Statistics (Lectures 1-7) HT19
the SB1.2/SM2 course
page for Lectures 8-13 for information about the course, including
details of classes and labs.
Week 1 Part B 2017, 2016, 2015,…, Week 3 2018 Part B, MSc… Q’s from this
Lecture slides (to appear; schedule subject to possible adjustment)
lectures will cover the material in Sections 1 and 4 of these lecture
notes prepared by
Meinshausen. My slides
from last year are also available.
Permutation tests and Monte Carlo tests. Slides and Code
Two-sample Wilcoxon Rank Sum Test. Location tests. Slides
Confidence Intervals for location; One-sample Wilcoxon Signed Rank Test. Slides
Smoothing methods. Linear Smoothers. Slides and Code
Local Polynomial Smoothers. Boundary error. Slides and Code
Bandwidth and cross validation. Smoothing Splines and Penalised Regression. Slides and Code
Smoothing Splines and Penalised Regression (cont).
Multivariate Smoothers. Slides, Code
Splines and Multivariate
smoothing (corrected paragraph about n+4
post lecture, reload pdf to see)
Week 3 classes: PS1
Week 5 classes: PS2 - further typo in Q4 corrected 10/2/19 ( (x-xbar)/h)^2 so
h^2 not h.
Part B Lab session (for lectures 1-7)
Week 4, Weds 3-4:30pm. Assessed
Q1. Data: baseball;
There are also some supplementary exercises with
sample solutions which may
be of interest.
MSc Lab session (for lectures 1-7)
Week 3, Friday 11-1. Non-assessed practical
on Lectures 1-5. Practical;
Reading (for Lectures 1-7)
Wasserman, “All of Nonparametric Statistics”, Springer, 2005
Wasserman, “All of Statistics”, Springer, 2004.
D. Gibbons, “Nonparametric Statistical Inference”, Marcel Dekker, 1985
D. Gibbons and S. Chakraborti, “Nonparametric
Statistical Inference”, CRC Press, 2011
Givens and J.A. Hoeting, “Computational Statistic”s, 2nd edition, Wiley, 2012.
H. Randles and D. A. Wolfe, “Introduction to the
Theory of Nonparametric Statistics”, Wiley 1979