Math 260
Make the world a little better today.
Questions and Answers
Syllabus
Homework Solutions
Exam Solutions
Applications
IMT
Desmos matrix tool
Day 
Date 
Before class 
In class supplements 
Homework to turn in before next class 
HW Sol. 
Section 
Video clips (length) 
HO 
HW 


Mon 
8/17 
Intro 
Don't be a slacker (do go the extra mile) (7:38) 


Coins Activity 



Tue 
8/18 
1.1 
Row reduction (7:36) 
1.1 
1.1 2, 8 
Row reduction tool
Another row reduction tool 
HW 1 
Section 1.1, Page 10
2, 3, 8, 17, 18, 21  24,
26, 27, 30, 32 
HW1 
Thu 
8/20 
1.2 
Infinite solutions (17:42)
No solution (12:07) 
1.2 
1.2 10, 16 
Row reduction tool
Some possible echelon forms

HW 2 
Section 1.2, Page 21
1, 10  12, 15, 16, 19  23,
25  27, 30, 31, 32 
HW2 
Fri 
8/21 
1.3 
Vectors (5:48)
Linear combinations, span (20:34)

1.3 
1.3 6, 12 
Echelon forms: Span 
HW 3 
Section 1.3, Page 32
6  13, 17, 20  27, 29,
31 (see 29), 32 
HW3 


Mon 
8/24 
1.4 
Matrix equation Ax = b (through 7:00) (7:00) 
1.4 
1.4 4, 22 

HW 4 
Section 1.4, Page 40
1, 4, 9, 13, 15, 16,
21  25, 28, 30  32 
HW4 
Tue 
8/25 
1.5 
Parametric vector form (24:45) 
1.5 
None 

HW 5 
Section 1.5, Page 47
2, 3, 6, 14, 18, 23  25,
29  33, 35 
HW5 
Thu 
8/27 
1.6 
Balancing chemical equations (4:41)
Network flow (8:18)

1.6 
None 

HW 6 
Section 1.6, Page 54 3, 7  9, 11, 13  15 
HW6 
Fri 
8/28 
1.7 
Linear independence (15:45) 
1.7 
1.7 16  19 
Echelon forms: Linear Ind. 
HW 7 
Section 1.7, Page 60
2, 4, 11, 17  23,
25, 27, 34  39 
HW7 


Mon 
8/31 
1.8 
Linear transformations (13:52)
Image of a subset (18:10)

1.8 
1.8 2, 8 
Visualizing linear transformations 
HW 8 
Section 1.8, Page 68
2, 5, 8, 16, 18, 19, 21, 22,
29ab, 31, 33  35 
HW8 
Tue 
9/1 
1.9 
The matrix of a linear transformation (17:31)
Image of a linear transformation (16:36)
Rotations, compositions, etc. (10:03)

1.9 
1.9 6, 18 
Rotations, reflections, etc. 
HW 9 
Section 1.9, Page 78
1  3, 7, 16, 23  26,
28, 36 
HW9 
Thu 
9/3 
Review 

1.R 
None 

HW 10 
Section 1.S, Page 88
1 (don't turn in), 5  8
10  12, 14  18, 21, 22

HW10 
Fri 
9/4 
2.1 
Matrix multiplication (6:25)

2.1 
2.1 5, 8 
Excel matrix multiply, invert

HW 11 
Section 2.1, Page 100
2, 5, 7  9, 15, 16, 18, 20
21, 22, 24, 25 
HW11 


Mon 
9/7 
No class 



   
Tue 
9/8 
2.2 
Matrix inverses (14:14)
Use Matrix inverse to solve Ax = b (6:39)

2.2 
2.2 10 
Excel matrix multiply, invert
Row reduction tool
Derivation of 2 x 2 inverse formula

HW 12 
Section 2.2, Page 109
6, 7, 9, 10, 13, 16, 17,
19, 21, 22, 24, 35

HW12 
Thu 
9/10 
2.3 

2.3 
2.3 12 

HW 13 
Section 2.3, Page 115
5, 11  18, 20  24, 27, 41

HW13 
Fri 
9/11 
2.4, 2.5 
Block/partioned matrices (15:19)
LU factorization (8:22)

2.4 2.5 
None 
Elem. matrices for LU factorization 
HW 14 
Section 2.4, Page 121
6, 13, 25
Section 2.5, Page 129
2, 8, 9, 17

HW14 


Mon 
9/14 
2.6 
Inputoutput analysis (6:04) 
2.6 
None 
Excel consumption matrix example 
HW 15 
Section 2.6, Page 136
1  4, 7, 8, 10, 12

HW15 
Tue 
9/15 
Review 





Section 2.S, Page 160
Don't turn infor practice
1  4, 6, 8  11, 17  20


Thu 
9/17 
Exam 1 



   
Fri 
9/18 
3.1 
2 x 2 and 3 x 3 determinants (10:00)
n x n determinants: part 1 (18:39)
n x n determinants: part 2 (9:02)
Shortcut for 3 x 3 determinants (2:38)

3.1 
3.1 26, 30 
Determinant, etc. finder
3 x 3 inverse formula

HW 16 
Section 3.1, Page 167
2, 10, 16, 19, 20, 22, 26, 28
30, 34, 36, 38, 39, 40b, 41

HW16 


Mon 
9/21 
3.2 
Determinant after multiplying row (13:19)
(and correction) (2:51)
Determinant after add row to another (16:54)
Determinants after row operation (10:24)
Determinant of triangular matrix (8:06)
An example (9:12)

3.2 
3.2 6 
Why det(AB)=det(A)*det(B) 
HW 17 
Section 3.2, Page 175
2, 4, 16  20, 22, 24, 27,
28, 31  33, 36 
HW17 
Tue 
9/22 
3.3 
Determinant & area of a parallelogram (21:37)
Cramer's Rule (11:07)

3.3 
3.3 4 
Visualizing Cramer's Rule 
HW 18 
Section 3.3, Page 184
4, 6, 9, 10, 17, 18, 20, 22, 30

HW18 
Thu 
9/24 
4.1 
Vector spaces (23:28) 
4.1 
None 

HW 19 
Section 4.1, Page 195
2, 5, 6, 8, 16, 21, 23
24, 27, 28, 32, 33 
HW19 
Fri 
9/25 
4.2 
Null space (10:22)
Calculating null space (13:06)
Column space (10:39)
Visualizing column space (21:10)

4.2 
4.2 24 

HW 20 
Section 4.2, Page 205
2, 4, 7, 15, 23  26, 28
30, 39 
HW20 
Mon 
9/28 
4.3 
Linear independence and null space (9:31)
Bases for null space and column space (25:12)
Pivot columns, basis for column space (8:32)

4.3 
4.3 8 

HW 21 
Section 4.3, Page 213
2, 3, 5, 6, 8, 14, 19, 21  24
29  32

HW21 
Tue 
9/29 
4.4 
Coordinates (16:07) 
4.4 
4.4 4, 6  
HW 22 
Section 4.4, Page 222
4, 6, 13, 14, 18, 22,
23, 25, 27, 31

HW22 
Thu 
10/1 
4.5 
Nullity: dimension of nullspace (13:58)
Rank: dimension of column space (12:47)

4.5 
4.5 8 

HW 23 
Section 4.5, Page 229
4, 8, 11, 14, 19  21,
25, 26, 29  31

HW23 
Fri 
10/2 
4.6 

4.6 
4.6 2  
HW 24 
Section 4.6, Page 236
1, 2, 5  27

HW24 


Mon 
10/5 
4.9 
Origin of Markov Chains (7:14)
Markov Chain matrix (12:49)

4.9 
4.9 6  
HW 25 
Section 4.9, Page 260
2, 3, 6, 7, 12, 13, 17,
18, 20, 21

HW25 
Tue 
10/6 
5.1 
Eigenvectors & e.values (through 2:16) (2:16)

5.1 
5.1 4 
Visualizing eigenvectors in Excel
Eigenvalue/vector finder
Proof by induction video

HW 26 
Section 5.1, Page 271
3, 4, 6, 10, 13, 16, 17,
21  25, 27, 30, 33

HW26 
Thu 
10/8 
5.2 
How to find eigenvalues (4:35)
x→
is ≠ 0
Find eigenvalues example (5:38)

5.2 
5.2 2 

HW 27 
Section 5.2, Page 279
2, 8, 11, 16, 19, 21,
22, 25, 26

HW27 
Fri 
10/9 
5.3 
Matrix diagonalization (11:36) 
5.3 
5.3 2 
HW 5.3.33 in Wolfram Alpha 
HW 28 
Section 5.3, Page 286
2, 4, 5, 10, 11, 21  24
26  31

HW28 


Mon 
10/12 
Review 




HW 29 
Section 4.S, Page 262
1 (don't turn in), 2, 3,
8, 9, 11  13

HW29 
Tue 
10/13 
6.1 
Orthogonal complements (6:00) 
6.1 

HW 30 not due until Monday 
HW 30 
Section 6.1, Page 336
2, 3, 6, 7, 10, 14, 17,
19, 20, 22, 23, 25, 28, 30

HW30 
Thu 
10/15 
Exam 2 




 

Fri 
10/16 
5.6 
Predatorprey systems (5:08)

5.6 

Predatorprey spreadsheet 
  


Mon 
10/19 
5.6 
Predatorprey example (10:16) 


Predatorprey spreadsheet 
HW 31 
Section 5.6, Page 309
1, 2, 6  8, 10, 13

HW31 
Tue 
10/20 
5.7 

5.7 


  
Thu 
10/22 
5.7 




HW 32 
Section 5.7, Page 317
1, 2, 5  8

HW32 
Fri 
10/23 
No class 




  


Mon 
10/26 
5.8 
Power Method (8:59) 
5.8 

Power Method spreadsheet 
HW 33 
Section 5.8, Page 321
1, 4  6, 8, 9, 19  21

HW33 
Tue 
10/27 
6.2 
Orhogonal sets (11:55) 
6.2 


HW 34 
Section 6.2, Page 344
2, 3, 8, 9, 12, 14, 21,
23  25, 27  30

HW34 
Thu 
10/29 
6.3 
Orthogonal bases (5:59) 
6.3 


HW 35 
Section 6.3, Page 352
1, 6, 8, 12, 13, 16, 19  24

HW35 
Fri 
10/30 
6.4 
GramSchmidt Process (19:23) 
6.4 


HW 36 
Section 6.4, Page 358
3, 4, 7  10, 17  19

HW36 


Mon 
11/2 
6.5 
Least squares example (13:24) 
6.5 6.6 

Calculusbased least sq. derivation

HW 37 
Section 6.5, Page 366
3, 4, 7, 8, 10, 11, 13,
17, 18, 22, 25

HW37 
Tue 
11/3 
6.6 



Summary of Least Squares
Summary of Techniques for Ax = b
and Eight Examples

HW 38 
Section 6.6, Page 374
2, 7  10, 13, 16

HW38 
Thu 
11/5 
Review 







Fri 
11/6 
Exam 3 





 


Mon 
11/9 
6.7 
Inner Product Spaces (12:08) 
6.7 


HW 39 
Section 6.7, Page 382
2, 3, 5, 7, 13, 15  26

HW39 
Tue 
11/10 
6.8 
Intro to Fourier Series (13:52) 
6.8 

What are Fourier Series? (8:24)
What are Fourier Series? Another view (19:42) 
HW 40 
Section 6.8, Page 389
5  12

HW40 
Thu 
11/12 
7.1 
Column by row matrix multiplication (12:02)

7.1 


HW 41 
Section 7.1, Page 399
2, 4, 6, 8  10, 14, 17,
24  29, 31, 34, 35

HW41 
Fri 
11/13 
IM1 
Jacobi Method (6:50)
GaussSeidel Method (6:04) 
IM1 

Jacobi, GaussSeidel, SOR Spreadsheet 





Mon 
11/16 
IM2 

IM2  




Tue 
11/17 
TBA 







Thu 
11/19 
No class 
Work on takehome exam 



 

The final exam will be takehome and will be due by 4:00 pm (California time) Friday, November 22. 
