Linear Algebra : Range and Null Space of a Matrix

Study concepts, example questions & explanations for Linear Algebra

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Example Questions

Example Question #11 : Range And Null Space Of A Matrix

What is the largest possible rank of a  matrix?

Possible Answers:

None of the other answers

Correct answer:

Explanation:

The rank is equal to the dimension of the row space and the column space (both spaces always have the same dimension). This matrix has seven rows and two columns, which means the largest possible number of vectors in a basis for the column space of a  matrix is , so this is the largest possible rank.

Example Question #12 : Range And Null Space Of A Matrix

What is the smallest possible nullity of a  matrix?

Possible Answers:

None of the other answers

Correct answer:

Explanation:

According to the Rank + Nullity Theorem, 

Since the matrix has  columns, we can rearrange the equation to get

So to make the nullity as small as possible, we need to make the rank as large as possible.

The rank is equal to the dimension of the row space and the column space (both spaces always have the same dimension). This matrix has three rows and five columns, which means the largest possible number of vectors in a basis for the row space of a  matrix is , so this is the largest possible rank.

Hence the smallest possible nullity is .

Example Question #302 : Operations And Properties

A matrix  with five rows and four columns has rank 3.

What is the nullity of ?

Possible Answers:

Correct answer:

Explanation:

The sum of the rank and the nullity of any matrix is always equal to to the number of columns in the matrix. Therefore, a matrix with four columns and rank 3, such as , must have as its nullity .

Example Question #14 : Range And Null Space Of A Matrix

, the set of all continuous functions defined on , is a vector space under the usual rules of addition and scalar multiplication.

True or false: The set of all functions of the form 

,

where  is a real number, is a subspace of .

Possible Answers:

False

True

Correct answer:

True

Explanation:

A subset  of a vector space is a subspace of that vector space if and only if it meets two criteria. Both will be given and tested, letting 

.

This can be rewritten as

One criterion for  to be a subspace is closure under addition; that is:

If , then .

Let  as defined. Then for some real :

It follows that .

The second criterion for  to be a subspace is closure under scalar multiplication; that is:

If , then 

Let  as defined. Then for some real :

It follows that 

, as defined, is a subspace of .

Example Question #15 : Range And Null Space Of A Matrix

, the set of all continuous functions defined on , is a vector space under the usual rules of addition and scalar multiplication.

True or false: The set of all functions of the form 

,

where  is a real number, is a subspace of .

Possible Answers:

True

False

Correct answer:

False

Explanation:

A subset  of a vector space can be proved to not be a subspace of the space by showing that the zero of the space is not in 

Let  be the subset in question, and let , the zero function, which is in . This cannot be expressed as  for any . It if could then

, in which case ,

and

, in which case .

By contradiction,  is not a subspace of .

Example Question #12 : Range And Null Space Of A Matrix

, the set of all continuous functions defined on , is a vector space under the usual rules of addition and scalar multiplication.

True or false: The set of all functions of the form 

where  is a real number, is a subspace of .

Possible Answers:

False

True

Correct answer:

False

Explanation:

Let .

We can show through counterexample that this is not a subspace of .

Let . This is an element of .

One condition for  to be a subspace of a vector space is closure under scalar multiplication. Multiply  by scalar . The product is the function 

.

.

This violates a criterion for a subspace, so  is not a subspace of .

 

Example Question #17 : Range And Null Space Of A Matrix

, the set of all continuous functions defined on , is a vector space under the usual rules of addition and scalar multiplication.

True or false: The set of all functions defined on  with inverses is a subspace of .

Possible Answers:

True

False

Correct answer:

False

Explanation:

Let  be the set of all functions  on  such that  is defined. 

A sufficient condition for  to not be a subspace of  is that the zero of the set - which here is the zero function  - is not in .  because the zero function - a constant function - does not have an inverse ( , violating a condition of an invertible function). It follows that  is not a subspace of  .

Example Question #12 : Range And Null Space Of A Matrix

, the set of all continuous real-valued functions defined on , is a vector space under the usual rules of addition and scalar multiplication. 

Let  be the set of all functions of the form 

True or false:  is a subspace of .

Possible Answers:

True

False

Correct answer:

True

Explanation:

A set  is a subspace of a vector space if and only if two conditions hold, both of which are tested here.

The first condition is closure under addition - that is:

If , then 

Let  as defined. Then for some ,

 

and

.

or

,

. The first condition is met.

 

The second condition is closure under scalar multiplication - that is:

If  and  is a scalar, then 

Let  as defined. Then for some 

For any scalar ,

,

and

. The second condition is met. 

, as defined, is a subspace.

Example Question #19 : Range And Null Space Of A Matrix

, the set of all continuous real-valued functions defined on , is a vector space under the usual rules of addition and scalar multiplication. 

Let  be the set of all functions of the form 

for some real 

True or false:  is a subspace of .

Possible Answers:

True

False

Correct answer:

True

Explanation:

A set  is a subspace of a vector space if and only if two conditions hold, both of which are tested here.

The first condition is closure under addition - that is:

If , then 

Let  as defined. Then for some ,

and

Then 

or 

or

. The first condition is met.

The second condition is closure under scalar multiplication - that is:

If  and  is a scalar, then 

Let  as defined. Then for some 

For any scalar ,

or

. The second condition is met. 

, as defined, is a subspace.

 

Example Question #12 : Range And Null Space Of A Matrix

If  is an  matrix, find

Possible Answers:

Correct answer:

Explanation:

Since a basis for the row space and the column space of a matrix have the same, number of vectors then their dimensions are the same, say .

By the rank-nullity theorem, we have , or same to say

.

.

Hence .

Finally, applying the rank-nullity theorem to the transpose of , we have

, or the same to say

.

 (The row space dimension of  is the same as its transpose.)

.

Adding all four of our findings together gives us

.

 

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