Research support
Resources targeted at Early Career Researchers (ECRs) who would like to learn new quantitative methods or extend their knowledge in this area.
These various guides, worksheets, and videos will also help any researcher, in any stage of their career, who wants to widen their expertise and develop new quantitative analysis skills.
Quantitative Analysis documents
Q-Step Sheffield has developed numerous 'How to Guides' and helpful videos on how to conduct different methodologies for different statistical analysis programmes, including SPSS, R, and STATA.
SPSS
These guides provide guidance on how to recode variables and run and interpret regression in SPSS.
Videos also demonstrate how to use Stata to make histograms, conduct regression, setting missing values, among other useful methods.
SPSS - Recoding Categorical Variables (PDF, 974KB)
SPSS - Running Linear Regression (PDF, 659KB)
R
These resources provide a range of guidance on various statistical analysis methods using R, including textual analysis, principal component analysis, and factor analysis.
R - Building Packages in R (PDF, 1.3MB)
R - Cronbach Alpha (PDF. 423KB)
R - Factor Analysis (PDF, 671 KB)
R - How to Build a Shiny App (PDF,1MB)
R - Linear Regressions (PDF, 718KB)
R - Principal Components Analysis (PDF, 508KB)
R - Textual Analysis (PDF, 846KB)
Stata
These resources provide guidance on how to conduct statistical analysis in STATA using methods such as Multivariate Linear Regression and Bivariate analysis.
Stata - Bivariate Associations (PDF, 469KB)
Stata - command sheet (PDF. 409KB)
Stata - Linear Regression (PDF. 543KB)
Stata - Multivariate Linear Regression (PDF, 496KB)
Stata - How to Recode Variables (PDF. 422KB)
Communicating your research
This lecture video series consists of 10 mini-series, comprising of three to five short videos, which explore and discuss the best way to communicate your research using data visualisation.
In these series, we will examine and think about the role that data visualisation plays in society, how different visualisations might be prepared for different audiences, and ‘best practice’ factors to consider when creating your own graphs in order to clearly and effectively communicate your research.
[Link to video playlist]
Data visualisation: Instructional 'R' guides
These nine detailed lab worksheets walk you through the creation of data visualisations using R software.
They are simple, straightforward and also a great introduction to statistical analysis. Through these worksheets we learn how to create bar graphs, scatter plots, maps and even interactive data visualisations.
Data Visualisation Worksheets 1 to 9 Combined (PDF, 5.3MB)
Suggestions
A short video accompanies each worksheet to help ease you into the labs - we recommend watching them.
[Link to video playlist]
When an error message comes up in your console, the simplest way to resolve the problem is to Google them (feel free to copy paste them into your browser's search engine).
Use helpful forums such as ‘Stackoverflow” and the RStudio community boards to troubleshoot different solutions.