Quantitative and qualitative data, methods of collecting data, and how to present data clearly in tables, graphs and charts.

What this dot point is asking

AQA wants you to distinguish quantitative from qualitative data, describe methods of collecting data, and choose and produce the right table, graph or chart to present data clearly.

Quantitative and qualitative data

Quantitative data are objective and easy to compare; qualitative data give more detail about quality but are more subjective.

Collecting data

Presenting data

Choose the chart that suits the data:

• Tables organise raw data clearly before graphing.
• Bar charts compare separate categories, for example the press-up scores of different people.
• Line graphs show change over time, for example heart rate before, during and after exercise.
• Pie charts show proportions of a whole, for example the percentage of body composition.

Always label the axes, give the units, add a title and use a sensible scale so the graph is clear.

Choosing the right graph is the most-tested skill here, so it helps to tie each chart to the kind of data it suits. A line graph is for a continuous variable changing over time, which is why it is the standard choice for a heart-rate trace through a session: time goes on the horizontal axis and heart rate on the vertical axis, and the line shows the rise during exercise and the fall during recovery. A bar chart compares separate, discrete categories, such as the press-up scores of five different players, where the gaps between the bars show the categories are not continuous. A pie chart shows how a whole is divided into proportions, such as the percentage split of fat, muscle and bone in body composition, and the slices should add to 100 percent. A table is not a graph but is the starting point: it records the raw data tidily so it can be checked and then turned into the right chart.

The quality of the data also depends on how it is collected. Reliable data comes from collecting in a standardised way (the same protocol, equipment and conditions each time), from a large enough sample to be representative, and from accurate measuring instruments. Quantitative methods such as timing a sprint or recording heart rate give objective numbers that are easy to compare, while qualitative methods such as a questionnaire or a coach's observation capture detail and opinion but are more subjective and harder to compare fairly. Many investigations use both, for example a bleep-test score (quantitative) alongside the performer's comments on how hard it felt (qualitative).