SPARC: A Tool for Statistical Processing and Analysis for Research Content

SPARC is a novel Python-based tool designed to automate and streamline the statistical analysis of experimental results, enhancing efficiency and accessibility for researchers. This user-friendly tool supports a wide range of statistical tests, enabling rapid preliminary assessment and evaluation of data. It supports multi-group and multi-variable between-subject experimental setups and generates output using LATEX to aid the write-up process while including descriptive text, summary tables, and figures to visualise the data. In this paper, we present the key features of SPARC, showcase its application in experimental contexts, and discuss its potential to transform data-driven research across disciplines. Additionally, we want to encourage feedback from the HCI community and invite other researchers to contribute to SPARC’s open repository. By providing an efficient platform for statistical analysis, SPARC empowers researchers to focus on interpreting, applying, and publishing their findings, ultimately promoting robust scientific advancement.