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Collecting and presenting data are important steps, but the real value of any geographical investigation comes from the analysis — the process of examining your data to identify patterns, trends, anomalies and relationships, and then using geographical knowledge to explain what you find. Analysis is where you demonstrate your understanding of geography, not just your ability to measure things.
In the Edexcel B exam, analysis questions typically carry higher marks (4–8 marks) because they require you to go beyond description and show interpretation — linking data to geographical processes, theories and case studies.
Many students lose marks by describing their data when the question asks them to analyse or explain it. Understanding the difference is crucial:
| Skill | What It Involves | Example |
|---|---|---|
| Describe | State what the data shows — patterns, values, trends | "Pebble size decreases from 85mm at Site A to 18mm at Site H" |
| Analyse | Break down the data to find patterns, relationships and anomalies | "There is a strong negative correlation (rs = -0.95) between distance and pebble size, with the greatest rate of decrease in the upper course" |
| Explain | Use geographical knowledge to say why the pattern exists | "Pebble size decreases downstream due to the processes of attrition (pebbles collide and break apart) and abrasion (pebbles are worn smooth by rubbing against the riverbed)" |
| Interpret | Combine description, analysis and explanation to make sense of the data in a geographical context | "The data supports the Bradshaw model prediction that sediment size decreases downstream, with attrition and abrasion being the dominant processes, particularly in the upper course where gradient is steepest and energy highest" |
Exam Tip: If a question says "analyse" or "interpret," you must go beyond description. State the pattern, quantify it with data, and then explain it using geographical knowledge. The formula is: Pattern + Evidence + Explanation.
A pattern is a recognisable arrangement or distribution in the data. A trend is the general direction of change.
| Pattern Type | Description | Example |
|---|---|---|
| Increasing trend | Values get larger over time or distance | River discharge increases downstream |
| Decreasing trend | Values get smaller over time or distance | Pebble size decreases downstream |
| Positive correlation | As one variable increases, the other increases | Distance from source vs river width |
| Negative correlation | As one variable increases, the other decreases | Distance from CBD vs land values |
| Cyclic pattern | Values rise and fall in a repeating cycle | Pedestrian counts higher at lunchtime, lower in early morning |
| Cluster | Values are grouped together in a particular area or range | Most pebbles at coastal sites are 20–40mm in size |
| Spatial pattern | A geographical distribution across an area | Highest environmental quality scores in suburban areas, lowest in the inner city |
| Uniform distribution | Values are evenly spread | Sampling points along a transect |
| Random distribution | No discernible pattern | Litter distribution across a park |
When describing patterns, use the following framework:
Example of a strong pattern description:
"There is a clear negative relationship between distance downstream and mean pebble size. At Site A (0.5 km from the source), mean pebble size was 85 mm, decreasing progressively to 18 mm at Site H (4.0 km from the source). The rate of decrease was greatest between Sites A and C (upper course), where pebble size dropped by 27 mm in 1.0 km, compared with only 7 mm per km in the lower course (Sites F to H). Site D was a slight anomaly, with pebbles slightly larger than expected at 45 mm, possibly due to a tributary joining the river and introducing coarser sediment."
An anomaly is a data point or value that does not fit the general pattern. Anomalies are not mistakes to be ignored — they are features to be investigated and explained.
| Cause | Example |
|---|---|
| Measurement error | The flow meter was not properly calibrated at one site |
| Sampling error | A randomly selected pebble happened to be unusually large |
| Local factors | A tributary joins the river, increasing discharge unexpectedly |
| Human interference | A weir or bridge changes the natural flow pattern |
| Temporal variation | Heavy rain the previous day increased discharge at one site |
| Microclimate effects | A sheltered spot has different conditions from exposed areas |
Exam Tip: Never ignore anomalies. If you spot one, describe it clearly ("Site D had a mean pebble size of 45 mm, which is higher than the downward trend would predict"), and then suggest a possible explanation ("This may be because a tributary joins the river just upstream of Site D, introducing coarser sediment from its catchment area").
When analysing maps and spatial data, you need to describe distributions — how things are spread across an area.
| Term | Meaning | Example Use |
|---|---|---|
| Concentrated | Clustered in a small area | "Vacant shops are concentrated in the northern part of the high street" |
| Dispersed | Spread out across a wide area | "Residential properties are dispersed across the suburban fringe" |
| Linear | Arranged along a line | "Tourist facilities are arranged in a linear pattern along the seafront" |
| Clustered | Grouped together | "Fast food outlets are clustered around the bus station" |
| Even / uniform | Equally spaced | "Sampling points were placed at even intervals along the transect" |
| Peripheral | Located around the edges | "Industrial sites are located on the periphery of the town" |
| Central | Located in the middle | "The highest pedestrian counts are in the central shopping area" |
Always use compass directions (north, south-east) and specific place names when describing distributions.
One of the most important analytical skills is linking different datasets together to identify cause and effect relationships.
| Variable 1 | Variable 2 | Expected Link | Geographical Explanation |
|---|---|---|---|
| Distance downstream | Channel width | Positive — width increases | Tributaries add water; erosion widens the channel |
| Distance downstream | Velocity | Positive — velocity increases | Less friction relative to volume; more efficient channel shape |
| Distance downstream | Pebble size | Negative — pebbles get smaller | Attrition and abrasion wear down sediment |
| Distance downstream | Discharge | Positive — discharge increases | Tributaries add water to the river |
| Gradient | Velocity | Positive — steeper = faster | Gravity pulls water downhill more on steeper slopes |
| Variable 1 | Variable 2 | Expected Link | Geographical Explanation |
|---|---|---|---|
| Distance from CBD | Pedestrian count | Negative — fewer people | CBD is the most accessible point; footfall decreases with distance |
| Distance from CBD | Shop rent | Negative — lower rent | Less footfall = less profit potential = lower rent |
| Environmental quality | House prices | Positive — better quality = higher prices | People will pay more to live in pleasant environments |
| Deprivation index | Life expectancy | Negative — more deprived = lower | Poor health services, diet, housing and income reduce life expectancy |
Exam Tip: When making links between datasets, always state: (1) the relationship you observe, (2) the data evidence, and (3) the geographical explanation. For example: "As distance downstream increases, mean pebble size decreases (from 85mm to 18mm over 4km). This is because the processes of attrition and abrasion gradually wear down pebbles as they are transported downstream by traction and saltation."
Analysis is not just about mathematics — it requires you to connect your data to geographical theory and knowledge. The best answers reference models, processes and case study evidence.
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