MTH 309LR V: Introductory Linear Algebra

Fall 2020


Instructor: Alexandru Chirvasitu

Lectures: Office: 216 Mathematics Building
Office hours: TR 11:00 AM - 12:00 PM, remote
Email: achirvas AT buffalo.edu

TA: Yuqing Ma

Recitations: Office: 138 Mathematics Building
Office hours: Th 4:30pm-5:30pm, via Zoom waiting room
Email: yuqingma AT buffalo.edu

There is a sample Math 309 syllabus here. Ideally that'll be a pretty good indication of the material and pace of the class.

Note that the syllabus specifies a computer-based component to the course; this might entail some computer-assisted assignments or exercises (more on this below).


Unusual circumstances

I'll take this space to summarize some of the ways in which the current situation (i.e. having to teach and learn remotely) has resulted in somewhat unconventional arrangements for this course. Further details appear below, down the page.


Textbook

We're using the 3rd custom UB edition of Linear Algebra and its Applications by Lay, Lay and McDonald. You do need it, as I'll be assigning problems from it as homework by just telling you the problem numbers. The 3rd UB custom edition is apparently identical to the standard 5th edition of the same book.


Reading

I'll probably ask you to read some of the sections in the textbook before most lectures, so we're in sync. I'll post the reading assignments here, numbered as sections of the textbook. The date is that of the lecture, so please do the reading before that.

Due date Assignment Remarks
1 Th Sep 10

1.1, 1.2, 1.3, 1.4

2 Th Sep 17

1.5, 1.6, 1.7, 1.8

3 Th Sep 24

2.1, 2.2, 2.3, 2.8, 2.9

4 Th Oct 08

3.1, 3.2, 3.3, 4.1

5 Th Oct 15

4.2, 4.3, 4.4

6 Th Oct 22

4.5, 4.6, 5.1

7 Th Oct 29

5.3, 5.4

8 Th Nov 05

5.5, 6.1

9 Th Nov 19

6.2, 6.3

No classes the whole week of Nov 23

10 Th Dec 03

6.4, 6.5

11 Th Dec 10

7.1, 7.2

Supplementary material

On occasion, I'll post extra notes, comments, etc. in this space.


Homework

The homework does not count towards the course grade, but treat it as exam practice. It will mostly consist of problem lists from our textbook, posted either here or on UBLearns.

Due date Assignment Remarks
1 Th Sep 03

Get acquainted with SymPy and Jupyter notebook for the purpose of doing linear algebra computations.

That link is to a tutorial / walkthrough once you have the software; see this for a quick setup guide.

2 Th Sep 10
  • 1.1: 3, 15
  • 1.2: 2, 8
  • 1.3: 10, 11*, 16
  • 1.4: 11, 14*, 31

The star indicates my suggestion that you also work out that problem in a Jupyter notebook, for practice with that technology. You do not need to turn in that computer-assisted work in any way; it's just a good opportunity for you to practice.

To help you along, I have worked out problem 12 from section 1.3 as a model (it's a close version of problem 11).

You can either stare at the html page produced from the Jupyter notebook I worked out or, even better, download the notebook for yourselves and modify it on your own machine (if your browser tries to open it directly, right-click the link and select 'Save Link As' or some analogous option).

3 Th Sep 17
  • 1.5: 2, 14
  • 1.6: 11
  • 1.7: 6*, 10*, 18, 29
  • 1.8: 4, 8, 11

As before, the stars indicate I'm suggesting you take the opportunity to play with Python while trying to solve those problems. For guidance, I've worked out problem 5 from section 1.7; you can also get the notebook source to run on your own Jupyter notebook instance and modify.

4 Th Sep 24
  • 2.1: 9, 12
  • 2.2: 14, 31
  • 2.3: 7, 16
  • 2.8: 4, 18*
  • 2.9: 10*, 13*

As previously, stars mean try to also employ Python to work through these. HTML and source for a Jupyter notebook working out problem 14 from section 2.9.

Th Oct 01

midterm 1

No homework this week

No solutions will be available here for the midterm. Instead, if you want to check your answers, please run the problems yourselves through SymPy; this will be a good incentive to use that tool.

Th Oct 08

A bonus problem (with the Jupyter source).

It will be worth some extra credit, but it is optional and not turning it in will incur no penalty. Ignore it if you like.

5 Th Oct 08
  • 3.1: 13, 27
  • 3.2: 8*, 19
  • 3.3: 12*, 24*, 29
  • 4.1: 10, 11, 16

Starred means the same thing as always: please turn in the work you do "by hand", and take the problem as a good opportunity to practice your Python skills as well.

An example of how to do this for problem 13 from section 3.3, with the Jupyter source.

6 Th Oct 15
  • 4.2: 5, 7, 24
  • 4.3: 11, 13*, 16*
  • 4.4: 7*, 11, 14, 17

Here's me working out problem 18 from 4.3 in a Jupyter notebook

7 Th Oct 22
  • 4.5: 6*, 10, 14
  • 4.6: 6, 8, 24
  • 5.1: 5, 16*, 18*, 37*

Problem 38 section 5.1 with Jupyter source

Th Oct 29

Another bonus problem (with the Jupyter source).

As before: some extra credit, but it is optional.

8 Th Oct 29
  • 5.3: 4, 12, 24, 32, 35*
  • 5.4: 2, 12, 18, 20, 30*

Problem 31 section 5.4 with Jupyter source

9 Th Nov 05
  • 5.5: 4, 8, 16, 22, 28*
  • 6.1: 2, 10, 14, 25, 34*

Problem 27 section 5.5 with Jupyter source

Th Nov 12

midterm 2

No homework this week

The same goes Re: solutions as for midterm 1: if you want the correct answers, please ask a computer to work them out for you.

10 Th Nov 19
  • 6.2: 2, 12, 26, 30, 35*
  • 6.3: 2, 12, 20, 26*

Problem 25 section 6.3 with Jupyter source

11 Th Dec 03
  • 6.4: 4, 8, 16*, 25*
  • 6.5: 4, 8, 14, 16*, 20

Problem 24 section 6.4 with Jupyter source

12 Th Dec 10
  • 7.1: 8, 24*, 27, 30, 40*
  • 7.2: 4, 7, 11, 23, 24

Problem 39 section 7.1 with Jupyter source


On computer use

As mentioned above, this class has a "computer component", but it is by no means central: this is still a math course. For that reason, I cannot focus on the relevant computer tools directly during lectures, but I nevertheless urge you to take seriously the task of learning those tools, mentioned in the homework table above:

To illustrate the power these wield, let me illustrate a point (this will make more sense after we've learned some of the incipient material). Suppose I ask you to solve a system of linear equations (something we'll do often). You'l learn how to do this on your own, but you can have a computer do it for you: see how I got SymPy to do this for me here.

In fact, as an exercise, you might try your hand at replicating that notebook by yourself (after you've installed Jupyter Notebook and all of the rest).

Exams

We're having three of these: they will be conducted via UBLearns, and the dates are as follows.

The midterms are scheduled for our usual class time, but you will have at least 150% of that time between my uploading the exam and you having to turn it in, to account for delays caused by the technology, etc.

Please note that UB academic-integrity policy very much applies to this class, and the integrity of the exams is taken very seriously.


Grading


Some links


If you have any questions, don't hesitate to email me.

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