Glossary

Key Points

Data Management: Introduction	Good data organization is the foundation of any research project
Data Management: File-naming and folder structures	Basic data management ideas can improve efficiency and reduce risk
Data Management: Meta-data	Files and folders with meta-data are far more useable than without
Data Management: Raw Data	The term ‘raw data’ means something specific in the world of data analysis. Without it, you can’t go back to the start of an analysis
Data Management: Data Management Planning	Projects that are expected to generate a large amount of data, and/or complex data, may benefit from such a plan
Spreadsheets: Introduction	Spreadsheets can be extremely useful, but they can also cause chaos
Spreadsheets: Guiding Principles	A number of simple concepts can increase the future usability of data
R introduction: Introduction	Coding isn’t always the answer, but it’s hard to justify not using it for anything large-scale and/or important
R introduction: Tidy data	Tidy data makes future analysis very straightforward, especially in coding environments
R introduction: R and RStudio	RStudio is the software used for coding in R
R introduction: R fundamentals	Base R features and techniques
R introduction: Data Manipulation and Plotting	Analysis code is built line-by-line
R introduction: Beyond Base R	R can be extended in thousands of different ways
Statistics in R	You can do anything, statistics-wise, in R

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