from the attached data set
Guidelines:
Final Project for Graduate Students
Note: The
final project is only for
students enrolled in this course as graduate students.
Overview: For
the final project, you are to find and analyze a dataset and write up your
results in a report (no longer than 10 pages double-spaced). The project is
intended to be an application of the skills you have learned in this course in
a less structured setting than in an exam or a problem set. The steps required
for the project include finding an appropriate dataset, conducting the
statistical analysis, and writing up findings.
Guidance:
Please post questions related to the final project on the Canvas discussion
board or reach out to your assigned teaching assistant. There will be a sample
final project to provide guidance to students.
I. Obtaining
Data: If you already have or found a dataset that you wish to
analyze, then you may use that dataset for the final project. If you do not
have a dataset, then you are free to analyze one of the datasets used in the
problem sets or lectures that are posted on the course website.
II. Conducting
the Analysis: The statistical analyses do not need to be
exhaustive. However, the analyses should be appropriate to the research
question and the data type and adhere to the grading rubric.
III. Writing
the Report: After conducting your analysis,
you need to write up your results in a paper no longer than 10 pages
double-spaced, Times New Roman, 12-pt font. The 10-page length includes tables
and graphs but excludes the Works Cited page. Graduate students must include at
least two peer-reviewed citations in the Works Cited paper, as the goal is for
you to learn how to identify and integrate relevant outside sources into the
context of data analysis. Please upload the completed work in Word format so
the teaching team could provide feedback as comments. Late submissions will
incur a 5-point deduction per each day late (i.e., a report submitted one
minute after the deadline (indicated on the syllabus) will be subject to a
five-point deduction, a report submitted 1.5 days late will be subject to a
10-point deduction). No submissions will be accepted 10 days after the
deadline.
The text of your report should follow this format, with
recommended page lengths and a brief description of what is expected:
1.
Abstract (50-300
words): Very short summary of the data, methods, and results
2.
Introduction (no
more than 1 page): Briefly outline your research question and your reasons for
conducting the analysis.
3.
Data
and Methods (no more than 1-2 pages): Describe your dataset,
including the number and type of observational units in addition to the types
of variables used in the analysis. In addition, outline and explain the
statistical techniques you are conducting.
4.
Results (approximately
3-5 pages): Present your findings from the data analysis using relevant tables
and graphs. Make sure to explain your results clearly rather than simply
cut-and-pasting tables or graphs.
5.
Conclusion (approximately
1-2 pages): Summarize your main findings, briefly describe the weaknesses of
your analysis, and outline implications for future research.
The following is the grading criteria that will be used for the final
project.
Format |
10 points |
Is the paper of the required length? (5 points) |
|
Abstract |
10 points |
Is an overview of the paper provided? (8 points) |
|
Introduction |
20 points |
Does the Introduction persuasively communicate the importance of the |
|
Data and |
20 points |
Is there a discussion – of where the data was obtained from? (4 points) – of which instrument was used, such as R Studio or Excel? (2 – substantiating the statistical methods used (10 points)? Are there descriptive statistics that provide the reader with an |
|
Results |
20 points |
Were at least two different inferential statistical methods used |
|
Conclusion |
18 points |
Does the section revisit the statistical findings and expand upon |
|
Works |
2 points |
Does the Works Cited page list the two or more peer-reviewed sources |
|