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Schedule
Staff
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Index
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All readings are from the textbook unless otherwise noted. Upcoming readings are adjusted after the fact, based on what was actually covered during lecture.
| Date | Topics |
| Jan 18 | Introduction, Taylor series § 1.1 Tying your shoes |
| Jan 23 | Taylor error § 1.2
[Matlab transcript] |
| Jan 25 | Polynomials, § 1.3 Floating-point representation § 2.1 |
| Jan 30 | Floating-point representation § 2.2-2.3
[Matlab transcript] |
| Feb 1 | Floating-point representation § 2.2-2.3
[Matlab transcript] |
| Feb 6 | Floating-point representation § 2.3-2.4 |
| Feb 8 | Floating-point representation § 2.4 Root finding § 3.1-3.2 |
| Feb 13 | Root finding (bisection) § 3.1-3.2
[Matlab transcript] |
| Feb 15 | Root finding (Newton) § 3.2 |
| Feb 20 | Root finding (Newton) § 3.2
[Matlab transcript] |
| Feb 22 | Root finding (Newton, secant) § 3.2-3.3
[Matlab transcript] |
| Feb 27 | Fixed point iteration § 3.4
[Matlab transcript] |
| Mar 1 | Fixed point iteration § 3.4 Ill-behaving problems § 3.5 |
| Mar 6 | Ill-behaving problems § 3.5 [Matlab transcript] |
| Mar 8 | Polynomial interpolation § 4.1 |
| Mar 20 | Polynomial interpolation § 4.1 [Matlab transcript] |
| Mar 22 | Midterm |
| Mar 27 | Error in polynomial interpolation § 4.2 [Maple example] |
| Mar 29 | Error in polynomial interpolation § 4.2 Midterm discussion [Interpolation applet] |
| Apr 3 | Spline interpolation § 4.3 |
| Apr 5 | Spline interpolation § 4.3 [Matlab example] |
| Apr 10 | Numerical integration § 5.1 |
| Apr 12 | Errors in numerical integration § 5.2 [Matlab example] |
| Apr 17 | Numerical differentiation § 5.4 [Matlab example] |
| Apr 19 | Numerical differentiation § 5.4 Solving linear systems § 6.1-6.3 |
| Apr 24 | Solving linear systems § 6.3-6.5 [Matlab example] |
| Apr 26 | Solving linear systems § 6.6 [Matlab example] |
| May 1 | Solving linear systems § 6.6 Least squares approximation § 7.1 [Matlab example] |
| Friday, May 5 | Final exam (4pm; 80 minutes) |
There will be roughly 6-7 written/programming assignments (in MATLAB). MATLAB is available on PCs in Rutgers public computer labs (such as ARC), and on remus. You can also purchase the student version from the bookstore.
All work on the assignments (written or programming) must be your own - there is to be no "group work". However, you are encouraged to discuss the course material with other students. We endorse and follow the DCS Academic Integrity Policy. Read it. If we have reason to believe you have not done your own work, we reserve the right to give you a brief oral exam about that assignment, and adjust your grade accordingly. Should you have any questions about this, please ask the instructor.
Each day (or partial day) late discounts your grade by 33.3% (so that a submission 48 hours late is worthless; however, it will still be graded). On occasion, the late period will be shortened (in order to hand back graded assignments before an exam); if this is the case the last day to hand in late will be stated on the homework webpage.
For physical handins, it is your responsibility to find the professor or TA to correctly register the time you hand in. Please don't just leave your assignment under a door.