|
|
(35 intermediate revisions by the same user not shown) |
Line 3: |
Line 3: |
|
==Boris== |
|
==Boris== |
|
|
|
|
|
====Try to Avoid the Einstellung Effect==== |
|
====Be Efficient==== |
|
|
|
|
|
By this point in the course, we become good at solving systems of linear equations. However, we should not use this same old |
|
By this point in the course, we become good at solving systems of linear equations. However, we should not use this same old problem-solving strategy over and over if a more efficient one exists. Consider the following problems: |
|
|
|
|
problem-solving strategy over and over if a more efficient one exists. Consider the following problems: |
|
|
|
|
|
|
|
|
|
Line 16: |
Line 14: |
|
|
|
|
|
|
|
|
|
::::<math>c_1(1, 4, -6) + c_2(1, 5, 8) + c_3 (2, 1, 1) + c_4(0, 1, 0) = (0, 0, 0)</math> where <math>c_i \in R</math>.
|
|
:::<math>c_1(1, 4, -6) + c_2(1, 5, 8) + c_3 (2, 1, 1) + c_4(0, 1, 0) = (0, 0, 0)</math> where <math>c_i \in R</math>. |
|
|
|
|
|
|
|
|
|
Yet there is a less time-consuming approach that relies on two observations: |
|
Yet there is a less time-consuming approach that relies on two observations: |
|
|
|
|
|
|
|
:(1) The dimension of <math>R^3</math> is <math>3</math> so the size of a basis is also <math>3</math>. |
|
:(1) The dimension of <math>R^3</math> is <math>3</math> so the size of a basis is also <math>3</math>. |
|
⚫ |
:(2) No linearly independent set can have more vectors than a generating set (by the Replacement Theorem) . |
|
⚫ |
Since a basis is a generating set and the size of <math>S</math> is <math>4</math>, then the Replacement Theorem tells us that |
|
⚫ |
<math>S</math> cannot be linearly independent. Hence, the problem can be solved without solving any linear equations. |
|
|
|
|
⚫ |
:(2) No linearly independent set has more vectors than a generating set (by the Replacement Theorem) |
|
|
|
|
|
|
|
|
|
|
⚫ |
'''Q2''': Determine if the polynomials <math>x^3 - 2x ^2 + 1, 4x^2-x+3, 3x-2 </math> generate <math>P_3(R)</math>. |
⚫ |
Since a basis is a generating set and the size of <math>S</math> is <math>4</math>, then the Replacement Theorem tells us that |
|
|
|
|
|
|
⚫ |
Once again, we can solve a linear equation but we do not have to. Observe: |
⚫ |
<math>S</math> cannot be linearly independent. Hence, the problem can be solved without solving any linear equations. |
|
|
⚫ |
:(1) The dimension <math>P_3(R)</math> is <math>4</math> so the size of a basis is also <math>4</math>. |
|
⚫ |
:(2) No generating set can have fewer vectors than a basis (by a Corollary to the Replacement Theorem). |
|
⚫ |
Since there are only <math>3</math> polynomials, then the Corollary tells us that it cannot generate <math>P_3(R)</math> . Once again, we used a more efficient strategy. |
|
|
|
|
|
|
|
|
|
⚫ |
====Extending a Linearly Independent Set to a Basis==== |
|
|
|
|
|
|
'''Boris's tip (for concrete sets and vector spaces only)''': |
⚫ |
'''Q2''': Determine if the polynomials <math>x^3 - 2x ^2 + 1, 4x^2-x+3, 3x-2 </math> generate <math>P_3(R)</math>. |
|
|
|
|
|
⚫ |
Once again, we can solve this linear linear equation but we do not have to. Observe: |
|
|
|
|
|
|
|
⚫ |
:(1) The dimension <math>P_3(R)</math> is <math>4</math> so the size of a basis is also <math>4</math>. |
|
|
|
|
|
|
|
If a problem requires us to extend a linearly independent set to a basis, then the easiest approach is to add vectors from the |
⚫ |
:(2) No generating set has fewer vectors than a basis (by a Corollary to the Replacement Theorem). |
|
|
|
standard ordered basis. Here is an example: |
|
|
|
|
|
|
|
|
|
|
Let <math>S = \{(-3, -6, 0), (0, 7, 0)\}</math> be a linearly independent subset of <math>R^3</math>. To extend <math>S</math> to a basis, add vectors from <math>\{(1, 0, 0), (0, 1, 0), (0, 0, 1)\}</math>. The only question is which vector(s) should we add? |
⚫ |
Since there are only <math>3</math> polynomials, then the Corollary tells us that there is no way that it generates <math>P_3(R)</math>. |
|
|
|
|
|
|
====Don't be Too Lazy==== |
|
|
|
|
|
|
|
We see that both vectors in <math>S</math> have a <math>0</math> as the third component so a safe choice is to add <math>(0, 0, 1)</math>. Since <math>R^3</math> has a dimension of <math>3</math>, then <math>\{(-3, -6, 0), (0, 7, 0), (0, 0, 1)\}</math> is a basis of <math>R^3</math>. |
⚫ |
====Extending Linearly Independent Sets==== |
|
|
|
|
|
|
==Nikita== |
|
==Nikita== |
Welcome to Math 240! (additions to this web site no longer count towards good deed points)
|
#
|
Week of...
|
Notes and Links
|
1
|
Sep 8
|
About This Class, What is this class about? (PDF, HTML), Monday, Wednesday
|
2
|
Sep 15
|
HW1, Monday, Wednesday, TheComplexField.pdf,HW1_solutions.pdf
|
3
|
Sep 22
|
HW2, Class Photo, Monday, Wednesday, HW2_solutions.pdf
|
4
|
Sep 29
|
HW3, Wednesday, Tutorial, HW3_solutions.pdf
|
5
|
Oct 6
|
HW4, Monday, Wednesday, Tutorial, HW4_solutions.pdf
|
6
|
Oct 13
|
No Monday class (Thanksgiving), Wednesday, Tutorial
|
7
|
Oct 20
|
HW5, Term Test at tutorials on Tuesday, Wednesday
|
8
|
Oct 27
|
HW6, Monday, Why LinAlg?, Wednesday, Tutorial
|
9
|
Nov 3
|
Monday is the last day to drop this class, HW7, Monday, Wednesday, Tutorial
|
10
|
Nov 10
|
HW8, Monday, Tutorial
|
11
|
Nov 17
|
Monday-Tuesday is UofT November break
|
12
|
Nov 24
|
HW9
|
13
|
Dec 1
|
Wednesday is a "makeup Monday"! End-of-Course Schedule, Tutorial
|
F
|
Dec 8
|
The Final Exam
|
Register of Good Deeds
|
Add your name / see who's in!
|
|
|
Boris
Be Efficient
By this point in the course, we become good at solving systems of linear equations. However, we should not use this same old problem-solving strategy over and over if a more efficient one exists. Consider the following problems:
Q1: Determine if is linearly independent in .
We can solve this linear equation to find the answer:
- where .
Yet there is a less time-consuming approach that relies on two observations:
- (1) The dimension of is so the size of a basis is also .
- (2) No linearly independent set can have more vectors than a generating set (by the Replacement Theorem).
Since a basis is a generating set and the size of is , then the Replacement Theorem tells us that
cannot be linearly independent. Hence, the problem can be solved without solving any linear equations.
Q2: Determine if the polynomials generate .
Once again, we can solve a linear equation but we do not have to. Observe:
- (1) The dimension is so the size of a basis is also .
- (2) No generating set can have fewer vectors than a basis (by a Corollary to the Replacement Theorem).
Since there are only polynomials, then the Corollary tells us that it cannot generate . Once again, we used a more efficient strategy.
Extending a Linearly Independent Set to a Basis
Boris's tip (for concrete sets and vector spaces only):
If a problem requires us to extend a linearly independent set to a basis, then the easiest approach is to add vectors from the
standard ordered basis. Here is an example:
Let be a linearly independent subset of . To extend to a basis, add vectors from . The only question is which vector(s) should we add?
We see that both vectors in have a as the third component so a safe choice is to add . Since has a dimension of , then is a basis of .
Nikita