Geographical Skills, Fieldwork and Investigative Analysis
Geographical Skills, Fieldwork and Investigative Analysis
This domain tests map, graph and statistical skills, fieldwork design and evaluation. Questions require correct method, accurate interpretation and critical judgement about reliability and validity.
Core rules
- A hypothesis is a testable statement; sampling can be random, systematic or stratified. Sample size and bias affect representativeness.
- Data types include nominal, ordinal and interval. Use measures of central tendency and dispersion such as mean, median, mode, range and interquartile range.
- Maps require scale, grid references, contour interpretation, cross-sections, land-use and choropleth interpretation. GIS overlays layers.
- Fieldwork includes aims, risk assessment, pilot study, primary and secondary data, controls and ethics.
- Statistical tests include Spearman rank for correlation, chi-square for association and Mann-Whitney U for difference. Interpret significance, not just the calculated value.
Worked example
A survey of 8 sites gives a Spearman rank value of 0.64. Reasoning: the value is positive, so higher values of one variable tend to accompany higher values of the other. With 8 pairs, compare the result with the critical value at the chosen significance level; if it exceeds that value, reject the null hypothesis. Then discuss sampling and measurement error before claiming a causal link.
Traps
Do not confuse correlation with causation. Do not use a small biased sample to generalise. Do not ignore units or scale. Do not accept a statistical result without checking significance and data quality.