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"Education is the most powerful weapon which you can use to change the world”
– Nelson Mandela

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Analysis and Interpretation Worksheet Part I: Analysis and Interpretation Interview Data: 1. Select an appropriate analytic procedure to code your interview data. 2. Code your data using a qualitativ...

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For starters I appreciate the feedback I received on my elevator speech because the girls did have good pointers for me to work on for the next speeches that will come my way. I did receive a comment...

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Deliverable 5

Deliverable 5

Q “Risk Management” covers a number of activities some of which are pure statistics. But modern financial risk management begins where statistics ends. Decisions for which enough data is to be estimated outcomes and probabilities accurately do not require risk management. Risk minimization is more appropriate in this system when to minimize the risk subject is expected to return in other constraints. Modern financial risk management was being invented to deal with this kind of situation ("What is Risk Management and Why is it Important?", 2020).

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Risk managers use a lot of statistics, generally the non-parametric ones. This requires non-statistical methods to estimate the border, but statistical methods to evaluate the non-statistical methods. This can also be performed in a reverse manner sometimes. Conventional statistical models are used to estimate distributions and thus to identify outliers. Sometimes this is even performed with the data that is not obviously relevant, as any glitch could be a sign of an important change ("The role of statistics in managing climate change-related disaster risks", 2020).