1  Software

1.1 Installing R and an IDE

During this subject, we use R to do some basic data analysis. Below are instructions for installing R and an integrated development environment (IDE) in which to run it.

1.1.1 R

R is a freely available language for statistical computing and graphics. It is the most common software used in applied behavioural science.

YOu can download R from the Comprehensive R Archive Network for Linux, macOS or Windows.

1.1.2 Integrated development environments (IDEs)

An IDE is a software application that provides a user-friendly interface for writing and running code. It typically includes features such as syntax highlighting, code completion and debugging tools.

1.1.3 RStudio

RStudio is an integrated development environment (IDE) for R and Python. It provides a user-friendly interface for writing and running code, as well as tools for data visualisation. RStudio is widely used in the R community and is a great choice for beginners.

You can download RStudio Desktop from Posit. The RStudio Desktop is free.

1.1.4 Visual Studio Code

Other IDEs also work with R. Visual Studio Code is a popular alternative, although it provides a less intuitive R interface.

1.2 Learning R and RStudio

If you are new to R, start with these introductory resources.

1.3 G*Power

During this subject, we will use G*Power to do power analysis.

G*Power is a tool to compute statistical power analyses for tests such as t-tests, F-tests and z-tests. You can use it to compute effect sizes and to graph the results of power analyses. Download it here.

1.4 Qualtrics

We will use Qualtrics as our experimental survey platform.

Qualtrics is a web-based survey tool. It provides a clean web interface for creating surveys.

Some core features of the Qualtrics platform are as follows:

  1. Qualtrics surveys are organised as “projects”. Learn more about creating and managing projects in the Qualtrics Projects Basic Overview.
  2. Within a project you build the survey in blocks containing questions. See the Survey Tab Basic Overview.
  3. Use the survey flow to set the order in which participants move through the survey and to manage randomisation. Read more about survey flow and randomisers.

Qualtrics is well documented and broadly used. The Qualtrics support page has a wealth of resources, and many questions can also be resolved via a web search or your favourite large language model.

1.4.1 Qualtrics tips

These tips are largely drawn from Gilad Feldman’s Collaborative Qualtrics and Survey Design guide.

  • Instructions: Provide clear instructions about what participants should do and what to expect. Do not vary instructions and items between conditions unless explicitly intended. As a general guide, the only difference between conditions should be the manipulation.
  • Meaningful names: Use block and variable names that describe their purpose.
  • Survey flow: Do not allow participants to go back and revise previous answers unless required by the design. This is to prevent one answer from being contaminated by subsequent answers or manipulations.
  • Preview and testing: Pre-test the questionnaire across all conditions. Check comprehension and attention checks, randomisation logic and validation rules.
  • Spelling and grammar: Export to Word for spellchecking or use tools such as Grammarly.
  • Sliders: Only use sliders without defaults; draggable sliders set defaults that participants may follow.
  • Validations: Use validations when you expect a particular response format (for example, numeric ranges). Allow for a wide enough range that includes all possible values. The point is to restrict the impossible, which is objective, and not the unreasonable, which is subjective.
  • Randomisation of conditions: Randomise at the block level in the survey flow. Use “Evenly Present Elements” to balance conditions.
  • Randomisation of item order: Randomise questions within a block when order does not affect the experiment.
  • Timers: Timers are useful for measurement but avoid displaying them to participants.