From SPSS to R

This course is an introduction to R for users of the analysis software SPSS. It provides an introduction to the RStudio working environment, fundamentals of coding in R, R data types and structures, and a grounding in tidyverse style coding for standard data management tasks. At the end of the course attendees should be able to work confidently with data within R in preparation for analysis, as well as produce simple descriptives to explore and understand their data.  This course may also be suitable for users of Stata.

The course will cover:

• How to understand the RStudio working environment, including the purpose of the Source, Console, Environment and Files windows, how to refer to objects stored in the Environment with code and the concept of assigning values to objects, and how to access R’s help tab. 

• How to use functions from packages in R. Packages are collections of R functions – essentially a bundle of tools and resources - that extend the functionality of the primary R software. Whatever challenge you encounter, there is usually a package that can help with it. 

• How to deal with common issues such as conflicts between packages, and how to find documentation and support for the use of new packages.

• The different object types (e.g. vectors, data frames and lists) and data types (e.g. numeric, character and logical) which R commonly uses and how to identify and manage them. 

• Explore the concept of object-orientated programming, how to apply functions in R, core features of applying R functions, and how these interact with different data and object types. 

• How R handles missing values and how to manage data with missing values.   

• Fundamentals of good coding practice in R. 

• An introduction to the R tidyverse: a collection of key R packages designed to make data science tasks easier and more efficient. These packages work together seamlessly to provide a consistent and powerful toolkit for data manipulation, visualization, and analysis.

• Key tools for data wrangling using tidyverse functions, including importing and exporting data of different types, how to explore and understand your data in R and produce basic descriptive analysis, and then how to edit your data - including recoding, sub-setting, sorting, and aggregation of data.

Before the course.

Attendees should install R / RStudio in advance of the session,  and verify that they can install packages successfully. It will not be possible to provide technical support for this during the training, as issues can be specific to each user, e.g. their operating system or organisational IT policies.  This device must be brought to the session to be used during the training.

The target audience is not specific to academia or government etc. It would be for people who are familiar with data wrangling in another software (e.g. SPSS) and would like to begin using R.

This course will be delivered Face to Face, from 09:30 to 16:30, at City, University of London, Room AG13, College Building, 280 St John St, London, EC1V 4PB.  This course will be charged at one full day rate.