Vector Placing in Transformation Matrix: Rows vs. Columns Explained

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Homework Help Overview

The discussion revolves around the construction of transformation matrices in linear algebra, specifically focusing on the placement of basis vectors as either rows or columns. Participants are exploring the implications of this choice on the transformation process.

Discussion Character

  • Conceptual clarification, Assumption checking, Exploratory

Approaches and Questions Raised

  • Participants are questioning the conditions under which basis vectors should be placed as rows versus columns in a transformation matrix. There are attempts to clarify the reasoning behind these placements, with references to matrix multiplication and transposition.

Discussion Status

The discussion is ongoing, with participants offering insights and suggestions for experimentation, such as trying both placements to see the outcomes. There is a request for simpler explanations and examples to aid understanding.

Contextual Notes

Some participants express difficulty in grasping how matrix multiplication influences the decision on vector placement, indicating a need for clearer examples and definitions. There is also a mention of previous guidance that may not have been fully understood.

transgalactic
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in previous question
i was tald that in the process of building the transformation matrix

i should have put the vectors of the new base as columns and not as rows

in what cases and in what formes i put them as rows??
in what cases and in what formes i put them as columns??
 
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transgalactic said:
in previous question
i was tald that in the process of building the transformation matrix

i should have put the vectors of the new base as columns and not as rows

in what cases and in what formes i put them as rows??
in what cases and in what formes i put them as columns??
Think about transposition...


regards

marco
 
Also, you can always check by applying the transformation matrix to one of your basis elements. If you want A to transform the vector v into the vector w, you can check that indeed
Av = w
and/or
A-1 w = v.

For example, if you write down a general matrix
A = \begin{pmatrix} a_{11} & a_{12} & \cdots \\ a_{21} & a_{22} & \cdots \\ \vdots & \ddots & \cdots \end{pmatrix}
you can apply it to the (old) basis vector
e_1 = \begin{pmatrix} 1 \\ 0 \\ 0 \\ \vdots \end{pmatrix}
and just do the multiplication explicitly. You will get a result expressed in the a_{ij} which will in fact be just a complete row or column from A. On the other hand, it should also be the new basis vector. So you can read off whether you need to put it in a column, or in a row.
 
can you give an actual example to this
and in simpler words

because i can't understand how this multiplication effects the desition to put the vectors by rows or by columns

using your multiplication i would get the first row of this matrix
now what??
 
He said: "Try both and see which gives what you want!"
 

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