Why do some graphs have gaps between the bars while others do not? The answer lies in the type of data being plotted. Geographers use discrete data (categories that can be counted, such as number of shops) and continuous data (measurements that can take any value, such as river depth).
Bar graphs are used for discrete categories and must always be drawn with equal width bars and equal gaps between them. In contrast, histograms represent continuous data.
On a histogram, the bars must touch to show that the numerical scale is uninterrupted. For OCR Geography, histograms typically feature equal class intervals on the x-axis.
If class widths were unequal, you would need to calculate frequency density to determine the height of the bars. This ensures the area of the bar represents the frequency.
Divided bar charts (also known as compound bar charts) allow you to show multiple components within a single bar. For example, a single bar representing total energy generation could be divided into segments for coal, wind, and solar. These can show absolute numbers or be plotted as percentage compound bars where every column reaches exactly .
A town's population grew from to over ten years. Calculate the percentage change.
Step 1: Calculate the difference between the new value and the original value.
Step 2: Divide the difference by the original value.
Step 3: Multiply by to find the percentage.
Every time you watch a weather forecast, you are likely interpreting complex line graphs without even realising it. Line graphs are specifically designed to illustrate how a variable changes over a continuous scale, such as time or distance.
A climate graph is a specialised combination chart that shows a specific location's average monthly weather. It features the twelve months of the year on the x-axis and uses two separate y-axes.
Precipitation is always plotted as a bar graph and read from the right-hand axis (measured in ). Temperature is plotted as a line graph and read from the left-hand axis (measured in ).
When constructing the temperature line, the points must be plotted in the exact centre of each month's column. These should be joined with a smooth, freehand curve rather than a ruler to reflect natural cycles.
When interpreting these graphs, always look for the general trend while watching out for an anomaly — a data point that breaks the established pattern. A reliable way to describe these graphs is using the TEA (Trend, Example, Anomaly) method.
Did you know that scaling circles by their width instead of their overall area completely distorts the visual data? When constructing proportional symbols on a map, the area of the shape must be mathematically scaled to match the data value.
This allows geographers to illustrate differences in magnitude across many different locations simultaneously. However, a major drawback is occlusion, where large symbols overlap and obscure smaller symbols or underlying map features.
Pie charts are similarly used to show proportions of a whole, where the total area of the circle represents . To draw a pie chart, you must convert your data into angles out of using the formula:
These pie charts can even be used as proportional symbols on a map. This allows you to show both the total size of a variable and its internal breakdown at different locations.
A city generates of solar power. Calculate the radius required for a proportional circle if the scale factor is .
Step 1: Find the square root of the data value.
Step 2: Multiply the result by the scale factor to find the radius.
Understanding how two variables connect helps geographers predict future events, such as estimating flood risks based on rainfall. Scatter graphs are used to plot bivariate data (two different variables) to see if a relationship, or correlation, exists. The independent variable goes on the x-axis, and the dependent variable goes on the y-axis.
To interpret scatter graphs, geographers look for the type of correlation:
A positive correlation shows a trend from the bottom-left to the top-right, meaning both variables increase together.
A negative correlation trends from the top-left to the bottom-right, indicating as one variable increases, the other decreases.
If the points are scattered randomly with no discernible pattern, there is no correlation.
If a clear pattern emerges, you can draw a line of best fit by eye, ensuring an equal number of points fall on either side of a straight, ruled line.
In contrast, dispersion graphs are used to plot univariate data (a single variable) to observe its spread and distribution. The data points are plotted as individual dots along a single vertical axis.
Because dispersion graphs only look at one variable, you must never draw a line of best fit through them. Instead, geographers analyse the spread by calculating the interquartile range (IQR).
Calculate the interquartile range (IQR) for the following pebble sizes (in ): .
Step 1: Rank the data in numerical order.
Step 2: Find the median (middle value).
Step 3: Find the lower quartile (median of bottom half) and upper quartile (median of top half).
Step 4: Subtract the LQ from the UQ.
While most graphs measure simple numbers, some are uniquely shaped to show demographics or environmental scores. Population pyramids consist of two back-to-back horizontal bar charts showing age groups for males on the left and females on the right. A wide base indicates a high birth rate.
Radial graphs (often called radar charts) feature multiple axes radiating from a central zero point. They are excellent for displaying bi-polar assessment scores from fieldwork, where variables like noise and litter are scored from negative to positive.
Rose charts are circular histograms used specifically for directional data. The length of a bar pointing outwards from a compass point indicates the frequency of an event, such as the prevailing wind direction.
A country has of its population aged -, aged -, and aged . Calculate the dependency ratio using the formula below:
Step 1: Add the percentages of the dependent age groups.
Step 2: Divide by the percentage of the economically active population (-).
Step 3: Multiply by to find the final figure.
Have you ever wondered how mapmakers turn a flat piece of paper into a 3D visual of a hill? Cross-sections are side-profile views showing the relief of the land between two points on a map. They are constructed using a paper strip laid across contour lines.
Because hills would look completely flat on a standard graph scale, geographers use vertical exaggeration (VE) to stretch the y-axis. This makes slopes more visible. The formula for VE is:
Cross-sections are vital for determining intervisibility (whether one location can be seen from another). They also help identify areas of dead ground hidden behind slopes.
To gather data across these landscapes, geographers use transects — straight lines along which measurements are taken at set intervals. Finally, to present simple discrete data, geographers might use pictograms. These use thematic icons to represent numerical units, making data visually memorable.
Students frequently read temperature data from the wrong axis on climate graphs. Always remember: precipitation is the bars (right axis in mm) and temperature is the line (left axis in °C).
Never draw a line of best fit on a dispersion graph. Lines of best fit are strictly for scatter graphs showing bivariate data.
When describing the correlation on a scatter graph, identify the direction: positive (bottom-left to top-right) or negative (top-left to bottom-right). If there is no pattern, state 'no correlation'.
Examiners expect graphical plotting to be highly accurate. Always use a sharp pencil and a ruler, ensuring your points or bars are within a +/- 1mm tolerance of the exact value.
When asked to 'describe the trend' of a line or scatter graph, always use the TEA method: state the Trend, provide Evidence/Examples using data units, and identify any Anomalies.
Discrete data
Numerical data that can only take specific, separate values and cannot be divided into fractions, such as the number of tourists.
Continuous data
Numerical data that can take any value within a given range and is measured rather than counted, such as temperature or distance.
Frequency density
A value used to plot the height of histogram bars when class intervals are unequal, calculated by dividing frequency by class width.
Divided bar charts
A bar chart where each bar is split into segments to show the relative proportions of different categories within a total.
Climate graph
A specialized combination chart showing a location's average monthly temperature (line graph) and precipitation (bar graph).
Anomaly
A piece of data or an observation that significantly deviates from the general trend or pattern shown on a graph.
Proportional symbols
Map symbols, typically circles, that are mathematically scaled so their area reflects the magnitude of the data at a specific location.
Occlusion
A visual issue on maps where larger proportional symbols overlap and hide smaller symbols or underlying map details.
Pie charts
Circular diagrams used to show proportions of a whole, where the total area of the circle represents 100% or 360 degrees.
Scatter graphs
Graphs used to plot bivariate data to identify relationships or correlations between two variables.
Bivariate data
Data that involves two different variables, used to determine if there is a relationship or correlation between them.
Positive correlation
A relationship where the trend line goes from the bottom-left to the top-right of the graph, showing both variables increasing together.
Negative correlation
A relationship where the trend line goes from the top-left to the bottom-right, showing one variable decreasing as the other increases.
No correlation
A situation where the data points are scattered randomly on a graph, showing no clear relationship between variables.
Line of best fit
A straight line drawn with a ruler through the middle of scatter graph points to represent the general trend.
Dispersion graphs
Graphs used to plot univariate data along a vertical axis to observe the spread and distribution of a single variable.
Univariate data
A data set that consists of observations on only a single variable or characteristic.
Interquartile range (IQR)
A measure of statistical spread that calculates the difference between the upper quartile and the lower quartile, representing the middle 50% of the data.
Population pyramids
Back-to-back horizontal bar charts showing the age and sex structure of a population, often in 5-year intervals.
Radial graphs
Circular charts with multiple axes radiating from a central zero point, used to display scores for several different variables.
Dependency ratio
A demographic calculation showing the ratio of dependent people (aged 0-14 and 65+) to the economically active working population (aged 15-64).
Bi-polar assessment
A fieldwork scoring system that uses opposite extremes (e.g., -3 for very poor to +3 for excellent) to evaluate environmental quality.
Rose charts
Circular histograms used specifically for directional data, such as showing the frequency and direction of the wind.
Cross-sections
Side-profile views showing the relief and topography of the land between two specific points on a map.
Vertical exaggeration
The deliberate stretching of the vertical scale on a cross-section compared to the horizontal scale, used to make the physical relief easier to see.
Intervisibility
The determination of whether one location can be seen from another, often assessed using a cross-section.
Dead ground
An area of the landscape that cannot be seen from a specific observation point because it is blocked by higher relief.
Transects
Straight lines or paths across a landscape along which measurements are taken at set intervals.
Pictograms
Diagrams that use thematic icons or pictures to represent numerical units of discrete data.
Bar graphs
Graphs used to compare distinct categories of discrete data, featuring bars of equal width with equal gaps between them.
Histograms
Graphs used for continuous data where bars must touch to show an uninterrupted numerical scale, typically with equal class intervals.
Line graphs
A graph designed to show how a variable changes over a continuous scale, such as time or distance, by connecting data points with a line.
Put your knowledge into practice — try past paper questions for Geography B
Discrete data
Numerical data that can only take specific, separate values and cannot be divided into fractions, such as the number of tourists.
Continuous data
Numerical data that can take any value within a given range and is measured rather than counted, such as temperature or distance.
Frequency density
A value used to plot the height of histogram bars when class intervals are unequal, calculated by dividing frequency by class width.
Divided bar charts
A bar chart where each bar is split into segments to show the relative proportions of different categories within a total.
Climate graph
A specialized combination chart showing a location's average monthly temperature (line graph) and precipitation (bar graph).
Anomaly
A piece of data or an observation that significantly deviates from the general trend or pattern shown on a graph.
Proportional symbols
Map symbols, typically circles, that are mathematically scaled so their area reflects the magnitude of the data at a specific location.
Occlusion
A visual issue on maps where larger proportional symbols overlap and hide smaller symbols or underlying map details.
Pie charts
Circular diagrams used to show proportions of a whole, where the total area of the circle represents 100% or 360 degrees.
Scatter graphs
Graphs used to plot bivariate data to identify relationships or correlations between two variables.
Bivariate data
Data that involves two different variables, used to determine if there is a relationship or correlation between them.
Positive correlation
A relationship where the trend line goes from the bottom-left to the top-right of the graph, showing both variables increasing together.
Negative correlation
A relationship where the trend line goes from the top-left to the bottom-right, showing one variable decreasing as the other increases.
No correlation
A situation where the data points are scattered randomly on a graph, showing no clear relationship between variables.
Line of best fit
A straight line drawn with a ruler through the middle of scatter graph points to represent the general trend.
Dispersion graphs
Graphs used to plot univariate data along a vertical axis to observe the spread and distribution of a single variable.
Univariate data
A data set that consists of observations on only a single variable or characteristic.
Interquartile range (IQR)
A measure of statistical spread that calculates the difference between the upper quartile and the lower quartile, representing the middle 50% of the data.
Population pyramids
Back-to-back horizontal bar charts showing the age and sex structure of a population, often in 5-year intervals.
Radial graphs
Circular charts with multiple axes radiating from a central zero point, used to display scores for several different variables.
Dependency ratio
A demographic calculation showing the ratio of dependent people (aged 0-14 and 65+) to the economically active working population (aged 15-64).
Bi-polar assessment
A fieldwork scoring system that uses opposite extremes (e.g., -3 for very poor to +3 for excellent) to evaluate environmental quality.
Rose charts
Circular histograms used specifically for directional data, such as showing the frequency and direction of the wind.
Cross-sections
Side-profile views showing the relief and topography of the land between two specific points on a map.
Vertical exaggeration
The deliberate stretching of the vertical scale on a cross-section compared to the horizontal scale, used to make the physical relief easier to see.
Intervisibility
The determination of whether one location can be seen from another, often assessed using a cross-section.
Dead ground
An area of the landscape that cannot be seen from a specific observation point because it is blocked by higher relief.
Transects
Straight lines or paths across a landscape along which measurements are taken at set intervals.
Pictograms
Diagrams that use thematic icons or pictures to represent numerical units of discrete data.
Bar graphs
Graphs used to compare distinct categories of discrete data, featuring bars of equal width with equal gaps between them.
Histograms
Graphs used for continuous data where bars must touch to show an uninterrupted numerical scale, typically with equal class intervals.
Line graphs
A graph designed to show how a variable changes over a continuous scale, such as time or distance, by connecting data points with a line.