I explored “The world map of CO2 emissions”
under the category of the environment from Data Visualization Links. This project, designed by Craig
Bloodworth of the Information Lab, provides
me with a way to navigate the latest US Energy Information Administration(EIA)
data. I
tried to find a video using Google Earth for a world map of CO2
emission but I didn’t find any video through the visualization link. But this project helped me find out the most recent carbon
dioxide emission data for different countries in the world. I downloaded data
using excel from US Energy Information Administration (http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=90&pid=45&aid=8&cid=regions&syid=1980&eyid=2010&unit=MMTCD).https://docs.google.com/spreadsheet/ccc?key=0AonYZs4MzlZbdGNQcEtMeF9VSzZvU3FOQ0F4V3pDbFE#gid=0. Using this website
we can find up-to-date visualized CO2 emission data for different
countries and continents in the world. If you are interested to use this data in
your class please visit this website. I
introduced the data this week for the Global Warming project in Elementary
Statistic class.
I have already designed and
developed a project called “Global Warming” using this data in my MAT
120-Elementary Statistic Class. The pedagogical
objective of this project is to give the students a chance to explore in details
some issues related to global warming such as CO2 (carbon dioxide)
emissions. The objective of this specific project is to enhance students’
skills in mathematical modeling, particularly modeling using polynomials of
first through third degree and the quality of curve fit. Using CO2 gas
emission visualization data obtained from the US
EIA database,
students will learn how to model and construct a polynomial function to predict
CO2 emissions using polynomials of first (linear), second and third
degrees. Using CO2 data obtained from the Data Visualization link
(http://www.eia.gov) students did some preliminary
work for this project. Students constructed a linear regression model and curve
fit using SPSS and used a linear regression equation to predict the level of CO2 emissions after 10, 20 and
30 years. For your consideration, I provided
one student sample in the following figures though the student didn’t complete
project yet. Hopefully, I will provide you with some completed students sample
work in the next seminar, along with students’ reflections.
I also introduced in my
class some related videos regarding global warming called “New York's
Carbon Emissions Visualized” (Dr. Richard showed this video last seminar) and “Carbon
dioxide emissions map released on Google Earth” (https://www.youtube.com/watch?v=KAUf1bRIFxM).
My personal communication with students gave me the impression that they
enjoyed learning about global warming.
