Graphs & Diagrams (Cambridge (CIE) IGCSE Geography)

Graphs & Diagrams

Types of data

• Continuous data is numerical data that can take any value within a given range, e.g. heights and weights

• Discrete data is numerical data that can only take certain values, e.g. shoe size

• Quantitative data is where the results can be expressed using numerical values

• Qualitative data is where the results can’t be expressed as numbers, e.g. opinions

Line graph

• One of the simplest ways to display continuous data

• Both axes are numerical and continuous

• Used to show changes over time and space

Strengths

• Shows trends and patterns clearly

• Quicker and easier to construct than a bar graph

• Easy to interpret 

• Anomalies are easy to identify

Limitations

• Does not show causes or effects

• Can be misleading if the scales on the axis are altered

• If there are multiple lines on a graph, it can be confusing

• Often requires additional information to be useful

Example

• A river cross-section is a particular form of line graph because it is not continuous data, but the plots can be joined to show the shape of the river channel

Bar chart

• A bar chart is the simplest form of displaying data

• Each bar is the same width but can have varying lengths

• Each bar is drawn an equal distance apart (equidistant)

• The data is discrete data

• Bar graphs are useful for:

  • Comparing classes or groups of data

  • Changes over time

Strengths

• Summarises a large set of data 

• Easy to interpret and construct

• Shows trends clearly

Limitations

• Requires additional information

• Does not show causes, effects or patterns; can be too simplistic

• Can only be used with discrete data

Example

Histograms

• Histograms show continuous data

• Always use a ruler to draw the bars

• All bars should be the same width 

• The top of the bar should reach the number on the side of the graph that is being represented

• There should be no gaps; all bars should be touching

• Ensure all axes are labelled and that the graph has a title

Strengths

• Large data sets can be graphed easily

• Data can be compared

Limitations

• Can be difficult to pinpoint exact data values

• They can only be used for numerical data

Example

Compound or divided bar chart

• The bars are subdivided to show the information, with all bars totalling 100%

• Divided bar charts show a variety of categories

• They can show percentages and frequencies

Strengths   

• A large amount of data can be shown on one graph    

• Percentages and frequencies can be displayed on divided bar charts

Limitations

• A divided bar chart can be difficult to read if there are multiple segments

• It can be difficult to compare data sometimes

Example

Population pyramid

• This is a type of histogram

• Used to show the age-sex of a population

• It can be used to show the structure of an area/country

• Patterns are easy to identify

Strengths

• Easy to compare age and sex data

• Easy to read and annotate

Limitations        

• Can take a long time to construct

• Detail can be lost in the data (figures just show a cohort); additional annotations may be necessary

Example

Pie chart

• Used to show proportions, the area of the circle segment represents the proportion

• A pie chart can also be drawn as a proportional circle 

• Pie charts can be located on maps to show variations at different sample sites

• Percentage of pie chart must add to 100%

• To calculate degrees of the pie chart (which totals 360°), divide the percentage by 100 and then multiply by 360

• Each segment should be a different colour

Strengths

• Clearly shows the proportion of the whole

• Easy to compare different components

• Easy to label

• Information can be highlighted by separating segments

Limitations

• Does not show changes over time; hard to compare two sets of data

• Difficult to understand without clear labelling

• Calculating the size of each section can be difficult

• Can only be used for a small number of categories; otherwise, lots of segments become confusing

Example

Rose diagram

• Uses multidirectional axes to plot data with bars

• Compass points are used for the axis's direction

• Can be used for data such as wind direction, noise or light levels

Example

Triangular graph

• Triangular graphs are used to display data, which can be divided into three

Strengths

• Triangular graphs can be used to plot data such as soil content, rock size or type, or employment in economic activities, etc.

Limitations

• The data must be in percentages 

• Can be difficult to read

Example

• Read each side carefully so you are aware which direction the data should be considered

  • Always read from 0 to 100 and follow through to the next 0

  • Can be either clockwise or counter-clockwise

  • In the example below, the data reads clockwise

Scatter graph

• Points should not be connected

• The best fit line can be added to show the relations

• Used to show the relationship between two variables

  • In a river study, they are used to show the relationship between different river characteristics, such as the relationship between the width and depth of the river channel

Strengths

• Clearly shows data correlation

• Shows the spread of data

• Makes it easy to identify anomalies and outliers

Limitations

• Data points cannot be labelled

• Too many data points can make it difficult to read

• Can only show the relationship between two sets of data

Example

Types of correlation

• Positive correlation

  • As one variable increases, so too does the other

  • The line of best fit goes from bottom left to top right of the graph

• Negative correlation 

  • As one variable increases, the other decreases

  • The line of best fit goes from the top left to the bottom right of the graph

• No correlation

  • Data points will have a scattered distribution

  • There is no relationship between the variables

Choropleth map

• These are maps that are shaded according to a pre-arranged key

• Each shade of colour represents a range of values

• It is common for one colour in different shades to be used

• Can be used for a range of data, such as annual precipitation, population density, income levels, etc.

Strengths

• The clear visual impression of the changes over space

• Shows a large amount of data

• Groupings are flexible 

Limitations

• Makes it seem as if there is an abrupt change in the boundary

• Distinguishing between shades of colour can be difficult

• Variations within the value set are not visible

Example

Proportional symbols map

• The symbols on the map are drawn in proportion to the variable represented

• Usually, a circle or square is used but it could be an image

• Can be used to show a range of data, for example, population, wind farms and electricity they generate, traffic or pedestrian flows

Strengths

• Illustrates the differences between many places

• Easy to read

• Data is specific to particular locations

Limitations

• Not easy to calculate the actual value

• Time-consuming to construct

• Positioning on a map may be difficult, particularly with larger symbols

Example

Pictograms

• These are a way of displaying data using symbols or diagrams drawn to scale

• Useful way of showing data if accuracy is not too important and data is discrete

• Years do not need to be continuous

• Symbols do not need to be whole but can represent a proportion

• A key is needed to show if the total number of objects or events that image represents exceeds one

How to read a pictogram

• Step 1: Read the problem carefully and identify the specific information requested from the pictogram

• Step 2: Count the symbols corresponding to the desired information and report the count

• In the pictogram above, you can see that 4 shoppers walked to the supermarket, but only one used a taxi

• The majority of shoppers used a car to travel to the supermarket