What does a row matrix represent geometrically?

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In summary, a row matrix represents a geometric entity in a multidimensional space, specifically as a point or vector in a Cartesian coordinate system. Each element of the row matrix corresponds to a coordinate along a specific axis, allowing it to define a unique position or direction in that space.
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tellmesomething
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What does a row matrix represent geometrically ?
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I understand that a column matrix of order n×1 is taken as a vector with each element representing the x coordinate (x ##\hat i ##) y coordinate(y ##\hat j ##) z coordinate(z ##\hat k ##) ... n coordinate (n × unit vector in nth dimension) of that vector.

I also understand that a matrix of order m×n , each column represents the linearly transformed vector of unit vectors leading up to the nth dimension.

What I dont get is what does a row matrix represent?
Does it represent the linearly transformed unit vectors but in this case it has all been squished into one dimension?
 
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As you say, an ##m\times n## matrix over ##\mathbb R##, say, represents a linear map ##\mathbb R^n \to\mathbb R^m##. Hence, a row would correspond to a linear map ##\mathbb R^n\to\mathbb R##. A projection, for instance.
 
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You should first say that, you are using the matrix, ##M##, as a multiplier on the left of a vector, ##\vec{v}##: ##M \vec{v}##, rather than on the right.
tellmesomething said:
What I dont get is what does a row matrix represent?
Does it represent the linearly transformed unit vectors but in this case it has all been squished into one dimension?
Yes, you are correct. In the case of a general ##m \times n## matrix, each of the ##m## rows represents a linear combination of the elements of any ##n \times 1## vector that it multiplies on the left. That is true no matter what the row dimension, ##m##, of the matrix is.
 
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A matrix in its most general sense, is a rectangular array of Mathematical objects that takes meaning depending on context. It can be an adjacency matrix for a graph, a correlation matrix between two Random Variables, a linear transformation.
 
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tellmesomething said:
What I dont get is what does a row matrix represent?
Also a vector. You can think of a dot product for vectors in ##\mathbb R^3## as a product of a row matrix (on the left) and a column vector (on the right).

For example,
##\begin{bmatrix} 1 & 3 & 2 \end{bmatrix}\begin{bmatrix} 2 \\ 3 \\ 6 \end{bmatrix} = 1\cdot 2 + 3\cdot 3 + 2\cdot 6 = 2 + 9 + 12 = 23##

Be aware that if you have a column vector on the left and a row vector on the right you get something different. For the example above if the vectors are switched, you get a 3 x 3 matrix.
 
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FactChecker said:
You should first say that, you are using the matrix, ##M##, as a multiplier on the left of a vector, ##\vec{v}##: ##M \vec{v}##, rather than on the right.

Yes, you are correct. In the case of a general ##m \times n## matrix, each of the ##m## rows represents a linear combination of the elements of any ##n \times 1## vector that it multiplies on the left. That is true no matter what the row dimension, ##m##, of the matrix is.

I see thankyou for your reply. :) additionally do you have any recommended books to further understand the different types of matrices its applications and its vector interpretation?
 
  • #8
tellmesomething said:
do you have any recommended books to further understand the different types of matrices its applications and its vector interpretation?
None that stand out from the others. You should know that there are a great variety of uses and interpretations of different types of matrices, some with very good geometric interpretations, and others more obscure. Linear functions can be represented by matrices, but there can be disadvantages of using a matrix which makes a representation depend on a particular basis and coordinate system.
 
  • #9
tellmesomething said:
I see thankyou for your reply. :) additionally do you have any recommended books to further understand the different types of matrices its applications and its vector interpretation?
I liked Steven Leon's Linear Algebra book. You may complement it with plenty of YouTube videos. Several from Prof Steven Brunton from University of Washington alone, include both theory and applications of SVD to face recognition and general Machine Learning

https://www.google.com/search?q=You...yAEAmAIAoAIAmAMAkgcAoAcA&sclient=gws-wiz-serp
 

FAQ: What does a row matrix represent geometrically?

What is a row matrix?

A row matrix is a matrix that consists of a single row of elements. It can be represented as a 1 x n matrix, where n is the number of columns. For example, the matrix [1, 2, 3] is a row matrix with one row and three columns.

What does a row matrix represent geometrically?

Geometrically, a row matrix can be interpreted as a point in an n-dimensional space. Each element of the row matrix corresponds to a coordinate along one of the axes in that space. For example, a row matrix with three elements represents a point in three-dimensional space.

How does the dimension of a row matrix affect its geometric representation?

The dimension of a row matrix directly affects its geometric representation. A row matrix with n elements represents a point in n-dimensional space. As the number of elements increases, the geometric representation extends into higher dimensions, which can be difficult to visualize beyond three dimensions.

Can a row matrix represent a vector?

Yes, a row matrix can represent a vector. Specifically, it is often referred to as a row vector. In linear algebra, row vectors are used to represent directions and magnitudes in vector spaces, and they can be used in operations such as dot products and matrix multiplications.

What is the relationship between a row matrix and linear transformations?

A row matrix can be used to represent the coefficients of a linear transformation. When a row matrix is multiplied by a column matrix (or vector), the result is a linear combination of the columns of the column matrix. This operation illustrates how the row matrix transforms the vector in the context of linear algebra.

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