Modelling Binary and Count Data (GLMI)
Date:
09/11/2017 - 10/11/2017
Organised by:
Lancaster University
Presenter:
Professor Brian Francis
Level:
Intermediate (some prior knowledge)
Contact:
Angela Mercer 01524 593064; psc@lancaster.ac.uk
Map:
View in Google Maps (LA1 4YF)
Venue:
Department of Mathematics and Statistics
C/o Postgraduate Statistics Centre
Lancaster University
Lancaster
Description:
This is the second of two related courses that consider generalized linear models as a broad class of statistical models that can be applied to a variety of commonly encountered data analysis problems in the social and biological sciences.
This course introduces the generalized linear model framework and extends it to the situation when we wish to model binary data as a dependent variable in a logistic regression analysis, and similarly count data in a Poisson regression analysis.
The use of categorical (factor) explanatory variables, continuous covariates and their interactions to build a flexible class of relationships will be considered.
The course will also use the software package R as a tool for such statistical analysis.
Prior knowledge of the material covered in the first course: Introduction to Multiple Linear Regression (GLM I), is a pre-requisite for this course.
Cost:
External from industry/commerce £540; External from academic institution/public sector/charity staff £460.
Website and registration:
www.lancaster.ac.uk/maths/postgraduate/short-courses/
Region:
North West
Keywords:
Generalized liner model (GLM)
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