MS Word Report that contains answers to all Parts of the Exam a. Your report should be clear and professional with appropriate labeling and works cited

economics

Description

Please submit your written report with the answers in MS Word and your complete work in Tableau by saving all your work as *.twbx files (Tableau Package Workbook)


What to submit: 

1. MS Word Report that contains answers to all Parts of the Exam a. Your report should be clear and professional with appropriate labeling and works cited 


2. Tableau files (*twbx files) for Part 2 and Part 3 (two separate files) a. Your files should be clear and well organized


Part 1: Theory of Visualization (20%): Short Essay Questions (1-2 paragraphs each) 


1. Discuss the ways in which visual perception is used to create compelling graphs and charts? 

2. Please discuss how the use of three-dimensional graphs can lead to misunderstanding of the data and relationships? 

3. How does an aspect ratio of a graph affect our understanding of the information displayed by a graph? 

4. Scatterplots are often used to display correlation in the data; discuss how shape of scatterplots can identify meaningful patterns? 


Part 2: Applied Visualization (30%): Short Answers and Tableau 

1. Use the UW-Madison library scholarly article search tool and find an academic article in an economics journal about a topic of interest to you. Be creative. Screenshot one of the figures (graphs) in the paper, paste below, and answer the following questions: 


a. Describe what relationship the author intends to show the reader with the figure 

b. List four things the author(s) did correctly (with regard to this figure) 

c. List four criticisms of the figure d. List four suggested improvements for the author(s) 


2. Download the following dataset “pollution” from Canvas under “Final Exam” in Modules and upload to Tableau, then follow the directions below. (Note: your data work should be in Tableau and in your write-up should briefly describe the steps you took in Tableau.) 


a. Clean the dataset to eliminate the ‘total’ rows. Describe your process.

 b. Convert the dates from strings ‘month, year’ to numerical (date) values. Describe your process.


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