Session 1 Presentation, worksheet and data at

• presentation: http://rpubs.com/lexcomber/session1_pres
• worksheet: http://rpubs.com/lexcomber/session1
• data: https://tinyurl.com/ydeuj2to

Lex Comber email: a.comber@leeds.ac.uk

Chris Brunsdon email: Christopher.Brunsdon@mu.ie

There will be 8 sessions over 2 days:

• 6 of these will be on the materials we have developed
  • 3 each day
• 2 empty sessions
  • to work with you and YOUR data, questions and problems

Day 1

• Introduction (Lex)
• Regression I (Chris)
• Visualisations with ggplot2 (Lex)

Day 2

• Introduction to Spatial Data and Mapping (Lex)
• Regression II: Other Forms of Regression (Chris)
• Spatial Interaction Models - A Poisson Regression Approach (Chris)

We have set aside time in the first session (Introduction) to make sure everything is set up

• You have R installed
• You can load all of the packages
• You have all of the materials on your computer
• To make sure that you establish robust workflows

In each session

• we will briefly introduce each Part (10-15 mins)
• then you will work through the exercise documents
• we will be going round the lab helping where it is needed
• you are not just expected to run the code but to play with it as well!

• We will be working in R and RStudio
• R is the engine

• RStudio is graphical front end to R

• we encourage you to work in RStudio

Prior to this workshop you should have worked through the Session0 (Session0.html) worksheet, especially if you have not used R before. This introduces R / RStudio and some core operations.

You should have made the following preparations:

1. You should R and RStudio installed on your computer
2. You should have done your homework and run the code in it
3. You will need to have an internet connection – this is really important!
4. All the data you and code you need are in the folders for each session
5. If possible You should have prepared some data: a .CSV or EXCEL file with latitude and longitude, or a shapefile. PLEASE let us know if you want some data - we have lots!!!

Technical aspects

1. Code is entered by a console
2. You should write your code in a script (like a text file)
3. This is not a typing / English lesson - so copy and paste from the documents
4. You can run code from the script
5. This means your code is saved, can be easily changed and re-run etc

Technical aspects: RStudio start

Technical aspects: Open a script

Technical aspects: RStudio Components

Conceptual aspects

1. You are not expected to remember every R command, function, etc
2. BUT ….you are expected to understand what you are trying to do with your code
   • so ask if you need to!!!
3. For these reasons you should annotate your code - use the # in your script

Conceptual aspects

• Learning is R is learning to drive.
• It takes time to become a good driver
• Learning by doing is important

• R includes a very large number of tools, functions and packages
• R has the latest methods and tools
• New tools are in R 10-20 years before commercial software
• The tools in R are open (i.e. the source code is visible)
• This support research transparency
• Oh - and R is free!

To introduce

• R packages
• saving workspaces and projects
• using scripts
• loading data
• simple visual data exploration (basic boxplots, histograms, scatter plots)
• summary statistics

AND… to make sure you are all set up!