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Internet Research AssignmentSubmit a single file containing text and images, do not submit a link.This research assignment asks you to use the Google Public Data website to examine several socioeconom
Internet Research Assignment
Submit a single file containing text and images, do not submit a link.
This research assignment asks you to use the Google Public Data website to examine several socioeconomic indicators and write up a short analysis of the connections between the variables and quality of life. (Reference: Google Public Data website http://www.google.com/publicdata (Links to an external site.)Links to an external site. )
1. Using the lists below, select the US plus four additional countries, each of the four from a different listed region.
2. Click on the link for the “World Development Indicators” page. Click on the box “Explore the Data”.
3. Click the button for LINE CHART in the upper right hand area and go to data element a. below. Use “Compare by : Country” and check the boxes for your 5 countries in the lower left list.
For each of the following 3 indicators 1, 2, 3: (Expand the headings for the data in the box on the upper left to get to the list of indicators for the category.)
1. Economic Policy and Debt – GDP per capita PPP constant 2005 International $
2. Health – Mortality rate, under 5
3. Environment – Energy use per capita OR Infrastructure – Mobile cellular subscriptions (per 100 people)
Paragraph 1: Do some very quick research on the indicator, then write a short paragraph on it that covers the following three points:
What is a definition of this indicator in your own words? (don’t cut and paste…)
What are the years of the data range for this indicator?
What does this indicator have to do with quality of life for people?
Graph: View a time-series graph with the indicator data on the Y-axis, capture each graph at the latest year possible with a screen shot and include it in your document,
Paragraph 2: Write a second short paragraph that covers these two points:
What trends do you see in the data - what’s the general pattern and who’s where?
How might government programs, history, cultural differences, industries, or other factors help explain the trends of the differences (or similarities) among the countries? (Use your informed imagination for this one, no need to do research.)
**Now repeat paragraph 1, the graph, and paragraph 2 for each of the other two indicators.
Click on button for BUBBLE CHART in the upper right. Click on Economic Policy - GDP per capita PPP constant 2005 International $ and select the option for X-axis; Click on Health - Life Expectancy in the data list and select the option for Y-axis; Click on Health – Health Expenditure per capita PPP and select the option for size. Click on Region and select Color by This. Click on the CHART OPTIONS button in the upper right and uncheck “Show non-selected bubbles.” Use the slider at the bottom of the chart to move through time. (If you have asterisks, then move the slider to see where the size data appear.) Capture your graph in 2012 to include in your document, and write a short paragraph that describes
A brief explanation of the definitions of the data included in the bubble chart.
Look at 1995 to 2015, what are the general trends? Which countries move the most in GDP per capita and life expectancy in this data range? Which countries move the least?
How might government programs, history, cultural differences, or other factors help explain what you see?
Write a concluding paragraph that explains why GDP per capita may only tell part of the story of quality of life. Use at least two examples from the countries and data from your earlier work for this assignment.
CHOOSE COUNTRIES:
(Four from different regions plus the USA )
AFRICA
Algeria
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Rep.
Chad
Comoros
Congo
Côte d'Ivoire
Dem. Rep. of Congo
Djibouti
Egypt
Equatorial Guinea
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Libya
Madagascar
Malawi
Mali
Mauritania
Mauritius
Morocco
Mozambique
Namibia
Niger
Nigeria
Rwanda
Sao Tome and Principe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Tunisia
Uganda
Zambia
Zimbabwe
ASIA
Afghanistan
Armenia
Azerbaijan
Bahrain
Bangladesh
Bhutan
Brunei Darussalam
Cambodia
China
Cyprus
Georgia
India
Indonesia
Iran
Iraq
Israel
Japan
Jordan
Kazakhstan
Korea, Democratic People's Republic of
Korea, Republic of
Kuwait
Kyrgyzstan
Laos
Lebanon
Malaysia
Maldives
Mongolia
Myanmar
Nepal
Oman
Pakistan
Philippines
Qatar
Saudi Arabia
Singapore
Sri Lanka
Syria
Tajikistan
Thailand
Turkey
Turkmenistan
United Arab Emirates
Uzbekistan
Viet Nam
Yemen
EUROPE
Albania
Andorra
Austria
Belarus
Belgium
Bosnia and Herzegovina
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Malta
Moldova
Monaco
Netherlands
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Slovak Republic
Slovenia
Spain
Sweden
Ukraine
United Kingdom
Yugoslavia (Serbia/Montenegro)
NORTH AMERICA
Antigua and Barbuda
Bahamas
Barbados
Belize
Canada
Costa Rica
Cuba
Dominica
Dominican Republic
El Salvador
Grenada
Guatemala
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Saint Kitts and Nevis
Saint Lucia
Saint Vincent and the Grenadines
Trinidad and Tobago
United States of America
OCEANIA
Australia
Fiji
Kiribati
Marshall Islands
Micronesia
Nauru
New Zealand
Palau
Papua New Guinea
Samoa
Solomon Islands
Tonga
Vanuatu
SOUTH AMERICA
Argentina
Bolivia
Brazil
Chile
Colombia
Ecuador
Guyana
Paraguay
Peru
Suriname
Uruguay
Venezuela
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