Mathematical Statistics

Course number: MATH-UA 234
Semester: Spring 2014
Time & Location: Tues & Thurs, 3:30pm - 4:45pm in WWH 512
Instructor: Mike O'Neil (oneil@cims.nyu.edu)
Office hours: Tues 10:00am - 11:00am & Wed 4:00pm - 5:00pm in WWH 1105A
   
Recitation: Fri 2:00pm - 3:15pm in WWH 512
Teaching assistant: Sinziana Datcu (datcu@cims.nyu.edu)
Course description

This course is intended as a thorough mathematical introduction to the theory of statistics, intended to be taken after sufficiency in probability is obtained at the level of Math 233: Theory of Probability. Topics covered in this class will include: sampling theory, hypothesis testing, point (parameter) estimation, regression, tests of significance, likelihood methods, and Bayesian statistics. Topics in computational statistics will be covered using Python and Pandas.

Download a copy of the syllabus here.

Materials

The course text is All of Statistics by Larry Wasserman. It can be accessed online through Springer from NYU connected computers at: http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-40272-7

Several other sources might be useful for studying and reference:

  • Freedman, Pisani, and Purves, Statistics.
  • Rice, Mathematical Statistics and Data Analysis.
  • McKinney, Python for Data Analysis
  • Schaum's Outline of Statistics
  • Schaum's Outline of Probability and Statistics
  • Durrett, The Essentials of Probability

The following Python tutorials might be useful:

Announcements

Important information for the course will appear below as necessary.

  • The midterm is scheduled for in-class on Thursday, March 13th.
  • The final is scheduled by NYU and is Thursday, May 15th, 4:00pm-5:50pm in room WWH 312.
Homework assignments

Below is a list of homework assignments along with the due date. Remember that each assignment is due at the beginning of class on the due date.

  • Install (or get access to) Python and Pandas. I recommend installing Anaconda as a one-stop shopping experience to getting Python up and running on your machine: Watch the 10 minute intro video to Pandas here: Experiment with the above Python tutorials through Codeacademy and Google.
  1. (Due 2/14/14) Problems from All of Statistics:
    • Section 1.10: 15, 19
    • Section 2.14: 4, 9, 14, 16, 20, 21
  2. (Due 2/21/14) Problems from All of Statistics:
    • Section 2.14: 17
    • Section 3.8: 1, 3, 4, 6, 7
  3. (Due 2/28/14) Problems from All of Statistics:
    • Section 3.8: 8, 10, 13, 15, 16
  4. (Due 3/7/14) Problems from All of Statistics:
    • Section 3.8: 17, 21, 22
    • Section 5.8: 2, 4
  5. (Due 3/14/14) Problems from All of Statistics:
    • Section 2.14: 8
    • Section 3.8: 2
    • Section 5.8: 6, 14
    • Section 6.6: 1, 3
    • Section 9.14: 1
  6. (Due 4/4/14) Problems from All of Statistics:
    • Section 9.14: 2 (ignore part d), 4, 5, 6 (ignore part d)
  7. (Due 4/11/14) Click here for the PDF
  8. (Due 4/18/14) Problems from All of Statistics:
    • Section 10.11: 2, 5, 6, 8, 13
  9. (Due 4/25/14) Problems from All of Statistics:
    • Section 11.12: 1, 3, 5, 6
  10. (Due 5/2/14) Problems from All of Statistics:
    • Section 13.10: 1, 2, 4, 5
  11. (Due 5/9/14) Problems from All of Statistics:
    • Section 20.7: 1, 4, 8