Lectures and tutorials are at the following times:

**Lecture**: Tuesday 6-8pm, E3B 218

**Tutorial: **Tuesday 8-9pm, 6 Eastern Rd (E4B) 306 Faculty PC Lab

External students are expected to study the course notes and attempt the tutorials, weekly. They are also welcome to optionally attend the weekly lectures and tutorials:

**Course notes**: Course notes are available on iLearn, prior to the lecture. Tutorial solutions are posted on iLearn.

**Required and recommended resources**

There is no prescribed text for this unit. The following are useful references:

1. McCullagh, P. and Nelder, J.A. (1989). **Generalized Linear Models**, 2nd edition, Chapman & Hall.

2. Dobson, A. J. and Barnett, A. G. (2008). **An Introduction to Generalized Linear Models**, 3rd edition, Chapman & Hall.

3. De Jong, P. and Heller, G.Z. (2008). **Generalized Linear Models for Insurance Data**, Cambridge University Press.

4. Lindsey, J.K. (1997). **Applying Generalized Linear Models**, Springer.

5. Faraway, J. J. (2016). **Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models**. CRC Press.

6. Stasinopoulos MD, Rigby RA, Heller GZ, Voudouris V, De Bastiani F (2017). **Flexible Regression and Smoothing: Using GAMLSS in R**. CRC Press.

7. Wood, Simon N. (2017). **Generalized additive models: an introduction with R, **2nd edition**.** CRC Press.

Some references to texts on Generalized Linear Models are given on http://www.statsci.org/glm/books.html

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**Recommended web sites**

http://www.statsci.org/glm/

http://en.wikipedia.org/wiki/Generalized_linear_model

**TECHNOLOGY USED **

#### SAS Software

#### R software

We will be providing R code in the notes, as an alternative to SAS. R is freely downloadable from the CRAN website. We recommend use of the RStudio interface, also freely downloadable.

**iLearn**

We will be using iLearn for posting of course notes, assignments, solutions and data sets, and online discussions. You are encouraged to use the forums for discussions on the course material. Remember that if you are confused about something, the chances are that other students are also confused. Everybody benefits from the discussions, and you should not be embarrassed to admit that you do not understand a concept.

**Audio recordings of lectures **

Audio recordings of the lectures (Echo) will be available on the iLearn site.