Read this article: https://www.theatlantic.com/entertainment/archive/2017/08/13-reasons-why-demonstrates-cultures-power/535518/
Secondary Knowledge Claims:
Increased attention
towards suicide and how the larger awareness is brought to it the greater the
rates of suicide would be.
“increased
coverage of suicide in the media leads to a related increase in suicide
attempts.”
Case studies and
sample studies reflect the group as a whole.
“An editorial published at JAMA commenting on the study
stated that teens are particularly vulnerable when it comes to binge viewing.”
Correlation is
causation. The use of statistical data is one of justifying the harsh analyses
and appears to have taken in two events around the time and discounted them
instead of eliminating other factors, such as season, global events, and region
of search.
“JAMA Internal Medicine, used Google Trends
to monitor certain search terms regarding the subject of suicide, like “how to
commit suicide,” “suicide hotline number,” and “teen suicide.” Seventeen out of
the top 20 searches were significantly elevated, and the biggest increases came
with terms related to suicidal thoughts and ideation, like “how to kill
yourself.” The time period for searches ended on April 18 to preclude the
suicide of the former NFL player Aaron Hernandez, which could have influenced
data, and any searches related to the movie Suicide Squad were
discounted.”
RQ:
How do we interpret data in order to form knowledge?
To what extent should we rely on correlation to formulate
arguments and justify ramifications?
When often reading articles we run across many firm stances
often backed up by the studies, and other primary sources. However, when examining
these studies and primary sources you might find that many of them will not be
directly linked to the articles purpose and or rely on correlations as the main
backbone of the argument or answer.
For example when analyzing large groups in order to create
an argument which the data “directly” answers and follows the question and
gives the almost desired answer. When analyzing search results of scary clowns
and other related monsters, in order to analyzing the impact of the newest
adaptation Stephen King’s IT. We see
the study follows search queries for clowns, monster, and Stephen king, while
excluding searches for It or other results that are two words which one is IT.
These parameters are emplaced in order to prevent skewing of data, according
the analyzers. While seemingly responsible and justified this research excludes
many other parameters which should be emplaced in order to give better and more
accurate results that follow a more direct correlation which should be more on
the line of causation. Such as questionnaires querying people who research
topics similar to the movie IT this
will help show and justify the argument that these results are due to the movie
and no other factors.
This commitment and time which it would take in order to get
these results is far greater than the reward, as well as unrealistic, most people
would avoid answering questionnaires and would often not spend the time to give
much thought into them. Research studies are very difficult to find direct
correlations, and even when there is a very seemingly apart examples they are
often nearly impossible to trace back to a main source and have too many
factors that impact the result, which make it nearly impossible to prove
causation. An example of high correlation which will never achieve causation is
Smoking and increased Cancer rates, they display great positive correlation.
Many correlations are very reliable and do give great insight and better
understanding of a situation and links between seemingly unrelated subjects, we
cannot leave the all our faith on these correlations and must be demandingly
selective when analyzing and studying research.