Transcript 21st century skills at post-16

GA Guildford 2011
Progress in Geography
21st Century Skills
Helen Hore
Subject Leader, Central Sussex College
Post 16 and HE Phase Committee
What skills should our students be
developing?
 Use
existing databases
 Be able to produce charts on Excel
 Use Excel (or calculator) for number
crunching Spearman’s Rank Correlation
Coefficient
Statistical Exercise on Water
Poverty
 Ready-made
exercise to analyse
relationship between variables and
attempt to explain them:

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

Water Poverty Index
% water use in agriculture
Water consumption
GDP (PPP)
Application
– A2 Water Conflicts
 WJEC – A2 Sustainable Water Supply
 AQA – A2 Contemporary Conflicts and
Challenges
 Edexcel
Water Poverty Index
– the quantity of surface and
groundwater per person, and its quality
 Access – the time and distance involved in
obtaining sufficient safe water
 Capacity – how well the community
manages its water (and health)
 Use – how economically water is used in
the home and by agriculture and industry
 Environment – ecological sustainability
 Resources
The Task – Acquiring Data
 Access
World Resources Institute
database
 http://earthtrends.wri.org/searchable_db/in
dex.php?action=select_countries&theme=
2&variable_ID=1299
 Click on Water Resources and Freshwater
Ecosystems from top menu
Acquiring data 1



Open the database for ‘groundwater
withdrawals - % used for agricultural
purposes’
Choose ONE country each – include
different levels of development
Access other databases – ‘Water
Poverty Index’ and ‘Water withdrawals,
annual per capita’
Acquiring data 2
 Select
from top menu ‘Economy,
Business, and the Environment – GDP
per capita (PPP – current international
dollars)
 Find latest value for your country
 Add all values to the class dataset and
then make this available to the class
Correlation
Create Charts

Wealth and WPI
Water Poverty Index
Select each of the
first 3 variables to plot
against GDP and
create scatter graph
for each
 Add title, label axes
 Click on chart area
and add trendline
80
UK
New Zealand
Dom Rep Brazil
Egypt
Bangladesh
Jamaica
60
France
USA
Australia
Kenya Jordan South Africa
Ghana
Ethiopia
Niger
40
20
0
0
5000
10000
15000
20000
25000
30000
GDP per capita
35000
40000
45000
50000
Spearman’s Rank Correlation
Coefficient
 FIRST
rank the values in each dataset
 Calculate coefficient for each water
variable against GDP (PPP) by correlating
the ranks
 Use the formulae:
=CORREL(A1:A10,B1:B10)
Spearman’s Rank Correlation
Coefficient
Significance
Analysis - Wealth GDP (PPP) and
Water Poverty Index
Water Poverty Index
Wealth and WPI
80
UK
New Zealand
Dom Rep Brazil
Egypt
Bangladesh
Jamaica
60
France
USA
Australia
Kenya Jordan South Africa
Ghana
Ethiopia
Niger
40
20
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
GDP per capita
As GDP (PPP) increases, so does
the WPI (high is good!)
Poverty means water poverty
Positive
correlation
Rs = 0.83
Analysis - Wealth GDP (PPP) and
Water Withdrawals for Agriculture
water withdrawals agric %
Wealth and w ater w ithdraw als for argiculture
Negative
correlation
120
Et hiopia
Cambodia
Madagascar
Niger
Tanzania
Egypt
Jamaica
Jordan
Ghana
Dom Rep
Kenya
Brazil
Sout h Af rica
100
80
60
Aust ralia
40
USA
New Zealand
20
UK
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
France
Rs = -0.71
50000
GDP per capita
As GDP (PPP) increases, water
withdrawals for agriculture decreases.
In poorer nations, a greater % of water is
used in agriculture.
Analysis - Wealth GDP (PPP) and
Water Withdrawals per Capita
water withdrawals
Wealth and water withdrawals
1800
1600
1400
1200
Egypt
1000
800 Bangladesh
600
Jamaica
400 Cambodia
Brazil
200 Kenya South Africa
Jordan
0
0
5000
10000
USA
France
New Zealand
UK
15000
20000
25000
30000
GDP per capita
35000
40000
45000
Aus tralia
50000
No
correlation
Rs = 0.26
Other variables are more important here
- Climate regions and variety within one nation
- Water availability, rivers, lakes, reservoirs