How do geographers collect and test data through fieldwork?
Fieldwork design and sampling strategies, the collection of primary and secondary data, and statistical tests such as Spearman's rank and chi-squared.
A focused CCEA A-Level Geography answer on statistical and fieldwork methods, covering fieldwork design and sampling strategies, primary and secondary data collection, and statistical tests such as Spearman's rank correlation and the chi-squared test, with a worked calculation, assessed in the CCEA written papers.
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What this dot point is asking
CCEA wants you to plan fieldwork, choose appropriate sampling strategies, collect and process primary and secondary data, and select and interpret statistical tests such as Spearman's rank and chi-squared, including the use of significance levels. These methods are examined in the written papers rather than as a separate report.
Fieldwork design and sampling
Good fieldwork begins with a clear aim, hypothesis and null hypothesis (which states there is no relationship or difference). You then choose a sampling strategy:
Collecting data
Primary data is collected first-hand in the field, for example river channel surveys (width, depth, velocity along the Shimna or Bann), beach profiles, environmental quality surveys, pedestrian counts and questionnaires. Secondary data comes from sources such as census data, Ordnance Survey maps and official statistics. Reliability depends on sample size, accuracy and controlling for bias.
Statistical tests
Spearman's rank uses the formula
Significance and interpretation
A result is statistically significant if there is less than a () probability that it occurred by chance. If the calculated value exceeds the critical value for the sample size, you reject the null hypothesis and accept that the relationship or difference is real.
Examples in context
Example 1. River study on the Shimna, County Down. A student tests the hypothesis that channel width increases downstream. Using systematic sampling, they measure width, depth and velocity at fixed intervals along the river in the Mournes, then rank distance and width and apply Spearman's rank. A strong positive coefficient supports the Bradshaw model prediction. The study shows how a clear hypothesis, systematic sampling, primary data and a statistical test combine into reliable evidence.
Example 2. Urban quality survey using chi-squared. A study of environmental quality across zones of Belfast records the number of high, medium and low quality scores in inner-city and suburban areas. The chi-squared test compares the observed frequencies with those expected if quality were independent of zone. If the calculated chi-squared value exceeds the critical value at , the student rejects the null hypothesis and concludes that environmental quality does differ significantly between zones. It illustrates testing frequency data rather than a correlation.
Try this
Q1. Distinguish between random and systematic sampling. [3 marks]
- Cue. Random gives every point an equal chance; systematic selects at regular intervals such as every nth point or fixed distance.
Q2. State what a Spearman's rank value of indicates. [2 marks]
- Cue. A strong negative correlation between the two ranked variables.
Q3. Explain how a significance level is used to interpret a statistical result. [4 marks]
- Cue. Compare the calculated value with the critical value at ; if it exceeds it, reject the null hypothesis as the result is unlikely to be due to chance.
Exam-style practice questions
Practice questions written in the style of CCEA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
CCEA 20184 marksDescribe two sampling strategies a geographer could use to collect fieldwork data.Show worked answer →
Worth 4 marks, about two per strategy, rewarding a clear method plus when it is appropriate.
Random sampling: every point or person has an equal chance of selection, often using random numbers or a grid, which avoids bias but may miss parts of an area by chance.
Systematic sampling: data is collected at regular intervals, for example every tenth pedestrian or every 50 metres along a transect, giving even coverage and simplicity but risking bias if a hidden pattern matches the interval.
Stratified sampling is also creditable: the population is divided into groups and each sampled in proportion to ensure representation. Reward the method and a strength or limitation.
CCEA 20216 marksExplain how Spearman's rank correlation is used to test a relationship, and how the result is interpreted using a significance level.Show worked answer →
Worth 6 marks. Reward the method, the meaning of the coefficient, and the use of critical values.
Method: rank both variables, find the difference in ranks d for each pair, square it, sum the squares, and apply the formula to get a coefficient between plus 1 and minus 1.
Meaning: a value near plus 1 is a strong positive relationship, near minus 1 a strong negative, near 0 no relationship.
Significance: compare the value with the critical value at the 0.05 level for the sample size; if it exceeds the critical value, reject the null hypothesis and accept the relationship is statistically significant, not due to chance.
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Sources & how we know this
- CCEA GCE Geography specification — CCEA (2016)