s3w7 gaussian elimination and Cramers rule.

Trim End | 09:54

Questions 1 & 2 | 03:14

Question 3 | 07:33

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Questions 1 & 2

03:14

Question 3

07:33

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Some versions of gaussian elimination require you to reduce the right side of the system to the identity matrix rather than the row echelon form. What is the difference between this version and the one the lady above explained?

Trim End | 04:11

Question 5 | 01:38

Questions 6 & 7 | 03:45

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Question 5

01:38

Questions 6 & 7

03:45

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Watch the following video explain inverse matrices. pay attention to the inverse matrix part. you don't need to worry too much about rank, column space and nullspace. do pay attention about what it means for the inverse if the determinant is 0. do you have any questions?

1

how do you take the inverse of a 3x3 matrix

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notice one of the things about matrices is that A \cdot B \ne B \cdot A when we have A \cdot \vec{x}=\vec{v} and we multiply both sides by A^{-1} we have to multiply both sides _on the same side_. we call this right and left multiplication. what would it mean if you multiplied A^{-1} on the right on one side of the equation, and on the left on the opposite side?

1

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule:

which of the following describes D_x?

1

How did the 3blue1brown videos explain why A\cdot B \ne B\cdot A?

1

For a linear transformation to be considered linear, the transformation needed

1

I'd mentioned that we are ripping through matrices at a decent clip. so I will set the scene for the next week - what are some tell tale signs a set of simultaneous equations are not linear.

1

how would you deal with simultaneous inequalities differently than you would simultaneous equalities?

1

categorize your understanding

algorithm for gaussian elimination
when to use gaussian elimination
what is cramers rule
how do you find the A_x, A_y, A_z matrices you need for cramers rule
how to find the determinencts of those matrices for cramers rule
When to use cramers rule
how are linear transformations related to matrices?
how do you break apart fractions

Ive got this
im fuzzy
so confused

s3w7 gaussian elimination and Cramers rule.

Some versions of gaussian elimination require you to reduce the right side of the system to the identity matrix rather than the row echelon form. What is the difference between this version and the one the lady above explained?

Watch the following video explain inverse matrices. pay attention to the inverse matrix part. you don't need to worry too much about rank, column space and nullspace. do pay attention about what it means for the inverse if the determinant is 0. do you have any questions?

how do you take the inverse of a 3x3 matrix

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule:

which of the following describes D_x?

How did the 3blue1brown videos explain why A\cdot B \ne B\cdot A?

For a linear transformation to be considered linear, the transformation needed

I'd mentioned that we are ripping through matrices at a decent clip. so I will set the scene for the next week - what are some tell tale signs a set of simultaneous equations are not linear.

how would you deal with simultaneous inequalities differently than you would simultaneous equalities?

categorize your understanding

The form of a matrix that has all 0s on the bottom side of the diagonal is called "Row Echelon Form". Why do you think row echelon form might be useful?

other videos will want you to get your matrix to "reduced row echelon form" to make everything simple. What do you think reduced row echelon form is?

notice that you are allowed to swap rows if that makes your life easier. just make sure you swap the entire row.

Some versions of gaussian elimination require you to reduce the right side of the system to the identity matrix rather than the row echelon form. What is the difference between this version and the one the lady above explained?

To find D_x you have to

Note that finding the determinant for a 3 or 4 square matrix is also time consuming and fraught with mistakes, but this is what matrix calculators are for. no question - just wanted to highlight that.

Also note what will happen if the determinant of the original matrix is 0. What do you think you can say when the determinant is 0?

Watch the following video explain inverse matrices. pay attention to the inverse matrix part. you don't need to worry too much about rank, column space and nullspace. do pay attention about what it means for the inverse if the determinant is 0. do you have any questions?

how do you take the inverse of a 3x3 matrix

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule:

which of the following describes D_x?

How did the 3blue1brown videos explain why A\cdot B \ne B\cdot A?

For a linear transformation to be considered linear, the transformation needed

I'd mentioned that we are ripping through matrices at a decent clip. so I will set the scene for the next week - what are some tell tale signs a set of simultaneous equations are not linear.

how would you deal with simultaneous inequalities differently than you would simultaneous equalities?

categorize your understanding

The form of a matrix that has all 0s on the bottom side of the diagonal is called "Row Echelon Form". Why do you think row echelon form might be useful?

other videos will want you to get your matrix to "reduced row echelon form" to make everything simple. What do you think reduced row echelon form is?

notice that you are allowed to swap rows if that makes your life easier. just make sure you swap the entire row.

To find D_x you have to

Note that finding the determinant for a 3 or 4 square matrix is also time consuming and fraught with mistakes, but this is what matrix calculators are for. no question - just wanted to highlight that.

Also note what will happen if the determinant of the original matrix is 0. What do you think you can say when the determinant is 0?

s3w7 gaussian elimination and Cramers rule.

s3w7 gaussian elimination and Cramers rule.

Some versions of gaussian elimination require you to reduce the right side of the system to the identity matrix rather than the row echelon form. What is the difference between this version and the one the lady above explained?

Watch the following video explain inverse matrices. pay attention to the inverse matrix part. you don't need to worry too much about rank, column space and nullspace. do pay attention about what it means for the inverse if the determinant is 0. do you have any questions?

how do you take the inverse of a 3x3 matrix

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule: which of the following describes D_x?

How did the 3blue1brown videos explain why A\cdot B \ne B\cdot A?

For a linear transformation to be considered linear, the transformation needed

I'd mentioned that we are ripping through matrices at a decent clip. so I will set the scene for the next week - what are some tell tale signs a set of simultaneous equations are not linear.

how would you deal with simultaneous inequalities differently than you would simultaneous equalities?

categorize your understanding

Some versions of gaussian elimination require you to reduce the right side of the system to the identity matrix rather than the row echelon form. What is the difference between this version and the one the lady above explained?

Watch the following video explain inverse matrices. pay attention to the inverse matrix part. you don't need to worry too much about rank, column space and nullspace. do pay attention about what it means for the inverse if the determinant is 0. do you have any questions?

how do you take the inverse of a 3x3 matrix

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule: which of the following describes D_x?

How did the 3blue1brown videos explain why A\cdot B \ne B\cdot A?

For a linear transformation to be considered linear, the transformation needed

I'd mentioned that we are ripping through matrices at a decent clip. so I will set the scene for the next week - what are some tell tale signs a set of simultaneous equations are not linear.

how would you deal with simultaneous inequalities differently than you would simultaneous equalities?

categorize your understanding

The form of a matrix that has all 0s on the bottom side of the diagonal is called "Row Echelon Form". Why do you think row echelon form might be useful?

other videos will want you to get your matrix to "reduced row echelon form" to make everything simple. What do you think reduced row echelon form is?

notice that you are allowed to swap rows if that makes your life easier. just make sure you swap the entire row.

To find D_x you have to

Note that finding the determinant for a 3 or 4 square matrix is also time consuming and fraught with mistakes, but this is what matrix calculators are for. no question - just wanted to highlight that.

Also note what will happen if the determinant of the original matrix is 0. What do you think you can say when the determinant is 0?

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule:

which of the following describes D_x?

There is a whole 3blue1brown video explaining Cramer's rule geometrically. You can dig into that if you want, it decided that one was probably a bridge too far. you are welcomed to watch it if you want. For Cramer's rule:

which of the following describes D_x?