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Quantifying Risks

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Running head: QUANTIFYING RISKS
Quantifying Risks
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QUANTIFYING RISKS 2
One of the places that I would like to visit during the vacation is the New York City. One
of the risks is that one may get lost in the Manhattan. Most of the tourists who visit the place get
lost in the Manhattan (Spira-Cohen, Caffarelli and Fung, 2017). However, the presence of the
trid grid system helps them in tracing the route. Another risk associated with visiting the site is
the presence of scams and frauds. The panhandlers seem to be corrupt and fraudulent a fat that
risks the security of the travelers (Spira-Cohen, Caffarelli and Fung, 2017). The picketers are
also common in the New York City meaning that a person should prepare adequately.
The risk that has the highest probability is the one of being lost in Manhattan. The
likelihood of this risk occurring is 0.9.Ideally, this is because research studies have evidenced
that most of the people who visit the New York City get lost in the place. The risk of being
attacked by the fraudulent individuals is 0.5 since the management of the city has made attempts
to employ a significant number of security individuals. However, the impact of this risk, if it
occurs, is higher as compared to the one of getting lost.

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Running head: QUANTIFYING RISKS Quantifying Risks Name Institution QUANTIFYING RISKS 2 One of the places that I would like to visit during the vacation is the New York City. One of the risks is that one may get lost in the Manhattan. Most of the tourists who visit the place get lost in the Manhattan (Spira-Cohen, Caffarelli and Fung, 2017). However, the presence of the trid grid system helps them in tracing the route. Another risk associated with visiting the site is the presence of scams and frauds. The panhandlers seem to be corrupt and fraudulent a fat that risks the security of the travelers (Spira-Cohen, Caffarelli and Fung, 2017). The picketers are also common in the New York City meaning that a person should prepare adequately. The risk that has the highest probability is the one of being lost in Manhattan. The likelihood of this risk occurring is 0.9.Ideally, this is because ...
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