Running Head: DATA SCIENCE
Olympic Medalist Research Paper
You can, of course, repeat this exercise on any subject of your choice but here is an additional dataset about some
contrasting Olympic medallist data.
This exercise involves you working with an already acquired dataset to undertake the remaining three key steps of
examining, transforming and exploring your data to develop a deep familiarisation with its properties and qualities.
Complete the "Olympic Medalists" exercise located at the following link:
Working With Data
Provide at least a 10-page paper and a 10-15 slide presentation of your findings.
For each dataset:
Examination: Articulate the meaning of the data (its representativeness and phenomenon)
and thoroughly examine the physical properties (type, size, condition) noting down your descriptions in each
case. Compare what the datasets offer and contrast their differences.
Transformation: What could you do/would you need to do to clean or modify the existing data? What other data
could you imagine would be valuable to consolidate the existing data?
Exploration: Use a tool of your choice (common recommendations would be Excel, Tableau, R) to visually explore
the two datasets separately in order to deepen your appreciation of their physical properties and their discoverable
qualities (insights) to help you cement your understanding of their respective value.
1. Make the data stand out. The focus here is on revealing the structure of the data. It includes
discussion of how to fill the data region, transform data, choose an appropriate scale for an axis,
eliminate chart junk and other superfluous material, and avoid having graph elements interfere
with data, which includes topics such as over plotting, jittering, and transparency.
2. Add information. In addition to the usual conveyance of the importance of labeling axes and using legends, we also
discuss how to: use color and plotting symbols to convey additional information; add context with reference markers
and labels; and write comprehensive captions that are self-contained, describe the important features, and
summarize the conclusions drawn from the graph.
3. Key Questions and Interpretations of Data Analysis...
What is the message?
Get past the presentation to
Is the source reliable?
Think about the
How strong is the evidence Understand how this
information fits with other
Does the information
Determine whether the
information changes your
thinking and leads you to
What do the numbers
importance of risk requires
that you understand the
How does the risk compare Put the risk into context.
What actions can be taken Identify the ways you can
to reduce risk?
mitigate the risk to improve
What are the trade-offs?
Make sure you can live with
the trade-offs associated
with different actions.
What else do I need to
Focus on identifying the
information that would
help you make a better
Where can I get more
Find the information you
need to make a better
Purchase answer to see full