Understanding Solutions in Linear Algebra: The Case of m>n

In summary, the question on the test asks for an explanation on why, in general, there may not be a solution to the equation Ax = b where A is an mxn matrix with m>n and b is a vector in Rm. This statement does not mean there will never be a solution, but rather that solutions are rare due to the nature of the matrix dimensions and the result of row reduction.
  • #1
Miike012
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I don't remember exactly how the question on my test was phrased but I believe it was phrased

"Let A be an mxn matrix where m>n. Explain why in general there is not a solution to the equation Ax = b where b is a vector in Rm"

This question was confusing to me because to me the meaning of the question is saying

For all matrices A with dimension mxn, m>n, There does not exist a solution x such that b = Ax, where b is a vector in Rm.

Which is obviously a false statement because I can easily produce a mxn (m>n) matrix A and a solution x such that
Ax = b, b is a vector in Rm.

This is what I would like to know. I don't want to know what you think it means. Based on how it is worded I want to know what the statement is saying. (I hope that makes sense what I'm asking for)
 
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  • #2
Miike012 said:
I don't remember exactly how the question on my test was phrased but I believe it was phrased

"Let A be an mxn matrix where m>n. Explain why in general there is not a solution to the equation Ax = b where b is a vector in Rm"

This question was confusing to me because to me the meaning of the question is saying

For all matrices A with dimension mxn, m>n, There does not exist a solution x such that b = Ax, where b is a vector in Rm.

Which is obviously a false statement because I can easily produce a mxn (m>n) matrix A and a solution x such that
Ax = b, b is a vector in Rm.

This is what I would like to know. I don't want to know what you think it means. Based on how it is worded I want to know what the statement is saying. (I hope that makes sense what I'm asking for)
When it says "in general there is not a solution" this doesn't mean that there is never a solution. It means that there can be a solution, but such solutions would be fairly rare.

To convince yourself of what the statement is saying, make up an m x n matrix A with m > n, say a 5 X 3 matrix. Here x would have to be a 3 X 1 column vector, and b would have to be a 5 X 1 column vector. Given that there are more rows in A than columns, row reduction would leave you with at least 2 rows of zeroes, and possibly more. If, during row reduction (using an augmented matrix), the column for b didn't end up with zeroes in the positions that correspond to the zero rows in the reduced matrix, there wouldn't be a solution.

The situation would be something like this:
$$\left[ \begin{array}{c c c c c} 1 & 0 & 0 & | & b_1 \\
0 & 1 & 0 & | & b_2 \\
0 & 0 & 1 & | & b_3 \\
0 & 0 & 0 & | & b_4 \\
0 & 0 & 0 & | & b_5 \\ \end{array} \right]$$
 
  • #3
Mark44 said:
When it says "in general there is not a solution" this doesn't mean that there is never a solution. It means that there can be a solution, but such solutions would be fairly rare.

To convince yourself of what the statement is saying, make up an m x n matrix A with m > n, say a 5 X 3 matrix. Here x would have to be a 3 X 1 column vector, and b would have to be a 5 X 1 column vector. Given that there are more rows in A than columns, row reduction would leave you with at least 2 rows of zeroes, and possibly more. If, during row reduction (using an augmented matrix), the column for b didn't end up with zeroes in the positions that correspond to the zero rows in the reduced matrix, there wouldn't be a solution.

The situation would be something like this:
$$\left[ \begin{array}{c c c c c} 1 & 0 & 0 & | & b_1 \\
0 & 1 & 0 & | & b_2 \\
0 & 0 & 1 & | & b_3 \\
0 & 0 & 0 & | & b_4 \\
0 & 0 & 0 & | & b_5 \\ \end{array} \right]$$

Thanks. I was wrong then. I though it was saying there will never be a solution. I was hopeing I would be able to get more point on my test ha.
 

Related to Understanding Solutions in Linear Algebra: The Case of m>n

1. What is linear algebra and why is it important?

Linear algebra is a branch of mathematics that deals with systems of linear equations and their properties. It is an important tool for solving problems in many fields, including physics, engineering, economics, and computer science. It provides a framework for understanding and manipulating multivariate data and can be used to model and analyze real-world systems.

2. What types of problems can be solved using linear algebra?

Linear algebra can be used to solve a wide range of problems, including finding solutions to systems of equations, performing transformations in geometry, analyzing data sets, and solving optimization problems. It is also used in computer graphics, machine learning, and cryptography.

3. What are the key concepts in linear algebra?

Some key concepts in linear algebra include vector spaces, matrices, determinants, eigenvalues and eigenvectors, and linear transformations. These concepts are used to analyze and manipulate systems of linear equations, perform transformations, and solve various problems in mathematics and other fields.

4. How can I prepare for a linear algebra test?

To prepare for a linear algebra test, it is important to review the key concepts and techniques, practice solving problems, and familiarize yourself with the types of questions that may be asked. It is also helpful to work through examples and exercises from textbooks or online resources, and to seek help from a tutor or instructor if needed.

5. What are some common mistakes to avoid in linear algebra?

Some common mistakes to avoid in linear algebra include mixing up row and column operations, forgetting to apply the distributive property when multiplying matrices, and neglecting to check for consistency in systems of equations. It is also important to pay attention to details and follow the correct steps when solving problems, rather than relying on shortcuts or intuition.

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