The enquiry process
An enquiry is a question answered with evidence. Most courses ask for two enquiries in contrasting settings: one physical (rivers, coasts, weather, soils) and one human (shops, traffic, quality of life, land use). Comparing two different places makes patterns clearer.
- Question and hypothesis
- Collect data (methods and sampling)
- Process and present data
- Analyse and conclude
- Evaluate
Question and hypothesis
A good question is short, measurable, safe and linked to a real place, for example: How does the river channel change downstream?
A hypothesis is a statement you can test: River width increases with distance downstream. A null hypothesis says there is no link. Link your question to geography theory (e.g. the river model, or land use models of a city).
Data collection methods
Primary and secondary data
- Primary: collected by you — tape and metre-rule measurements, float tests for speed, questionnaires, traffic counts, photos, field sketches, environmental quality scores.
- Secondary: collected by others — census data, maps, weather records, newspaper reports, websites.
Qualitative and quantitative
Quantitative data are numbers (width = 5 m). Qualitative data are words, pictures or opinions (an interview, a sketch).
Sampling
- Random: every point has an equal chance (random number tables).
- Systematic: regular gaps (every 50 m, every 10th person).
- Stratified: sample each group in proportion (e.g. ages, land types).
Always do a risk assessment (deep water, traffic) and respect people's privacy.
Processing and presenting data
Choose the graph that fits the data:
- Bar chart: compare places or categories.
- Line graph: change over time or distance.
- Scatter graph: test a link between two variables; add a line of best fit.
- Pie chart: parts of a whole.
- Cross-section: the shape of a river channel.
- Maps: flow lines, proportional symbols, choropleth shading (by area, no borders needed for a small study area).
Work out the mean, median, mode and range and look for anomalies (results that do not fit).
Analysis, conclusions and evaluation
Analyse: describe the pattern, quote numbers, explain it with theory, mention anomalies.
Conclude: answer the question and say whether the hypothesis is supported or rejected.
Evaluate: How reliable are the results (would you get the same again)? How accurate (close to the true value)? What limited the study (small sample, one day, weather, equipment)? How could it be improved?
Using data to argue and decide
In an issue evaluation you study a resource booklet (maps, graphs, quotes, photos) about a real issue, such as a flood scheme or a new road.
- Analyse the sources: who wrote them? Are they fact or opinion?
- Weigh options: list benefits and costs of each option for people, the economy and the environment, now and in the future.
- Justify: choose one option, give evidence from the sources, and explain why the others were rejected.
An extended written argument has a clear opinion, uses both quantitative (numbers) and qualitative (views) evidence, considers the other side and ends with a judgement.
The independent investigation
At higher level, students write their own investigation of about 3,000–4,000 words. It needs your own question linked to the course, your own primary data plus secondary data, careful analysis (often with statistics such as Spearman's rank), clear conclusions and an honest evaluation. Plan the time: about a third each for collecting, analysing and writing.
Try it: a mini enquiry at home
Question: Is the street outside busier in the morning or the evening? Count vehicles for 5 minutes at 8 am and 6 pm on three days (systematic sampling). Draw a bar chart, find the mean for each time, write a conclusion and one way to improve your study. In the 3D step 6, see how more readings give a better estimate.
Key formulas and definitions
- Hypothesis: a testable statement, e.g. 'width increases downstream'
- Mean = total of values ÷ number of values
- Range = highest value − lowest value
- Cross-section area ≈ width × mean depth
- Discharge (m³/s) = cross-section area (m²) × velocity (m/s)
- Velocity = distance ÷ time (float test)
- Reliable = gives the same results if repeated; accurate = close to the true value
Worked examples
1. Write a hypothesis for a study of a town centre's shops.
'The number of shoppers decreases with distance from the main square.' It is testable: count shoppers at points every 100 m from the square.
2. Depth readings across a 4 m wide stream are 0.1, 0.3, 0.5, 0.3 m. Find the mean depth and the cross-section area.
Mean = (0.1 + 0.3 + 0.5 + 0.3) ÷ 4 = 1.2 ÷ 4 = 0.3 m. Area ≈ 4 × 0.3 = 1.2 m².
3. A float travels 10 m in 25 s in that stream. Find the velocity and discharge.
Velocity = 10 ÷ 25 = 0.4 m/s. Discharge = 1.2 m² × 0.4 m/s = 0.48 m³/s.
4. A pedestrian count was done only once, on a rainy Monday. Evaluate it.
Low reliability: one day is a small sample and rain kept people away, so counts may be too low. Improve by repeating on several days, including a weekend, at the same times.
Common mistakes
- Writing a question that cannot be measured, like 'Is the town nice?'. Make it testable.
- Mixing up primary (you collected it) and secondary (someone else collected it) data.
- Choosing a pie chart for data that change over time — use a line graph.
- In evaluation, only saying 'it went well'. Name real limits and real improvements.