Interpreting Data on Participation and Performance
Why Data Skills Matter in PE
Physical education is not just about sport — it also requires you to make sense of evidence. Data appears across this paper in questions about participation rates, health trends, fitness scores and commercial figures. The ability to read a graph accurately, make a comparison, calculate a percentage change, and then explain what the numbers actually mean in a sporting or wellbeing context is tested directly in questions worth up to four marks. These marks are predictable and highly attainable if you follow a clear method.
Types of Data: Quantitative and Qualitative
Quantitative data deals with numbers. It can be collected through questionnaires (tick-box formats, rating scales) and surveys. Examples in a PE context include the number of students who exercise three or more times a week, a table of body mass index (BMI) values, or a bar chart of participation in different sports by gender.
Qualitative data deals with descriptions, opinions and experiences. It cannot be counted directly. Common collection methods are interviews and structured or unstructured observations. A PE researcher conducting in-depth interviews with teenage girls about barriers to sport participation would be collecting qualitative data. Qualitative data is rich and detailed, but it cannot be placed on a graph in the same way as quantitative figures.
Presenting Data: Tables, Bar Charts, Line Graphs and Pie Charts
Data can be displayed in four main formats, each with strengths for different purposes. A table presents raw values in rows and columns, making exact figures easy to read. A bar chart uses rectangular bars to compare values across categories — for example, comparing weekly participation in different sports. Both axes must be labelled: the horizontal (x) axis typically shows the category (sport, age group, school); the vertical (y) axis shows the value being measured (number of participants, percentage, score).
A line graph is used to show change over time — for example, tracking the average resting heart rate of a cohort over a 12-week fitness programme. Each point on the line represents a value at a specific time, and the trend (rising, falling, levelling off) is the key thing to describe. A pie chart displays proportions as slices of a circle, with each slice representing a percentage or share of the whole. Pie charts are commonly used to show the distribution of media revenue across sports, or the breakdown of a population’s activity levels.
Bar charts compare categories. Line graphs show change over time. Pie charts show proportions. Tables give exact figures. Both axes on bar charts and line graphs must always be labelled with the variable name and its unit.
How to Interpret Data: A Four-Step Method
The inference (what the data means) earns more credit than simply reading off a figure. A reliable method for any interpret-data question is: (1) Read — identify the exact values you need from the chart or table. (2) Compare — compare at least two figures (e.g. between two groups, two time points, or two sports). (3) Calculate — if the question asks for it, calculate the difference, percentage share, or percentage change. (4) Explain — state what the comparison means in a sporting or wellbeing context. Missing step 4 is the most common reason students drop marks: copying a number from a table earns nothing if the question asks you to “interpret.”
Imagine a bar chart shows weekly participation in netball at three Year-10 schools: School A 18%, School B 27%, School C 12%. A typical 4-mark question asks: “Interpret what the data shows about participation patterns across the three schools.”
Step 1 (Read): School B has the highest participation at 27%; School C has the lowest at 12%.
Step 2 (Compare): School B’s rate is 15 percentage points higher than School C’s (27 − 12 = 15).
Step 3 (Calculate if needed): School B has more than twice School C’s participation (27 ÷ 12 = 2.25×).
Step 4 (Explain): This suggests significant variation in engagement patterns between schools, which could reflect differences in facilities, media coverage, role models or socio-economic factors in the local area.
Calculating Percentage Change and Mean
Two calculations appear regularly. Percentage change is calculated as: (new value − old value) ÷ old value × 100. For example, if the number of female participants in a club rises from 40 to 52, the percentage change is (52 − 40) ÷ 40 × 100 = 30%. The mean (average) is the sum of all values divided by the number of values. The range (highest minus lowest) describes the spread of data. Always state your units (bpm, %, Kcal, participants) and show working for calculation questions.
Percentage change = (new − old) ÷ old × 100. Mean = sum ÷ number of values. Range = highest − lowest. Always show working and include units in your final answer.
A very common error on 4-mark interpret-data questions is simply copying numbers from the table or graph: “School A has 18%, School B has 27%, School C has 12%.” This reads the data but does not interpret it. A full answer needs: a comparison (quoting at least two figures), a calculated difference or ratio where appropriate, and a sporting or wellbeing explanation for what the pattern suggests. Practise finishing every data answer with the phrase “This suggests that…” and completing the sentence with a real-world implication.