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Instructor-led course

Provided by: University Computing Service


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R: Regression Analysis in R
Prerequisites


Description

This course is for new users who have learnt how to get data into R already, and know how to operate basic syntax. Emphasis will be on examples of running applied analyses of regression models for continuous, binary and ordinal outcomes using standard R procedures. Guidance will also be provided on further addons that may be of interest.

Prerequisites
  • Working knowledge of R
  • Familiarity with simple statistical concepts
Topics covered
  • Linear regression for continuous outcomes
  • Bootstrapping standard errors
  • Logistic regression
  • Logistic regression for clustered data
  • Ordinal regression for multi-category outcomes that can be ordered
  • Logit and probit models
  • Nominal regression (in brief) for unordered multicategory outcomes
  • Categorical covariates using xi:
Format

Presentations, demonstrations and practicals.

System requirements

R v. 2.9.1 on PWF Windows

Notes

DEP 22/4/2010 CNCLD DUE TO TRAINER NOT BE AVAILABLE.

Duration

Two half day sessions

Themes

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