Quantitative data analysis makes sense of numerical data. We can use numbers to summarise the experiences or characteristics of a group of participants, for example their average age or the number of symptoms they report. We can also use numbers to look at people’s behaviours, experiences and views. Perhaps most importantly, we can use numbers to look at differences between groups of people or the same group over time. This can help us understand the effect of new treatment or policy initiatives, both in terms of the type of effect (e.g. does a new policy make things better, worse or leave things unchanged?) and the size of its impact (e.g. are any changes big enough to be meaningful or could they have happened just by chance?). This chapter explores some of the different approaches to analysing numerical data, examines the difference between descriptive and inferential statistics, and highlights some of the ways in which you can begin to interpret research data presented as numbers.

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