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examBoard: Cambridge
examType: IGCSE
lessonTitle: Pattern and Trend Identification
Being able to spot patterns and trends in geographical data is a super important skill that will help you in your iGCSE Geography exams and beyond. When geographers look at data, they're trying to make sense of what's happening in the world around us - whether that's changes in climate, population growth, or migration patterns.
Key Definitions:
Patterns are about how things are arranged in space. For example, settlement patterns might be linear (along a river), nucleated (clustered together), or dispersed (spread out).
Trends are about how things change over time. For example, a population might show an upward trend (increasing), downward trend (decreasing), or fluctuating trend (going up and down).
Identifying patterns and trends helps us:
Line graphs are brilliant for showing trends over time. They're commonly used for climate data, population change, economic growth and more.
When describing a line graph, follow these steps:
Looking at a graph of global temperatures from 1900-2020:
"The graph shows an overall increasing trend in global temperatures. Between 1900-1950, temperatures remained relatively stable with minor fluctuations. From 1950 onwards, there has been a steady increase, with temperatures rising by approximately 1°C. The steepest rise occurred after 1980, with the years 2016 and 2020 showing the highest recorded temperatures. There was a slight anomaly in 1991-1992 when temperatures temporarily dropped following the Mount Pinatubo volcanic eruption."
Bar charts are perfect for comparing different categories, while histograms show the distribution of data across continuous ranges.
Compare different categories at a single point in time.
Example: Comparing GDP of different countries
Show multiple variables for each category.
Example: Energy sources used by different countries
Show frequency distribution across continuous ranges.
Example: Distribution of rainfall amounts
When analysing bar charts:
Scatter graphs help us spot relationships between two variables. They're great for testing geographical theories and models.
Positive correlation: As one variable increases, so does the other (e.g., temperature and ice cream sales)
Negative correlation: As one variable increases, the other decreases (e.g., distance from city centre and land prices)
No correlation: No clear relationship between variables
Just because two things correlate doesn't mean one causes the other!
Example: Countries with more internet users also have higher life expectancy, but internet use doesn't directly cause longer life. Both are linked to development levels.
Maps show how geographical features are distributed across space. Being able to describe these patterns is a key skill.
Features grouped together in certain areas
Example: Settlements in fertile valleys
Features arranged in lines
Example: Settlements along transport routes
Features spread out evenly
Example: Farms in agricultural areas
When describing patterns on maps, consider:
The UK population shows clear spatial patterns:
These patterns reflect historical development, physical geography and economic opportunities.
Climate graphs combine temperature (line) and precipitation (bars) data for a location across the year.
When analysing climate graphs, look for:
Population pyramids show the age and gender structure of a population.
Wide base, narrow top
High birth rate, lower life expectancy
Example: Nigeria, Kenya
Similar-sized bars until older ages
Stable birth rate, longer life expectancy
Example: UK, Australia
Narrower at the base than middle
Low birth rate, ageing population
Example: Japan, Italy
Use this DRCT approach:
Be prepared to:
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