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Analysing and presenting data


Statistical software packages

Software packages can be used to analyse and present data. The most widely used ones are listed below:

Software for analysing and presenting data


A statistical analysis and data management package for quantitative data analysis. It can perform a wide variety of statistical procedures. Some examples are:

  • Data management, e.g. creating subset of data; transform data.
  • Summarise, describe or present data, e.g. mean, median, frequency.
  • Look at distribution of data, e.g. standard deviation.
  • Compare groups for significant differences using parametric (e.g. t-test) and non-parametric (e.g. Chi-square) tests.
  • Identify significant relationship between variables, e.g. correlation.

Web resources

Statistics support for students from Statstutor

Other information: These materials were developed at Loughborough and Coventry Universities and with colleagues in other university mathematics support centres. The site is designed for university students and anyone else who needs help with statistics post-16 level. There are a variety of resources on the site, including video tutorials.

University of Hull SPSS tutorials

Other information: This page on Hull’s website has useful information and videos about using SPSS.


SamplePower software helps you to find the best sample size for your research.


What can it do?

Can be used for qualitative data analysis. It does not place any restrictions on methodology. It supports grounded theory; survey data; case studies; focus groups; phenomenology; field research; action research.

NVivo can:

  • process data such as interview transcripts, literature or media extracts, historical documents,
  • code data on screen and explore all coding and documents interactively,
  • rearrange, restructure, extend and edit text, coding and coding relationships,
  • search imported text for words, phrases or patterns, and automatically code the results.
Who is it used by?

Researchers, postgraduates, undergraduates, social scientists, market researchers, historians, literary critics, health researchers, business analysts.