In order to understand a program, we firstly need to be clear about the population we are working with, or our population, and find out certain information about them, so that we can describe our client group meaningfully.

Standard demographic data can include some of the following:

»» Age, gender, ethnic or racial identity, suburb of residence, first language, social and economic status, employment status, income, education, residential status, family, relationship and parenting status and ages of children.

In order to describe your data, you will want to be able to indicate the average or typical value, and how broadly your data is spread out. The typical value can also be described as a measure of central tendency, or the value around which most results are gathered, whilst the spread is also referred to as variation or dispersion.

Measures of dispersion

Whilst there are many indications of dispersion or how spread out your data is, the most useful for most purposes are either the range of results, i.e. the minimum and maximum values, or the standard deviation, which is a statistical measure of the typical variation from the average, and is sometimes reported with the phrase “plus or minus”.

Whilst the standard deviation formula is somewhat complex, it is easily found in databases such as excel. A low number indicates that the data is closely clustered around the mean, whilst a high value suggests a broad spread.

Using these together

Typically, the Mean and Standard deviation are reported together. For example, for age, you would report the mean and standard deviation, e.g.,the average age of participants was 18.6 ± 2.6 years.

Alternatively, when using the median, you would be more likely to use the maximum and minimum values, e.g., the median number of children for program participants was 2, with a range of 1-5.

Where categorical values are used then the most common result or mode is reported, as the most typical result, with other frequencies reported as relevant.