Interpreting and analysing graphical data on trends in participation rates, commercialisation and ethical and socio-cultural issues in sport.

What this dot point is asking

Edexcel wants you to interpret and analyse graphical data on trends in participation rates, commercialisation, and ethical and socio-cultural issues in sport. This is the use-of-data topic, embedded throughout Component 2.

Reading trends from graphs and tables

Calculating changes correctly

Choosing the right chart

The exam expects you to know which presentation suits which data. A bar chart compares separate categories, so it suits participation rates across the five social groups (gender, age, socio-economic group, ethnicity and disability), where each bar is one group. A line graph shows change over time, so it suits a trend such as obesity rates or broadcasting income rising across the years. A table lists exact values, useful when the precise figures matter (for example a normative-data table). Reading the chart type correctly tells you whether the question is about comparing groups or describing a trend, which shapes your answer.

Describing versus explaining data

A strong answer separates describing the data from explaining it. Describing states what the data shows ("participation among 16 to 24 year olds is 12 percentage points higher than among over-65s"). Explaining gives the reason ("because older adults have less free time, lower fitness and fewer suitable opportunities"). The highest marks come from doing both, then drawing a conclusion that links back to the question. It is also good practice to note the limits of the data: a small sample, a single survey or a short time period may not be enough to be sure, so a careful answer says whether more data would strengthen the judgement rather than over-claiming from one figure.

Using socio-cultural data

Data is not just read, it is used. A table of participation rates by social group shows which groups are under-represented, so providers and the government can target funding, facilities and campaigns at the lowest group, then re-collect the data to check whether participation has risen. Data on commercial income shows how fast money has flowed into sport, and data on doping cases shows whether anti-doping measures are working. A strong answer reads the data, draws a conclusion, and links it to a decision.