Skip to end of banner
Go to start of banner

Quantitative data analysis

Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 6 Next »

Analysing the numbers

It is likely that you will analyse the quantitative data you have collected in Excel or Google Sheets. These are popular tools that are often free or more affordable to use, as well as being easier. A lot of analysis can be completed in Excel. It is unlikely that you will need other software, but if you are trained and know how to use this, then do!

We can’t teach you how to do analysis on Excel. We recommend that you look up some tips and take a refresher course. Alternatively, consider what skills you have in your organisation or get some external support at this stage.

Reporting on statistical validity relies on the interpretation and assessment of the researcher. However, there are ways to think about and report on the validity of your study that might help you collect better data as well as tell more accurate stories about your impact.

Sampling, representativeness and validity

Triangulation

This refers to finding data to support (or disprove) a result based on data from two or more sources. This helps control for various external factors that might influence results (e.g. procedural bias in an interview).

You might compare a survey result with what you find in interviews or observation. This means that you are triangulating your results. It’s not only important to do this for validity, but also more broadly because it helps more with your analysis.


Next step

  • No labels