Introduction to R/Open Science Practices

This 2-day course will introduce participants to important open science practices in the social sciences including the pre-registration of study hypotheses, experimental design and plans for data analysis, as well as processes and procedures for sharing research data and analytic code. The course will also provide applied researchers with an entry-level, practical introduction to R for the purposes of conducting reproducible data manipulation and analysis.

Course leader

Dr Eoin McElroy and Professor Victoria Simms

Target group

Basic knowledge of descriptive and inferential statistics (specifically correlation and regression) would be beneficial for the R-portion of the course.

Course aim

It will introduce attendees to the basic functions of R, assuming no prior knowledge of computer programming. Particular attention will be paid to data exploration and visualisation techniques. Attendees will also gain experience of conducting a range of common statistical techniques used in the behavioural and social sciences (e.g. correlational and regression analysis). Participants will also be shown how to install R packages for additional functionality. This course uses lectures to provide a clear understanding of the logic underlying the use of statistical techniques and procedures; however, a greater amount of time will be devoted to giving participants experience of hands-on use of R.

Fee info

GBP 330: Full fee (educational/charitable sector); £400 for Government/commercial sector
GBP 220: Student rate (evidence required)

Scholarships

NA