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Entertainment on a Cruise Ship
I read the cruise ship case after I watched both videos and read the first chapter, and I
am glad I did. The case was interesting to me because it stressed the notion that each
situation or variable is valuable and when forming research and data collection, one
must understand that many factors contribute to effective data analysis. I certainly
would not approach the entertainment issue from the ?deadbeat passenger?
perspective. I think that it is a counter productive approach. There is certain information
that the cruise ship does possess; they know for certain that people are not attending
their shows. They also know that they are paying their entertainment employees,
regardless of the turnout and also recouping the money necessary to pay them on the
backend when customers pay their fee.
If I were in charge of the entertainment, I would focus on the areas that would bring in
revenue, including increasing the attendance of the passengers and also the potential to
boost liquor sales. In order to get the passengers to the shows, it would be necessary to
understand why they are not attending and how they feel about the entertainment
through feedback. Gathering information from the passengers about how they view and
participate in entertainment on the cruise ship would be immeasurable. It would be
necessary to create demographical information and profiles of the customers. I would
more than likely employ a more rigid approach to collecting data, but also acknowledge
that the process could take an unexpected turn. I have some experience with scenario
planning from my undergraduate and former work experiences (also referenced in the
Common Sense video) so I would prepare and plan for different probability outcomes.
The lecture video
This week?s video lecture presented statistics in a very interesting format. I enjoyed
Hans Rosling explanation and use of the tool Gapminder. His presentation really
highlighted using visual representations of data in an enlightening way. Visual
representations give researchers, policy makers, and other professions more
encompassing views of data and an ability to see changes or shifts. In using his
example, Rosling discussed how controlled we, as humans, can be by our preconceived ideas when we don?t have the data in front us. In using visual representations
of data, like those presented with Gapminder, we are given access to more accurate
information and essentially a better place to draw conclusions from and make decisions.
More specifically, visual presentations of data allow for policy makers to study data in a
more accessible way about the citizens they represent and, in turn, make more
informed policy decisions. I found so much of his presentation interesting, especially the
data he provided on different countries and their growth and poverty levels. Watching
each country?s changes in comparison to one another over time was particularly
informative. Rosling points out how dangerous it is to use average data when
discussing different countries because there?s such a difference between them. For
example, the top 20 percent earners of one country may look quite different than the top
20 percent earners of another. He framed improvement of the world with real data in an
easy to consume way.

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