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:

• https://developers.google.com/edu/python/
• http://www.nyu.edu/lynda

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:
  • https://store.continuum.io/cshop/anaconda/
  Watch the 10 minute intro video to Pandas here:
  • http://pandas.pydata.org/
  Experiment with the above Python tutorials through Google or NYU Lynda.

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