Math 230 01 — Programming and Mathematical Problem Solving

Time and Place: MWF 8:30 - 9:20, South 336

Final Meeting: Wednesday, December 10, 8:00 - 11:00 AM

Instructor: Doug Baldwin
Office: South 307
Phone: 245-5659
Email: baldwin@geneseo.edu
Office Hours: Any time Monday through Friday, 8:00 AM to 5:00 PM, when I’m not committed to something else. See my Calendar for details and to make appointments electronically. You don’t need to make appointments to see me, but may if you want to be sure I’ll be available.

TA: Nick Lavigne (nsl3@geneseo.edu); office hours TBA

Web Pages:
Lecture Notes: http://www.geneseo.edu/~baldwin/math230/fall2014/lectures.php
Exercises: http://www.geneseo.edu/~baldwin/math230/fall2014/exercises.php

The purpose of computing is insight, not numbers - Richard Hamming

Hamming was a mathematician who is known for discovering some fundamental ideas about how information can be coded in computers—the computer on your lap may very well use “Hamming codes” to protect itself against memory errors. But, as shown by the quotation, Hamming realized that computing is important for more than its pragmatic applications: it can also be a source of deep insight. This course introduces you to computer programming as a way to develop insight into mathematics.

In particular, this course will teach the rudiments of programming in a language called “Matlab.” Matlab is a popular tool for programming mathematical calculations, and you will certainly learn to write such programs. But as you practice programming by using it to solve various mathematical problems, you will also learn a lot about what the mathematics inside those problems means and how it works. Both of these lessons—how to program time-consuming calculations, and how to deepen your understanding of mathematics by doing so—will stand you in good stead in future mathematics courses, and in any even remotely mathematical career you might pursue.

Corequisite(s): Math 222

Learning Outcomes: On completing this course, students who meet expectations will be able to…

• Write code using for/do loops, while constructions, conditional statements (if, then, else), and make use of logical constructs in the context of mathematics
• Do basic 2- and 3-D plotting
• Write code in the prescribed language for a number of algorithms for the topics covered given pseudo-code, or modify a given code to perform an indicated task
• Create functions or subroutines
• Debug code in the prescribed language at an appropriate level, and decide if they can make their code more efficient
• Verify the correctness of a solution or decide whether the result is an acceptable approximation to the solution
• Identify algorithms with which to solve mathematical problems
• Write programs from the underlying algorithms, and demonstrate the ability to employ good commenting and coding techniques

Books and Other Resources

Textbook

The (required) textbook for this course is

Attaway, Matlab: A Practical Introduction to Programming and Problem Solving (3rd ed.)

It is available from the College bookstore and other sources.

Software

You will need to install a copy of Matlab on your own laptop. You can get copies for either Macintosh or PC computers from Geneseo, at

http://software.geneseo.edu

(Scroll down through the list of software until you find Matlab)

Instructions for installing Geneseo’s Matlab on your own computer are at

https://wiki.geneseo.edu/display/cit/MatLab+R2014a+Installation+Guide

The copy of Matlab you get from Geneseo will only run on a computer connected to the Geneseo network. If you commonly work off campus, you can use a “virtual private network” (VPN) to make it look like your computer is on Geneseo’s network. The VPN is simply a piece of software you install on your computer. Windows users can download the “Cisco VPN” package from software.geneseo.edu. Macintoshes come with a VPN pre-installed; follow the instructions at https://wiki.geneseo.edu/display/cit/Setting+up+Geneseo+VPN+on+Mac+OS+X+10.6+Snow+Leopard+to+10.9+Mavericks to activate it.

Online Resources

From time to time I will refer you to online videos that complement the material in the textbook. Most of these videos will be optional, you can watch them or not as you see fit. A few will be required, as they will provide information that is not in the textbook.

Many of the videos come from a short Matlab course online at the University of Edinburgh:

http://www.see.ed.ac.uk/teaching/courses/matlab/

A few that I have developed are at

https://cloud.ensemblevideo.com/app/sites/index.aspx?destinationID=IlO-D-b-vUWVkAsj2Is5Zg

The official web site for Mathworks, the developers of Matlab, is

http://www.mathworks.com/

Finally, materials from a course similar to this that I taught last semester are at

http://www.geneseo.edu/~baldwin/csci120/spring2014

Course Schedule

The following dates are best estimates. They may well change as students’ actual needs become apparent. Refer to the Web version of this syllabus for the most current information, I will keep it as up-to-date as possible:

Grades and Such

Your grade for this course will be calculated from your grades on exercises, exams, etc. as follows:

In determining numeric grades for individual assignments, questions, etc., I start with the idea that meeting my expectations for a solution is worth 80% of the grade. I award the other 20% for exceeding my expectations in various ways (e.g., having an unusually elegant or insightful solution, or expressing it particularly clearly, or doing unrequested out-of-class research to develop it, etc.); I usually award 10 percentage points for almost anything that somehow exceeds expectations, and the last 10 for having a solution that is truly perfect. I deliberately make the last 10 percentage points extremely hard to get, on the grounds that in any course there will be some students who routinely earn 90% on everything, and I want even them to have something to strive for. I grade work that falls below my expectations as either meeting about half of them, three quarters, one quarter, or none, and assign numeric grades accordingly: 60% for work that meets three quarters of my expectations, 40% for work that meets half of my expectations, etc. This relatively coarse grading scheme is fairer, more consistent, and easier to implement than one that tries to make finer distinctions.

This grading scheme produces numeric grades noticeably lower than traditional grading does. I take this into account when I convert numeric grades to letter grades. The general guideline I use for letter grades is that meeting my expectations throughout a course earns a B or B+. Noticeably exceeding my expectations earns some sort of A (i.e., A- or A), meeting most but clearly not all some sort of C, trying but failing to meet most expectations some sort of D, and apparently not even trying earns an E. I set the exact numeric cut-offs for letter grades at the end of the course, when I have an overall sense of how realistic my expectations were for a class as a whole. This syllabus thus cannot tell you exactly what percentage grade will count as an A, a B, etc. However, in my past courses the B+ to A- cutoff has typically fallen somewhere in the mid to upper 80s, the C+ to B- cutoff somewhere around 60, and the D to C- cutoff in the mid-40s to mid-50s. I will be delighted to talk with you at any time during the semester about your individual grades and give you my estimate of how they will eventually translate into a letter grade.

Policy on Late and Missed Work

I will accept exercise solutions that are turned in late, but with a 10% per day compound late penalty. For example, homework turned in 1 day late gets 10% taken off its grade; homework turned in 2 days late gets 10% taken off for the first day, then 10% of what’s left gets taken off for the second day. Similarly for 3 days, 4 days, and so forth. I round grades to the nearest whole number, so it is possible for something to be so late that its grade rounds to 0.

I do not normally give make-up exams.

I may allow make-up exams or extensions on exercises if (1) the make-up or extension is necessitated by circumstances truly beyond your control, and (2) you ask for it as early as possible. At my discretion, I may require proof of the “circumstances beyond your control” before granting a make-up exam or extension.

Policy on Collaboration

Assignments in this course are learning exercises, not tests of what you know. You are therefore welcome to work on them in small groups, unless specifically told otherwise in the assignment handout—a well-managed group makes a successful, and thus more educational, project more likely.

In order to avoid confusion when people work together, please indicate clearly what work is yours and what comes from other sources on everything you hand in. The appropriate “indication” depends on how much work is yours and how distinguishable it is from your collaborators’. At one extreme, if a group of people work together on all parts of an assignment, they could hand in one solution with all their names, and a brief statement of what each person contributed, on it. At the other extreme, if you do most of an assignment on your own but get a specific idea from someone else, you might just include a comment or footnote to the effect of “this idea comes from Betty Smith” in whatever you hand in. The bottom line is that everything you take credit for must include some identifiable contribution by you, and you should never claim credit for work or ideas that aren’t yours. I’ll be glad to advise you on what I consider appropriate forms and acknowledgements of collaboration in specific cases if you wish.

Please note that tests are tests of what you know, and working together on them is explicitly forbidden. This means that if you take advantage of the collaboration policy to avoid doing your share of the work on the exercises, you will probably discover too late that you haven’t learned enough to do very well on the tests.

I will penalize violations of this policy. The severity of the penalty will depend on the severity of the violation.

Accomodations

SUNY Geneseo will make reasonable accommodations for persons with documented physical, emotional, or cognitive disabilities. Accommodations will be made for medical conditions related to pregnancy or parenting. Students should contact Dean Buggie-Hunt in the Office of Disability Services (tbuggieh@geneseo.edu or 585-245-5112) and their faculty to discuss needed accommodations as early as possible in the semester.