Quantitative analysis

What it is

The process of analysing data that can be counted or measured in some way and given a numerical value. You want to know the locations of the most popular study spaces on UofG’s campus. To identify the most popular spaces, you might count the number of students studying in different locations at regular time intervals over a period of days or weeks. This result would be quantitative data.

Why use this method

Analysing this data helps you to identify areas for improvement, understand patterns and trends, and prioritise development efforts. By presenting the data to stakeholders in a clear and accessible way, you can help them understand the results and use them to make informed decisions.

How to use

  1. Understand the different response options and scales, such as ordinal scales e.g. ‘agree’, ‘neutral’, or ‘disagree’ response categories.
  2. Use Z test calculators like this Z test calculator to determine whether differences are statistically significant.
  3. Identify differences between your respondents and benchmarking data(if it is available).
  4. Group data by demographics or other variables and compare responses between different groups.
    • Make sure you are not misinterpreting the data and keep your biases in check when making groupings or identifying insights!
  5. Present the data in a clear and accessible way. Use charts and other visualizations- optimize axis labels, colour schemes, and create a visual narrative or infographic for key messages. Visual communication needs to be clear and accessible if insights are to be acted on.
    • Excel will automatically present your data for each question as bar charts, and these charts can quickly be pasted into reports. Numerical analysis programs such as Power Bi, SPSS, R offer a wider variety of charting options. These software packages allow you to visualise your data and create interactive dashboards, using charts and other visualisations.
  6. Engage stakeholders in the process by asking for their feedback and using the data to inform decision-making.

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