1. When a system of linear equation is consistent and inconsistent? Give an example for each. Test the consistency and solve: x + y + z = 4, x + 2y + 2z = 2, 2x + 2y + z = 5.

1. When a system of linear equation is consistent and inconsistent? Give an example for each. Test the consistency and solve the system of equations: x - 2y = 5, -x + y + 5z = 2, y + z = 0

1. Why the system x_{1} - 3x_{2} = 4; -3x_{1} + 9x_{2} = 8 is consistent? Give the graphical representation?

1. What are the criteria for a rectangular matrix to be in echelon form?

1. What do you mean by linearly independent set and linearly dependent set of vectors?

1. Define linear combination of vectors. When the vectors are linearly dependent and independent?

1. When is system of linear equation consistent or inconsistent?

1. Illustrate by an example that a system of linear equations has either no solution or exactly

one solution.

2. Define singular and nonsingular matrices.

2. Define linear combination of vectors. If v_{1}, v_{2},v_{3} are vectors, Write the linear combination of 3v_{1} - 5v_{2} + 7v_{3} as a matrix times a vector.

2. Write numerical importance of partitioning matrices.

2. prove that (a) (A^{T})^{T} = A (b) (A + B)^{T} = A^{T} + B^{T} , Where A and B denote matrices whose size are appropriate for the above mentioned operations.

2. Define linear transformation between two vector spaces.

2. What is meant by independent of vectors?

2. When is a linear transformation invertible?

2. Define linearly dependent and independent vectors. If (1, 2) and (3, 6) are vectors then the vectors are linearly dependent or independent?

3. Using the Invertible matrix Theorem or otherwise, show that is invertible.

3. Show that the matrix is not invertible.

3. Solve the system

3x_{1} + 4x_{2} = 3, 5x_{1} + 6x_{2} = 7

by using the inverse of the matrix

3. How do you distinguish singular and non-singular matrices?

3. Is invertible matrix?

3. What is normal form of a matrix?

3. Define invertible matrix transformation.

3. What do you mean by consistent equations? Give suitable examples.

4. Let A and B be two square matrices. By taking suitable examples, show that even though AB and BA may not be equal, it is always true that detAB = detBA.

4. State the numerical importance of determinant calculation by row operation.

4. Let S be the parallelogram determined by the vectors b_{1} = (1, 3) and b_{2 }= (5, 1) and let Compute the area of the image S under the mapping

4. Define invertible linear transformation.

4. What do you mean by change of basis in R^{n}?

4. Define nonsingular linear transformation with suitable example.

4. What is numerical drawback of the direct calculation of the determinants?

4. If A and B are n x n matrices, then verify with an example that det(AB) = det(A)det(B).

4. Define invertible matrix transformation.

5. Determine the column of the matrix A are linearly independent, where

5. State Cramerâ€™s rule for an invertible n x n matrix A and vector to solve the system Ax = b. Is this method efficient from computational point of view?

5. Calculate the area of the parallelogram determined by the columns of

5. Find the dimension of the vector spanned by (1,1,0) and (0,1,0).

5. Let S be the parallelogram determined by the vectors b1 = (1, 3) and b2 = (5, 1) and let Compute the area of the image S under the mapping

5. Show that the matrices do not commute.

5. Consider the matrix as a linear mapping. Write the corresponding co-ordinate equations.

5. Verify with an example that det (AB ) = det ( A) det ( B) for any n x n matrices A and B.

5. Let S be the parallelogram determined by the vectors b_{1} = (1,3) and b_{2} = (5,1) and let . Compute the area of the image S under the mapping

5. Using Cramer's rule solve the following simultaneous equations:

5x + 7y = 3

2x + 4y = 1

6. Define vector space.

6. Find a matrix A such that *col*(A).

6. Define subspace of a vector space.

6. When is a linear transformation invertible.

6. Determine if {v_{1}, v_{2}, v_{3}} is basis for R^{3}, where

7. Determine if {v_{1}, v_{2}, v_{3}} is a basis for , where

6. Define vector space with suitable examples.

6. Define vector space.

5. Change into reduce echelon form of the matrix

7. Let **W** be the set of all vectors of the form , where b and c are arbitrary. Find vector **u** and **v** such that **W** = Span {**u**, **v**}.

7. Find the rank of AB where

7. Show that the entries in the vector x = (1, 6) are the coordinates of x relative to the standard basis (e_{1}, e_{2}).

7. Determine if w = (1, 3, -4) is a Nul A, where

7. Define subspace of a vector with an example.

7. Determine if is a Nul(A) for

6. Determine if is Nul(A), where,

7. If and let u = (5, 3, 2), then show that u is in the Nul A.

8. Show that 7 is an eigen value of

8. Is an Eigen value of

8. What are necessary and sufficient conditions for a matrix to be invertible?

6. State the numerical importance of determinant calculation by row operation.

8. Are the vectors; eigen vectors of

8. If u = (6, -5) is an eigen vector of ?

8. Is u = (3, -2) is an eigen value of ?

8. Find the characteristic polynomial for the eigen values of the matrix

8. Is an Eigen value of ?

9. Find the distance between vectors u ( ) and v ( ). Define the distance between

two vectors in *R ^{n}*.

9. Let Find a unit vector in the same direction as

7. Show that {(1, 1), (-1,0)} form a bias for *R ^{2}*.

9. Determine whether the pair of vectors are orthogonal or not?

9. If S = {u_{1},... .... ... ... , u_{p}} is an orthogonal set of nonzero vectors in R^{2}, show S is linearly independent and hence is a basis for the subspace spanned by S.

9. Find the inner product of (2, -5, -1) and (3, 2, -3).

9. Define kernel and image of linear transformation.

9. Find the inner product of (1, 2, 3) and (2, 3, 4).

9. Find the unit vector u of v = (1, -2, 2, 0) along the direction of v.

10. Let w = span {x_{1}, x_{2}}, where Then construct orthogonal basis for w.

10. Find the norm between the vectors u = (1, 2, 3, 4) and v = (0, 1, 2, 3).

10. Let {u_{1},... ... ... u_{p}}be an orthogonal basis for a subspace W of R^{n}. Then prove that for each ,the weights in y = c_{1}u_{1} + ... ... ... + c_{p}u_{p} are given by

8. Let be a linear transformation defined by T(x, y) = (x + y, y). Find Ker T.

10. Compute the norm between the vectors 4 = (7, 1) and v = (3, 2).

10. Let W = span{x1, x2} where and Their construct orthogonal basis for W.

10. What do you understand by least square line? Illustrate.

10. Find the norm vector v = (1, -2, 3, 0).

10. What is meant by Discrete dynamical system? Give suitable example.

9. If Î» is an eigen values of matrix A, find the eigen values of A^{-1}.

11. Let be the linear transformation defined by T(x, y, z) = (x, y, x - 2y). Find a basis and dimension of (a) Ker T (b) Im T

11. Determine if the given set is linearly dependent:

11. Let and . Find the images under T of

11. A linear transformation is defined by . Find the image of T of

11. If a set s = {v_{1}, v_{2, ... ... ... ,}v_{p}} in R^{n} contains the zero vector, then prove that the set is linearly dependent. Determine if the set is linearly dependent.

11. Let , u = (1, 0, -3) and v = (5, -1, 4), If defined by T(x) = Ax, find T (u) and T (v).

11. Prove that any set{v_{1},... ... ... ... , v_{2}} in R^{n} is linearly dependent if p > n.

11. What are the criteria for a transformation T to be linear? If is defined by T(x) = 3x,

Show that T is a linear transformation. Also give a geometric description of the transformation

10. Let u = (1,2,-1,3) and v = (3,0,2,-2). Compute the inner product (u, u + v).

12. Show that the following vectors are linearly independent:(1, 1, 2),(3, 1, 2),(0, 1, 4).

12. Find the 3 x 3 matrix that corresponds to the composite transformation of a scaling by 0.3, a rotation of 90^{0} , and finally a translation that adds (-0.5, 2) to each point of a figure.

**OR**

Describe the Leontief Input-Output model for certain economy and derive formula for (I-C)-1, where

symbols have their usual meanings.

12. Consider the Leontief input â€“ output model equation x = cx + d, where the consumption matrix is

Suppose the final demand is 50 units of manufacturing, 30 units of agriculture, 20 units for services. Find the production level x that will satisfy the demand.

12. Given the Leontief input-output model x = Cx + d, where the symbols have their usual

meanings, consider any economy whose consumption matrix is given by Suppose the final demand is 50 units for manufacturing 30 units for agriculture, 20 units for services. Find the production level x that will satisfy this demand.

12. If compute (Ax)^{T}, x^{T}A^{T} and xx^{T}. Can you compute x^{T}A^{T}?

12. Find the determinant of

12. Prove that if A is an invertible matrix, then so is A^{T}, and the inverse of A^{T} is the transpose of A^{-1}.

13. What do you mean by basis of a vector space? Find the basis for the row space of

**OR**

State and prove the unique representation theorem for coordinate systems.

13. Find the coordinate vector [X]_{B} of a x relative to the given basis B = {b_{1}, b_{2}}, where

13. Define subspace of a vector space **V**. Given v_{1} and v_{2} in a vector space **V**, let H = span {v_{1}, v_{2}}. Show that **H** is a subspace of **V**.

**OR**

If is a basis for a vector space V and x is in V, define the coordinate of x relative to the basis . Let Then is a basis for H = Span {v_{1}, v_{2}}. Determine is X is in **H**, and if it is, find the coordinate vector of **x** relative to

13. Show that the vectors (1, 0, 0),(1, 1, 0) and (1, 1, 1) are linearly independent.

13. If v_{1} and v_{2} are the vectors of a vector space V and H = span {v_{1}, v_{2}}, then show that H is a subspace of V.

13. If b_{1} = (2, 1), and B = {b_{1}, b_{2}}, find the co-ordinate vector [x]_{B} of x relative to B.

13. Find the matrix representation of linear transformation defined by T(x, y) = (x + 2y) relative to the standard basis.

11. Determine whether the following vectors in* R ^{3}* are linearly dependent:

a. (1,0,1), (1,1,0),(-1,0,-1),

b. (2,1,1),(3,-2,2),(-1,2,-1).

13. Define rank of a matrix and state Rank Theorem. If A is a 7 x 9 matrix with a

two-dimensional null space, find the rank of A.

14. What do you mean by eigen values, eigen vectors and characteristic polynomial of a matrix? Explain with suitable examples.

14. Find the eigen values of

14. Find the eigen values of .

14. Determine the eigen values and eigen vectors of in complex numbers.

**OR**

Let and basis B = {b_{1}, b_{2}}.Find the B-matrix for the transformation with P= [b_{1}, b_{2}].

14. Is the set of vectors {(91, 0, 1),(0, 1, 0),(-1, 0, 1)} orthogonal? Obtain the corresponding orthonomal set R^{3}.

12. Investigate and interpret geometrically the transformation of the unit square whose vertices are O(0,0,1),A(1,0,1),B(0,1,1),and C(1,1,1) effected by the 3 x 3 matrix:

OR

Is the set of vectors {(),(),()} orthogonal? Obtain the corresponding orthogonal? Obtain the corresponding orthonormal set in R^{3}.

14. Let and basis B = {b1, b2}.Find the B-matrix for the transformation with P = {b_{1}, b_{2}}.

14. The mapping defined by T(a_{0} + a_{1}t + a_{2}t^{2}) = a_{1} + 2a_{2}t is a linear transformation.

a) Find the matrix for T, when is the basis {1, t, t^{2}}.

b) Verify that [T(**p**)]_{B} = [T]_{B}[**p**]_{B} for each** p** in **P**_{2}.

14. Find the eigen values of

15. Let u and v be non-zero vectors in R^{3} and the angle between them be Then prove that where the symbols have their usual meanings.

15. Let Find a least square solution of Ax = b, and compute the associated least square error.

15. If v_{1} = (3, 6, 0), v_{2} = (0, 0, 2) are the orthogonal basis then find the orthonal basis of v_{1} and v_{2}.

**OR**

Find an orthogonal projection of y onto u, where y = (7, 6), u = (4, 2)

15. Let u and v be nonzero vectors in R^{2} and the angle between them be Î¸ then prove that u.v = â€–uâ€– â€–vâ€– cos Î¸,

where the symbols have their usual meanings.

15. Show that {v_{1}, v_{2}, v_{3}} is an orthogonal set, where v_{1} = (3,1,1), v_{2} = (-1, 2, 1),

15. Define the Gram-Schmidt process. Let W=span{x_{1}, x_{2}}, where Then construct an orthogonal basis {v_{1}, v_{2}} for w.

13. In the vestor space R^{2}, express the given vector the given vector (1,2 ) as a linear combination of the vectors (1, -1) and (0,1)

15. Let the four vertices O(0, 0), A(1, 0), B(0, 1) and C(1, 1) of a unit square be represented by 2 x 4 matrix . Investigate and interpret geometrically the effect of pre-multiplication of this matric by the 2 x 2 matrix:

**OR**

State and prove orthogonality property for any two non-zero vectors in **R ^{n}**

^{}.

15. Show that (v_{1}, v_{2}, v_{3}) is an orthogonal basis of R^{3}, where

**OR**

Find an orthogonal projection of y onto u, where y = (7, 6), u = (4, 2).

14. Find the matrix representation of the linear transformation defined by T(x,y) = (x,x + 2y) relative to the basis (1,0) and (1,1).

16. Let be a linear transformation and let A be the standard matrix for T. Then prove that: T map **R ^{n} **on to

**R**if and only if the columns of A span

^{m}**R**; and T is one-to-one if and only if the columns of A are linearly independent. Let T(x

^{m}_{1}, x

_{2}) = (3x

_{1}+ x

_{2}, 5x

_{1}+ 7x

_{2}, x

_{1}+ 3x

_{2}). Show that T is a one-to-one linear transformation. Does T map

**R**onto

^{2}**R**?

^{3}16. Determine if the following system is inconsistent.

x_{2} - 4x_{3} = 8

2x_{1} - 3x_{2} + 2x_{1} = 1

5x_{1} - 8x_{2} + 7x_{3} = 1

OR

Let a_{1} = (1, -2, -5), a_{2 }= (2, 5, 6) and b = (7, 4, -3) are the vectors. Determine whether b can be generated as a linear combination of a_{1} and a_{2}. That is determine whether x_{1} and x_{2} exist such that x_{1}a_{1} + x_{2}a_{2} = b has solution, find it.

16. Determine if the following system is consistent, if consistent solve the system.

-2x_{1} - 3x_{2} + 4x_{3} = 5

x_{1} - 2x_{2} = 4

x_{1} + 3x_{2} - x_{3} = 2

OR

Let and define a transformation so that

a) Find T(u)

b) Find x in R^{2} whose image under T is b.

15. Let u and v be nonzero vector in Rn and the angle between them be . Then prove the

Where the symbol have their usual meanings.

16. Given the matrix discuss the for word phase and backward phase of the row reduction algorithm.

16. Determine if the following homogeneous system has a nontrivial solution. Then describe the

solution set. 3x_{1} + 5x_{2} - 4x_{3 }= 0, - 3x_{1} -2x + 4x_{3}= 0, 6x_{1} + x_{2} - 8x_{3} = 0.

16. Find a matrix A whose inverse is

16. Let be a linear transformation. Then T is one-to-one if and only if the equation T(x) = 0

has only the trivial solution, prove the statement.

**OR**

Let and