1 About this module
1.1 About this module
This module will provide you with the fundamental skills in
- basic programming in R
- reproducibility
- data wrangling
- data analysis
basis for
- Geospatial Data Analysis
- Geospatial Databases and Information Retrieval
- as well as Geographical Visualisation
1.2 R programming language
One of the most widely used programming languages and an effective tool for (geospatial) data science
- data wrangling
- statistical analysis
- machine learning
- data visualisation and maps
- processing spatial data
- geographic information analysis
1.3 Suggested schedule
The lectures and practical sessions have been designed to follow the schedule below
- 101 Introduction
- 102 Data types
- 201 Selection and manipulation
- 202 Table operations
- 301 Reproducible analysis
- 111 Control structures and functions
- 501 Exploratory data analysis
- 502 Regression models
- 601 Unsupervised
1.4 Reference books
Suggested reading
- Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R by Michael Freeman and Joel Ross, Addison-Wesley, 2019. See book webpage and repository.
- Machine Learning with R: Expert techniques for predictive modeling by Brett Lantz, Packt Publishing, 2019. See book webpage.
Further reading
- The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff, No Starch Press, 2011. See book webpage
- Discovering Statistics Using R by Andy Field, Jeremy Miles and Zoë Field, SAGE Publications Ltd, 2012. See book webpage.
- R for Data Science by Garrett Grolemund and Hadley Wickham, O’Reilly Media, 2016. See online book.
- An Introduction to R for Spatial Analysis and Mapping by Chris Brunsdon and Lex Comber, Sage, 2015. See book webpage