ST505 - Applied Nonparametric Statistics

Instructor: Dr. Wenbin Lu (email: lu@stat.ncsu.edu)
Lectures: M, W 10:15-11:30am, 1108 SAS Hall.  
Office Hour:
W 1:00-2:00pm, 5212 SAS Hall (or by appointment)

Syllabus: fall2016

 

TAWanying Ma (email: wma9@ncsu.edu)           

Office Hour: T 1:30-2:30pm and TH 10-11am, 1101 SAS Hall
 

Textbooks: Introduction to Modern Nonparametric Statistics by J. J. Higgins, Duxbury (Thomson)

 

Descriptions: The course provides an introduction to statistical estimation and inference methods that require relatively mild assumptions about the population distribution. Classical nonparametric hypothesis testing methods, Spearman and Kendall correlation coefficients, permutation tests, bootstrap methods, and nonparametric regressions will be covered.

 

 

Course Schedule

Week 1

Lecture 1: Introduction (HW1) solution

Note 1

Week 2

Lecture 2: One sample method

Note 2

Lecture 3: One sample method (HW2) solution

 

Week 3

Lecture 4: One sample method

Lecture 5: One sample method (HW3) solution

 

Week 4

Labor Day (no class)

Lecture 6: One sample method

Note 3

Week 5

Lecture 7: Two sample method (HW4) solution

Lecture 8: Two sample method

 

Week 6

Midterm #1, 09/19/2016 (Monday), in class

 

Lecture 9: Two sample method (HW5) solution

 

Week 7

Lecture 10: Two sample method

Lecture 11: Two sample method

 Note 4

Week 8

Lecture 12: K sample method (HW6) solution

Lecture 13: K sample method

 Note 5

Week 9

Lecture 14: K sample method

Lecture 15: Paired comparison and block design (HW7) solution

Week 10 

Lecture 16: Paired comparison and block design

Lecture 17: Paired comparison and block design (HW8) solution

 

Week 11

Midterm #2, 10/24/2016 (Monday), in class ---- coverage

Note 6

Lecture 18: Tests for trends and association 

Week 12 

Lecture 19: Tests for trends and association (HW9) solution

 

Lecture 20: Tests for trends and association 

 

Week 13 

Lecture 21: Tests for trends and association (HW10) solution

 

Lecture 22: Tests for trends and association 

Week 14

Lecture 23: Bootstrap methods (HW11) solution

Note 7

 

Lecture 24: Bootstrap methods

Week 15 

Lecture 25: Smoothing methods and robust model fitting 

Note 8

 

Thanksgiving  Holiday (no class)

Week 16

Lecture 26: Review and questions (November 30) coverage

Lecture 27: no lecture (preparation for final exam)

Final Exam

12/05/2016 (Monday), 8-11am, SAS Hall 5270