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Linear Algebra and Vector Spaces Worksheet

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

The rank nullity Theorem Applies to

a)

Homogeneous differential equations

b)

Linear transformation

c)

Quadratic equation

d)

skew symmetric matrices

2.

The image of a linear transformation is

a)

Null space

b)

Range

c)

Kernal

d)

Domain

3.

If nullity |T|=0 then

a)

T is on to

b)

T is one to one

c)

T is not linear

d)

T is zero transformation

4.

If nullity = 0 then the transformation is

a)

Not linear

b)

injective

c)

subjective

d)

non - invertible

5.

The rank of an identity matrix of order n is

a)

0

b)

n

c)

n-1

d)

1

6.

A transformation is on to if

a)

Rank = number of columns

b)

Rank = number of rows

c)

Nullity = number of columns

d)

Nullity = number of rows

7.

If v is an eigenvector of a matrix A and λ is the corresponding eigen value, which of the following is always true?

a)

Av = v + λ

b)

Av = λv

c)

Av = v/λ

d)

Av = 0

8.

What is an eigenvalue of the matrix A = | 4 1 |

| 2 3 |

a)

6

b)

5

c)

4

d)

2

9.

The matrix representation of a linear transformation depends on

a)

Choice of bases

b)

Choice of field only

c)

Number of rows

d)

Types of equations

10.

If matrix A is 3 × 3 and nullity(A) = 1, then rank(A) =

a)

0

b)

1

c)

2

d)

3

11.

The inner product of vectors u = [1,2], v = [3,4] in R^2 is

a)

11

b)

7

c)

10

d)

14

12.

If u = (a, b), then ⟨u, u⟩ = 0 implies:

a)

a = b

b)

a = -b

c)

a = 0, b = 0

d)

a ≠ 0, b ≠ 0

13.

If ||u|| = √⟨u, v⟩, Then ||u|| ≥ 0 is a property of:

a)

Linear transformation

b)

Inner product

c)

Orthogonality

d)

Basis

14.

Which of the following is an orthonormal set in R^2?

a)

[1,0], [0,1]

b)

[1,1], [1,-1]

c)

[2,0], [0,3]

d)

[1,2], [2,1]

15.

The dot product of two orthogonal vector is:

a)

1

b)

-1

c)

0

d)

Either 0 or 1

16.

To make a vector v into a unit vector, divide it by:

a)

Its magnitude

b)

2

c)

Its first coordinate

d)

Its transpose

17.

If u = (1/√2, 1/√2), then ||u|| =

a)

1

b)

0

c)

√2

d)

1/2

18.

If →u = [3, 4], →v = [1, 0], then proj_→u_→v =

a)

(3,0)

b)

(0,4)

c)

(1,1)

d)

(2,2)

19.

The projection vector lies:

a)

Perpendicular to →v

b)

Along →v

c)

Along →u

d)

In a random direction

20.

In Gram-Schmidt process the projection is used for

a)

Normalize vectors

b)

Make vector orthogonal

c)

From a determinant

d)

None