Leaflets resources

Self-help resource providing an overview of correlation and regression in R. This resource has been made available under a Creative Commons licence by Sofia Maria Karadimitriou and Ellen Marshall, University of Sheffield.

Self-help resource providing an overview of correlation in R, used for exploring the (linear) relationship between two variables. This resource has been made available under a Creative Commons licence by Sofia Maria Karadimitriou and Ellen Marshall, University of Sheffield.

Self-help resource providing an overview of outliers, Durbin-Watson, and interactions for regression in R. This resource has been made available under a Creative Commons licence by Sofia Maria Karadimitriou and Ellen Marshall, University of Sheffield.

Self-help resource providing an overview of multiple regression in SPSS, used to look for significant relationships between two variables or predict a value of one variable for given values of the others. This resource has been made available under a Creative Commons licence by Ellen Marshall, University of Sheffield.

Self-help resource providing an overview of simple linear regression in R, used to look for significant relationships between two variables or predict the value of one variable for a given value of the other. This resource has been made available under a Creative Commons licence by Sofia Maria Karadimitriou and Ellen Marshall, University of Sheffield.

This guide contains information on a wide range of popular statistics learning resources, used within a statistics support context in Higher Education (HE) in many Universities across the UK. The information could be used to identify a suitable resource for a student, to assist with the CPD of statistics support tutors or indeed to determine which book/resources to download/purchase for a mathematics support centre.

This is a publicity leaflet for mathcentre showing resources that are available for students and staff.

A handy quick guide to statistical tests and techniques for those providing statistics support. This covers when to use each technique along with the interpretation of results, checking assumptions and what to do if the assumptions are not met. This was developed by the MASH Centre at the University of Sheffield and contributed to the statstutor Community Project by Ellen Marshall (University of Sheffield) and Alun Owen (University of Worcester) and reviewed by Jean Russell and Nick Fieller, (University of Sheffield).