MATH-UA 252 – Numerical Analysis
Syllabus
Logistics
PDF available for free via the NYU Library
Grading: Homework (15%), Midterm 1 (25%), Midterm 2 (25%), Final exam (35%)
Course Description
An introduction to numerical analysis (the algorithms of continuous mathematics). We will cover classical and modern topics, including Monte Carlo methods, the solution of linear and nonlinear equations, floating point arithmetic and roundoff error, conditioning, interpolation, quadrature, numerical differentiation, numerical methods for ordinary differential equations, and the computation of eigenvalues.
The course will cover the analysis of numerical methods, but the homeworks will also have an implementation component.
Course Prerequisite
Exam policy
No notes, calculators, phones, etc. are allowed during exams.
Homework policy
Homework will be assigned weekly via Brightspace. Completed assignments will be uploaded in pdf form only to Gradescope. Programming assignments must be written in Python.
Late homework will not be accepted, but the two lowest homeworks will be dropped.
• You must make an honest attempt at homework problems before discussing them with anyone else.
• You must do the final write-up independently in your own words
• You may compare final answers with others to check for mistakes.