linear-models-r

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linear-models-r

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Going beyond the t-test in R and introducing linear regression and ANOVA (http://tinyurl.com/linear-models-r)

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# Introduction to Linear Modelling with R

## Description

The course will cover ANOVA, linear regression and some extensions. It will be a mixture of lectures and hands-on time using RStudio to analyse data.

# Aims: During this course you will learn about:

- ANOVA
- Simple and multiple regression
- Generalised Linear Models 
- Introduction to more advanced topics, like non-linear models and time series.

# Objectives: After this course you should be able to

- Realise the connection between t-tests, ANOVA and linear regression 
- Fit a linear regression
- Check if the assumptions of linear regression are met by the data and what to do if they are not
- Know when linear regression is not appropriate and have an idea of which alternative method might be appropriate
- Know when you need to seek help with analysis as the data structure is too complex for the methods taught

# Pre-requisites

This course assumes basic knowledge of statistics and use of R, which would be obtained from our Introductory Statistics Course and an "Introduction to R for Solving Biological Problems" run at the Genetics department (or equivalent).
 
 - [Introduction to Solving Biological Problems with R](http://cambiotraining.github.io/r-intro/)
 - [Introduction to Statistical Analysis](http://bioinformatics-core-shared-training.github.io/IntroductionToStats/)

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