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2 pages or 600 word essays- MLA style- Use the data in the Attachment- For two different people

Microtheme Based on EIA Dataset

 I need 2 different essays on the same topic listed below. So, in the end, you will be preparing 2 documents with 2 different writing styles. These are the same assignment for me and my friend.

PLEASE FOLLOW THE INSTRUCTIONS.

            Write a microtheme (a 2-page or 600-word essay) in MLA style referencing one of the following datasets from the Energy Information Administration website:

 

1) U.S. Electricity Profiles: http://www.eia.gov/electricity/state/

 

2) Petroleum Imports to U.S. by Country: http://www.eia.gov/petroleum/imports/companylevel/

 

3) U.S. State Energy Profiles: http://www.eia.gov/state/index.cfm?ref=bookshelf

            (look at raw data under map)

 

4) State-Level Energy-Related CO2 Emissions: http://www.eia.gov/environment/emissions/state/analysis/

            (if you select #4, select only one of the available datasets on the right of the page).

 

How to approach this assignment:

 

a) Study the table you select and identify, discuss, and reference the patterns or “stories” in the dataset source. See the section in Chapter 9 called “How Tables Contain a Variety of Stories” (202-204).

 

b) Provide a brief summary of the data, including the main observations and conclusions represented in the dataset.

 

c) Based on the patterns or “stories” you have identified from the dataset, develop a supportable claim.

 

d) To support your claim, create and embed a graph into your argument by making inferences from your dataset, doing calculations, and converting the tabular data (dataset) into a bar or line graph. Be sure to label and title your graph (see “Special Strategies for Framing Statistical Evidence” on pp. 100-101). Follow the rule of independent redundancy: “the graphic should be understandable without the text; the text should be understandable without the graphic; the text should repeat the most important information in the graphic” (207).

 

e) Argue/defend the overall conclusions you have interpreted from the dataset.


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