What relationships exist between the pre-election polling attributes and the 2020 election results that indicate that former President Trump would or could lose the election?
Use Table 1 and Table 2 to understand what information is available for the project. Download the RData files from this document.
Table 1
Data Dictionary for the Polling before 2020 Presidential Election Data
Column |
Description |
State |
The target location of the polling sample |
Candidate Names |
The candidate receiving the percentage of polling votes in pct |
Start Date |
The first day interviews were conducted for this poll |
End Date |
The last day interviews were conducted for this poll |
Pollster |
The name of the polling organization |
Sample Size |
The size of the sample |
Target Population |
Whether the population interviewed was adults a, registered voters rv, voters v, or likely voters lv |
Percentage |
The percentage of the vote the candidate in candidate_namereceived in the poll |
Poll Identification Number |
Specific poll the data is derived from |
Note. The data dictionary of the polling data leading up to 2020 presidential the election is adapted from FiveThirtyEight (2020).
Table 2
Data Dictionary for the Results of 2020 Presidential Election Data
Column |
Description |
State |
The location of the voting results |
Available Electoral Votes |
The number of electoral votes allocated to the state in the state field |
Biden |
The percentage of election votes Biden received |
Trump |
The percentage of election votes Trump received |
Note. The data dictionary of the 2020 presidential election results is adapted from Wikipedia (n.d.).
You will analyze the data in R. You will submit an R script file with programming that demonstrates the collection, cleaning, exploration, and analysis of the data. When you are conducting your research, you will come across key findings. A key finding is a graph that is interesting and must specifically relate to the overall objective of the research project. Only key findings are included in the research paper. Investigating critical findings from multiple perspectives in the programming will demonstrate your understanding of the weaknesses of visual analysis and prevent false conclusions. If you have done this correctly, there should be numerous figures in the programming that are not in the paper. Lastly, make sure that you provide interpretations of the information learned from each figure included in the paper. The report shall also include how these findings relate to the research objective.
When you think you’ve finished your analysis, revisit the objective. Did you achieve the objective? Did you provide an answer or answers to the research question? Were you thorough? Did you make sure that you did not misinterpret or misrepresent the results due to false conclusions?
Good to know
When you initialize the R script file for the assignment, make sure that the file begins with the three leading comments required in every script file. After these leading comments, call the necessary libraries and load the data before documenting other programming code. Don’t forget to use inline comments.
Submission Requirements
When you document this information, you will need to write it as paper. This is not a blog, a discussion, or a short answer paper. You will need to include an introduction, a topic sentence, supporting paragraphs, and a conclusion. Not great at writing? Go to Start Here in the main menu and look at the resources available to you. Make sure that you document your work using the standards of APA 7. To help with formatting, use the APA 7 student paper template.
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