# Statistics Module for TiP Summer School

Some of the material relating to the statistics module given
in the TiP Summer School, November 2011
is available on this page.

The page is currently under development and material will be added to it over the coming days.

The computer package for the course is **R**. A brief introduction to **R** is given here. More information is given on the CRAN home page. This will allow you to download and install **R** for either a Windows or a Mac platform.

Detailed information on using **R** for matrix calculations is given in the notes Basics of Matrix Algebra. As well as describing the basics of matrix algebra, including numerical calculations ‘by hand’, for example of matrix multiplication and inversion, the notes give guidance on how to do numerical calculations in R and other basic operations. Answers to some of the exercises are given here.

### Course notes and Exercises

Complete course notes are here (pdf)

Exercises are here (pdf)
Solutions to Question 1 - 6 are here (pdf)

Script file with R-code for Questions 1 - 6 is here (pdf)

(Open script file from inside R or with Notepad or a text editor)

### 1: Introductory Statistics

Lecture slides (PowerPoint) are given here

Handout version of slides (Acrobat pdf) are here

### 2: Linear Models and Smooth Regression

Lecture slides (PowerPoint) are given here

Handout version of slides (Acrobat pdf) are here

### 3: Multivariate Methods

Lecture slides (PowerPoint) are given here

Handout version of slides (Acrobat pdf) are here

### 4: Tree-based Methods

Lecture slides (PowerPoint) are given here

Handout version of slides (Acrobat pdf) are here

### 5: Neural Networks

Lecture slides (PowerPoint) are given here

Handout version of slides (Acrobat pdf) are here

### 6: Introduction to Cluster Analysis and Time Series

Lecture slides (PowerPoint) are given here

Handout version of slides (Acrobat pdf) are here

### Lecture recordings

TiP One:1: Exploratory Data Analysis and Robust Summaries
TiP Two: 2: Clssical univariate tests, randomization & bootstrap tests

TiP Three: 3: R tips, linear models and scatterplot smoothing

TiP Four: 4: Introduction to multivariate techniques

TiP Five: 5: Multivariate methods continued with tree-based methods

TiP Six: 6: Introduction to Cluster Analysis and Time Series

Participants

Photo gallery

TiP HomePage link

This page is maintained by
the
Dr Nick Fieller
and was last updated on 31 December 2011.