Applied Linear Algebra and
Numerical Analysis
Instructor: Niall Mangan, niallmm at uw dot edu Office hours: Lewis 116, Mon 4:305:30pm, Thurs 9:3010:30am, Friday 1:302:30pm Teaching Assistant: Felix Xiaofeng Ye, yexf308 at uw dot edu Office hours: Lewis 115 Tuesday 35pm
We Meet: MWF 12:301:30 in MLR 301
Announcements and Discussion  Solution set for Final exam. Final grades are also posted on Catalyst.
 Grades for Final exam are posted.
 Grades and Feedback for PS7 are available. Problem Set 7 Solutions Statistics without zeros:
Mean  43  Median  47  Mode  51  Min  7  Max  52  Std. Dev.  11.86

 Office Hours by appointment only Exam week.
 Grades and Feedback for PS6 are available. Please check your feedback (there were some errors earlier, which have been corrected now).
Mean  45  Median  48  Mode  52  Min  27  Max  52  Std. Dev.  7.56 
 Final exam review sheet
 Problem set 7 is posted at the catalyst dropbox with corrections. Deadline has been extended to Friday 6/3/2016.
 Office hours 6/1/2016 4:005:30pm.
 Problem Set 5 solution set.
 Grades and feedback for PS5 are available. There were a few zeros, please check your feedback! Stats:
Mean  58  Median  60  Mode  60  Min  36  Max  62  Std. Dev.  5.7 
 Live broadcast Office hours have started. Send me an email if you can't connect.
 Videos replacing Monday 5/23 Lecture
 Office Hours rescheduled: Sunday 5/22 @ 4:305:30pm PT (link to Hangouts on Air here). You can start posting questions on the Q/A Hangouts app ahead of time. No office hours Friday 5/20 or Monday 5/23.
 Problem set 6 is posted.
 Problem set 5 is posted. I have added the .tex file and update 3b.
 Office hours rescheduled: I will have office hours Wednesday 5/18 from 1:302:30 pm.
 Grades are posted through catalyst. Go here to view yours: https://catalyst.uw.edu/gradebook/niallmm/97908
 If you have not picked up your midterm, come to office hours. I will also bring them to next class 5/11/2016.
 Answer key for Midterm. Please visit Felix during Office hours this week if there is a significant concern about your grade: Thurs 9:3010:30am, Friday 1:302:30pm.
 Feedback is available on PS4 in the dropbox I gave you for PS1. The stats (including bonus, but not including those who did not turn in homework) are:
Mean
 45  Median  48  Mode  48  Min  8  Max  52  Std. Dev.  8.99
 There was a typo on the Midterm Review. I have updated the pdf. Midterm Review  Solution set for PS3 is available. In this solution set I gave you more directions on how to submit corrections for 1/2 points back on PS3. The deadline for corrections for 1/2 points has past for PS2, so I am also posting the code for that problem set.
 Midterm Review is posted.
 Feedback on PS3 is available in the dropbox I gave you for PS1. The stats (including bonus, but not including those who did not turn in homework) were:
Mean
 46.7  Median  49  Mode  50  Min  25  Max  52  Std. Dev.  6.39

 Partial solution set for PS2 is available. Make up for PS2 for half credit are due Wed 4/27. I have not provided code for the algorithms as it would be too difficult to grade make up solutions.
 Problem Set 4 is posted.
 Feedback on PS2 is available in the dropbox I gave you from PS1. The stats (including bonus, but not including those who did not turn in homework) were:
Mean
 41.31  Median  44  Mode  49.0  Min  17  Max  52  Std. Dev.  8.88 
 Feedback on PS1 is posted. Go to the dropbox where you turned it in and click on the link. The stats for grades on PS1 (including bonus) were:
Mean  55.1  Median  58.0  Mode  61.0  Min  18.0  Max  65.0  Std. Dev.  9.39

 Problem set 3 is now posted. It will be due at 12:30PM on 04/20/2016.
 There is a correction to problem 2.3c on PS2. You should analyze the order of convergence by looking at the plot of error(n+1) vs error(n). .
Here is the code you can use to generate the plot if you have the error vector:
figure(3) loglog(esave(1:N1), esave(2:N), 'o') xlabel('error at n') ylabel('error at n+1') title('determining order of convergence')
Using this, you can analyze the slope and determine order of convergence. The Problem set in the link has also been updated.  Solution set for problem set 1 (I only included the .m files for the last problem):
 I made a video reviewing fixed point iteration, that might help you get started on Problem Set 2. I also made a video going through a solution to problems set 1 problem 2.4 c and d. It's a bit long and there is a long pause in the middle. But I don't have time to do much editing... sorry!
 Homework 2 is assigned. Download the materials here.
 Homework 1 is due today. Make sure your zip file is uploaded! Email me if you are having technical difficulties.
 Latex template for homework now available! Download zip file with latex file for problem set, a matlab script example, and plot file.
 Office hours now posted ^ above
 Problem Set 1 Assigned (see left column)
 If you have never used Matlab before the intro video, intro to the workspace video, and video on scripts and functions will be helpful for the first homework.
 Homeworks should be submitted to the Catalyst drop box folder here.
 Due to the large number of students in the class we will not be answering homework or coding related questions via email. Please visit the forum to discuss or scheduled office hours.
 Discussion Board Here. Felix and I will monitor the board and provide more resources when you show you are interested or stuck on particular topics, and other students do not respond within 24 hours. You are also encouraged to discuss topics and problems in study groups. However, you must write up your own solutions. Please do not post solutions on the discussion board.
Prerequisites: Math 126 or Q SCI 293
Schedule:  Homework Deadlines: Homeworks will be due on Wednesdays a week after they are assigned. I will keep the topics and homework schedule updated here.
 Exams:
 Midterm: Wednesday May 4, 2016; 12:301:30 (in class); MLR 301
 Final: Thursday June 9, 2016; 8:3010:20AM; MLR 301
 UW Academic Calendar
Course Description: Nearly every discipline with a quantitative component including engineering, physical sciences, social sciences, finance, computer graphics, big data, and machine learning rely on linear algebra. Numerical computation greatly enables modeling the data analysis in these fields. In order to utilize linear algebra and computing for problem solving, it is essential to understand how to set up problems (in the linear framework and numerically), determine when well defined solutions exist, write programs and algorithms in MATLAB to solve these problems, evaluate whether the algorithm will find the solution efficiently, and evaluate the accuracy of the computation. For a detailed list of topics please go here.
Textbook & Resources: No textbook will be required for this course. We will supply class notes for each class here.
Here are a few other freely available texts, if I am directly referencing them I will let you know: If you want to purchase a textbook as a reference, I really like the explanations in Burden and Faires Numerical Analysis (9th ed). A cheaper alternative that Prof. Kutz notes are based on is Matthews and Fink (3rd ed), but it is denser. For a very focused quick read, I originally learned Numerical Methods from Peter Turner's Guide to Scientific Computing also fairly inexpensive.
Homework and Computing Resources
Matlab/Ocatave Resources: You need to obtain a copy of or access to MATLAB. You can either buy a student copy for about $100 at the UW Bookstore, get a $30 total headcount license from the link below (expires 9/1/2016), or use the computer labs/remote access listed below. LaTeX Resources for typesetting
Homework Policy and Grading
 To encourage you to go over material you had difficulty with, you have an opportunity to make up half the lost points on homework. Within one week of getting your homework back you should find or write an equivalent homework problem, explain why it is an equivalent problem (or why it has changed), and provide a solution. Your updated solution must show that you now understand the concept(s) covered by the problem, and have not just switched out numbers.
 We strongly encourage you to typeset your problem sets and recommend LaTeX, doing so will earn up to 24 bonus points. Typesetting is a useful skill, and will also help us grade more efficiently.
 Problem sets must be turned at the beginning of class (12:30pm on Wednesdays) in either hard copy or digitally through a shared dropbox folder. Code, submitted through dropbox and included in the problem set write up, will usually be requested.
Your grade will be determined by 7 weekly problem sets, and 2 exams.
The points will be as follows: 7 problem sets worth 50 pts each = 350 pts 2 exams (1 midterm + 1 final) worth 100 pts each = 200 pts Max points: 550 pts
Bonus: 10 pts for typesetting first problem set + 2pts for typesetting subsequent 7 problem sets = 24 total bonus points from typesetting possible (not to exceed 600 max points)
Group work and Academic Honesty policy: You are encouraged to discuss and work in groups to solve problem sets.
You must write up your own solution and your own code. Copy, pasting, and editing will be considered plagiarism. Do not be a cheater, it does not help you learn the material and I will have you do something harder to make up the grade, give you a zero, and/or report you for academic misconduct depending on the situation.
Please read the UW policy here. By staying registered in the class you indicate your acceptance of all its terms. We do not accept late homework or absence without official reasons (medical, etc.) approved by a student dean. If you miss class, please coordinate with colleagues to find out what you missed (do not email the professor to help you catch up).

