Analysing: PQE Method (2024)

Analysing: PQE Method

PQE is a tool used by geographers to analyse sources and data (such as maps, tables, graphs and diagrams) and reach conclusions.

Hints
(for exams) Annotate the figure to help you understand it, especially graphs. E.g. circle countries, circle key data, write notes to help identify relationships between data
Remember to look at the legend/key to better understand the data and information.

Avoid
When analysing figures, you do not need to tell the reader what type of map or graph it is or what the figure is about.
Examples of what not to write:

"Figure 1 is a choropleth map showing life expectancy around the world"
"Figure 2 is a line graph showing the proportion of the population who had internet access between 2000 and 2020"

(in exams) If the question asks you todescribethe pattern, you do not need to explain reasons for why the pattern occurs.

(P) Pattern

In this step, give an overview of any patterns, trends or relationships evident in the figure.

When looking at any form of data, look for things that stand out or form patterns. A pattern may be a group of similar features on a diagram, a concentration of a particular colour or feature on a map, or a particular shape that is created by data on a column graph.

Maps:

Spatial patterns - Spatial distribution refers to the way in which different geographical features (bothnatural and human) are spread over the Earth's surface.What patterns are evident over the spaceon the map (across the world, or region)?
Temporal (time) patterns - What have been the patterns ofchange over time?

Graphs:

Scattergraphs -What is the relationship between the two variables? Is it a positive or negative correlation? Is the correlationweak, medium or strong?
Line graphs - What has been the overall trend (change) over time? Has there been an increase or decrease? Has itbeen sharp or steady?
Column or bar graphs - What pattern is evident in the data?

Examples
Maps and Satellite Images

physical map of Australia:"Most mountains in Australia are on the east coast."
choropleth map of death rates from Malaria: "The highest death rates from malaria in 2017 were in African countries, especially in central Africa."
series ofsatellite images of the Aral Sea between 1989 an 2009: "The Aral seasignificantly reduced in size between 1989 and 2009"

Graphs

scattergraph showing the variables of income and life expectancy:"There is a strong positive correlation between income per person and life expectancy"
line graph of life expectancy for Australia between 1900 and 2015: "Australia's life expectancy has steadily increased between 1900 and 2015"
line graph showing fertility rates in selected countries in Europe: "The fertility ratefor the selected European countries shows a gradual decrease over the last 20 years"
bar graph of the deadliest natural disasters of 2020: "The top four deadliest natural disasters were from flooding and/or flash floods and they all occurred in developing countries"

(Q) Quantify

In this step, you need to provide evidence to support the patterns, trends or relationships you identified. Use specific information and/or data.

Quantifying involves:

using data from themap's legend or graph's key
stating a point on the graph (e.g. highest numberor lowest number in a line graph)
calculating differences(e.g. calculation of total increase over time as a number or percentage)
referring to specific names of places (continents, countries, regions, cities etc.)
using compass points to refer to specific areas (e.g. northern part of the country, or along the east coast.)

Examples
Maps

After"Most mountains in Australia are on theeast coast.", quantify the statement: "The largest mountain range is the Great Dividing Range which extends more than 3500 kilometres along the eastern coastfrom Queensland to Victoria."
After"Most of the forest is located in the centre of the continent", quantify the statement: "240.3 million hectares of forest existsin Central Africa, compared to 35.4 million hectares in East Africa"

(E) Exceptions

In this step, you need to identify anything that does not fit into the pattern you have described.
Often there are no exceptions or anomalies, but you should look for and identify any where possible.

Examples
Maps

physical mapof Australia:"There are a number of other smaller mountain ranges that are not on the east coast. These include the Flinders Ranges in South Australia and the MacDonnell Ranges in the Northern Territory."

Graphs

Column graph showing life expectancyin Australian states and territories:"Northern Territory was the only state/territory which had a significantly lower life expectancyby about 4 years compared to the other states and territories."

Examples of Analysing Figures Using the PQE Method

Notes:

Exams - you don't have to refer to the figure number, just get straight into the analysis (likethe examples below)
Reports - you have to refer to the figure number to show its relevance e.g. Figure 3.2 shows...

Line Graph

Example 1
Life expectancy mostly increased in Belize over the 65 year period. Between 1950 and 2015, life expectancy increased by approximately 19 years (from 55 to 74 years), however between 1988 and 1999 there was a declineby approximately 4 years (from 72 to 68 years).

Example 2
Between 1950 and 2015, life expectancy in Belize steadily increased except for a decline between 1988 and 1999. In the 65 year period, life expectancy increased by 35% from 55 years to 74 years, however over the 11 year period from 1988, there was a decline by 4 years.

Example
In the last 71 years, Australia’s population has steadily increased. It has more than tripled from approximately 8 million people in 1950 to approximately 26 million people in 2021.

Bar Graph

Generally, animal products have the highest levels of greenhouse gas emissions while plant-based food products have the lowest levels of greenhouse gas emissions.Most food products emit between 0.07 and 13kg of greenhouse gas emissions per 1000 kilocalories, except for prawns and beef (beef herd) which emit 26.09kg and 36.44kg respectively.Plant based food products emit between 0.07kg to 3.0kg of greenhouse gases per 1000 kilocalories, while animal products emit over 3.0kg of greenhouse gases per 1000 kilocalories. Tomatoes are the exception to this, as this plant product ranks fifth and produces 11kg of greenhouse gas emissions per 1000 kilocalories.

Choropleth Map

The countries which had the highest share of deaths from unsafe water sources in 2017 were in Africa and Asia. Most African countries (except in northern Africa) had between 2% to 8% of deaths from unsafe water sources, and five countries had high rates of 8% to 12%. In Asia, India had the highest rates of deaths from unsafe water sources with between 5% to 6%, and some countries in Asia had 3% to 5%. Europe, Oceania and the Americas (except one country in the central American region) had between 0-1% share of deaths resulting from unsafe water sources.

Scattergaph

There is a positive correlation betweentotal expenditure on health care as a percentage of Brazil’s GDP and life expectancy, aslife expectancy increased when a higher percentage of the country’s GDP was spent on healthcare.In the 15 years between 1995 and 2010, total health spending increased by 2.36%, from6.65% to 9.01% of GDP, and life expectancy increased by5.1 years, from 69.3 years to 74.4 years.

Analysing Stacked Graphs

Hint: Annotate the graph to help work out specific numbers (in purple, on the graph on the right)

The table is to help understand the data. This may not be realistic to do for every stacked graph.

In the USA between 2008 and 2018, the average hours per day spent engaging with digital media more than doubled from approximately 2.7 hours to 6.3 hours per day. The mobile phone became the most popular device for engaging in digital media, surpassing the previous most popular desktop/laptop device in around 2014. In 2008, the mobile phone was used for only around 0.3 hours per day, but ten years later it was used for around 3.6 hours per day. The amount of time using 'other connected devices' fordigital media increased by a small amount but remained under 1 hour (from approximately 0.2 hours to 0.7 hours).

Hint: Annotate the graph to help work out specific numbers (in purple, on the graph on the right)

The table is to help understand the data. This may not be realistic to do for every stacked graph.

In Norway between 2013 and 2019, the proportion of new diesel and petrol cars decreased, while hybrid and electric cars increased. In 2013, battery electric cars only made up 5% of new vehicle registrations, while in 2019 they made up almost half (42%). Diesel and petrol cars, which made up 86% of new vehicle registrations in 2013, only made up 32% in 2019. The percentage of diesel cars dropped the most (-36%) followed by petrol cars (-18%). Full hybrid cars had the smallest change over the time period.

Analysing Population Data

Notes:

Annotations have been added to the graph using Microsoft Word to help identify patterns.
Colours have been used to also help with this - green which has connotations to being positive (or higher) and red being negative (or lower). This depends on which data you are basing your comparison on - e.g. Focus placeis Greater capital cities. Comparison place isthe Rest of Australia (non-capital cities).

(P) PATTERN – What is the overall pattern showing?

The capital cities have a much greater percentage of people in the 20 to 49 age cohorts than the rest of Australia. In contrast, the rest of Australia has a greater percentage of people in the older (50+) and younger (19 and below) age cohorts than the capital cities.

The capital cities contain a greater proportion of people who are generally in the working-age bracket (20-49 years old) than the rest of Australia.

(Q) QUANTIFY – What is some evidence to support this?

Approximately 44% of the people in capital cities are between 20-49 years old, compared to 36% for the rest of Australia.

(E) EXCEPTIONS – Are there any exceptions evident?

Despite there being a lower percentage of younger people in capital cities than the rest of Australia, the 0-4 age cohorts are higher for both males and females.

What does this data tell us overall?

Working-age population live in capital cities, likely for work and lifestyle reasons.
Potentially when they start a family, they move out of the capital city area.
When people get older and retire, they tend to move out of capital cities looking for a tree-change or sea-change.

This graph shows the demographic distribution in the Rural North (Queensland) compared to the general Queensland (state) population.

Notes:

Annotations have been added to the graph using Microsoft Word to help identify patterns.
The focus is on Rural North (Queensland).The comparison data is Queensland (state of Queensland)

(P) PATTERN – What is the overall pattern showing?

The Rural North has a notably higher percentage of individuals in the older age cohorts and lower percentage in the working-age and younger age cohorts, compared to the general Queensland population.

The Rural North has a notably higher percentage of older dependents and lower percentage in the working-age and young dependents, compared to the general Queensland population.

(Q) QUANTIFY – What is some evidence to support this?

The Rural North has a higher percentage than Queensland for every age cohort between 50-84 years for males and 55-79 years for females.
The largest difference is for 65-69 males, where they make up approximately 2.5% of the population in Queensland but 7.5% in Rural North.

(E) EXCEPTIONS – Are there any exceptions evident?

The only age cohort under 49 years old where the percentage of people in the Rural North is higher than the Queensland averageis25–29 year old males. The female counterparts are consistent with the general pattern ofthe other age cohorts under 49 years old where the percentage is higher in Queensland than the Rural North.
While the Rural North typically has an older population compared to Queensland as a whole, the percentages of males aged 85 and above and females aged 80 and above are higher in Queensland.

What does this data tell us overall?
For the higher percentage or older dependents:

The data showsan ageing population in the Rural North Queensland region.
The Rural North has a lot of retirees - it is potentially appealing for the lifestyle.
While the Rural North generally has an older population overall, Queensland has a higher proportion of very elderly individuals, particularly among males aged 85 and above and females aged 80 and above. This could suggest differences in life expectancy or healthcare access.

For the lower percentage or working-age and young dependents

When students graduate high school, they likely move away from the Rural North to pursue tertiary study, a career and/or a lifestyle change.

For the exception/anomaly of 25-29 year old males

The high percentage of males in the 25-29 years cohort may represent males who work in the mining or agricultural industry in the Rural North.

Analysing: PQE Method (2024)