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Introduction to data analysis and linear regression in R

This repository contains content for a 4-day course for new PHD students (and other interesting people), run within the School of Biological, Earth & Environmental Sciences (BEES) at the University of New South Wales.

Details for this session are as follows:

  • Dates: Monday 04 February to Thursday 07 February (9.00am to 5.00pm)
  • Audience: New Honours or HDR students in BEES
  • Venue: BEES Teaching Lab 3, Ground Floor E26
  • What to bring: your laptop
  • Presenters
    • Daniel Falster (BEES)
    • Will Cornwell (BEES)
    • Ben Maslen (Stats Central)
    • Gordana Popovic (Stats Central)
  • Demonstrators:
    • Dony Indiarto
    • Sally Crane
    • John Wilshire

Aims & Content

Day 1 – Introduction to R

Getting started with R

  • Introduction to Rstudio
  • Introduction to coding in R
  • Getting data in and out of R - R objects and classes
  • Packages

Day 2 – Project management and data manipulation

Project management

  • Projects: Organising and managing data - Reproducible research with Rmarkdown Data manipulation & visualisation with the tidyverse
  • Data manipulation with the tidyverse - Data visualisation with ggplot

Day 3 – Introduction to design and analysis

Introduction to statistics

  • Which method do you use when? - Statistical inference
  • Two-sample t-test

Introduction to Experimental design

  • Sample sizes
  • Treatments

Linear regression

  • Linear regression
  • Equivalence of two-sample t and linear regression

Day 4 – Introduction to linear modelling

Linear models

  • Multiple regression
  • Analysis of variance (and equivalence to multiple regression)

Weirder linear models

  • Blocked and paired designs - ANCOVA
  • Factorial experiments
  • Interactions in regression

Installation instructions

The course assumes you have the R software and the development environment RStudio installed on your computer.

R can be downloaded here.

The Desktop version of RStudio can be downloaded here.

For instructors

Notes for Instructors are included within the file Instructor.md.