Fieldwork and data-gathering techniques, the difference between primary and secondary data, sampling methods, and choosing and justifying techniques for a geographical investigation.

What this key area is asking

The SQA wants you to know the main ways geographers collect data, tell primary from secondary data, understand sampling, and be able to choose and justify a technique for a particular investigation, naming its strengths and limitations. This underpins both the skills paper and the Assignment.

Primary and secondary data

A good investigation usually combines both: secondary data set the context (population figures, land-use maps) and primary data test the specific question on the ground.

Fieldwork techniques

Sampling

Because you cannot record every point, you take a sample:

• Random sampling: every location or person has an equal chance of being chosen (for example using random number tables or coordinates), which avoids bias but may miss or under-represent a pattern.
• Systematic sampling: readings are taken at regular intervals (every 10 metres along a transect, every fifth person), which is even and quick but may by chance coincide with a hidden repeating pattern.
• Stratified sampling: the sample is divided to match the proportions in the area (for example by age group, by land-use type, or by distance zone), so every group is fairly represented.

Choosing and justifying a technique

The technique must fit the aim. To study how a river changes downstream you measure width, depth and velocity at systematic intervals; to study opinions on a regeneration scheme you use a questionnaire with a stratified sample. A strong answer justifies the choice and notes limitations such as questionnaire bias, the weather affecting measurements, sample size, and safety near rivers or roads.

Examples in context

Example 1. A river-change investigation. To test whether a river's width, depth and velocity increase downstream (a standard SQA fieldwork aim), you would measure systematically at several sites with a tape, metre stick and timed float, recording on a field sheet, and back it with secondary data such as a 1:25,000 OS map of the catchment. The justification is that even spacing gives comparable readings to reveal the trend, while limitations include safety near deep water and the effect of recent rainfall on flow. This is the classic physical-geography data-gathering case.

Example 2. An urban environmental-quality survey. To compare living conditions between an inner-city and a suburban area, you would use an environmental quality survey, scoring factors such as litter, noise, greenery and building condition on a numbered scale at sampled streets, plus a pedestrian count and a short stratified questionnaire. The numerical scores allow direct comparison and mapping, while limitations include the subjectivity of scoring (reduced by using a fixed scale and the same observer) and the influence of the time of day. This shows human-geography data gathering combining primary survey and opinion data.

Try this

Q1. Explain the difference between primary and secondary data, with an example of each. [3 marks]

• Cue. Primary is first-hand fieldwork (measuring river velocity); secondary already exists (census population figures); both can inform the same investigation.

Q2. For an investigation into river change downstream, describe a suitable data-gathering technique and justify your choice. [4 marks]

• Cue. Measure width, depth and velocity at systematic intervals down the river; this gives comparable readings to show the trend; note limitations such as safety and the effect of recent weather on flow.