1. SPSS: SPSS (Statistical Package for the Social Sciences) is a popular statistical analysis software tool for analysing quantitative data. It is beneficial for analysing survey data and can be used to perform descriptive statistics, inferential statistics, and regression analysis.
2. Excel: Excel is a spreadsheet program that can be used for data analysis. It is beneficial for analysing small data sets and creating charts and graphs to visualise data.
3. R: R is an open-source programming language for statistical analysis and data visualisation. It is beneficial for advanced statistical analysis and for creating custom data visualisations.
4. SAS: SAS (Statistical Analysis System) is a powerful statistical tool for data analysis in many fields. It is beneficial for analysing large data sets and can be used for various statistical breakdowns.
5. Stata: Stata is a statistical software package for data analysis and management. It is handy for analysing large data sets and performing advanced statistical analysis.
6. NVivo: NVivo is a qualitative data analysis software tool for analysing text-based data, such as interview transcripts or survey responses. It can be used for coding, organising data, and analysing relationships between different concepts.
7. Atlas.ti: Atlas. It is another qualitative data analysis software tool used for analysing text-based data. It is beneficial for analysing large data sets, coding and organising data and identifying patterns and relationships between different concepts.

When choosing a software tool for data analysis, it is essential to consider the type of data you are analysing, the complexity of your comment, and your level of expertise with different tools. Many universities and research institutions offer workshops and training on various software tools to help researchers choose the best tool for their needs.