Question 1: Demonstrate the use of continuous probability distribution and discrete probability distribution for quantitative risk management using examples. Probability Distribution: Continuous probability distributions are widely used in modeling and simulations and represent uncertainty in values ​​such as activity durations or cost of project component work packages. These distributions can help us perform quantitative analysis. Discrete distributions can be used to represent uncertain events (a test result or a possible scenario in a decision tree) The most common numerical technique for PRA (analysis where a large number of variables need to be evaluated simultaneously) in evaluations of large-scale aviation risk is Monte Carlo simulation. Monte Carlo simulation integrates several assumptions, usually about exposure, to obtain possible risk distributions (or ranges) instead of point estimates. A continuous probability distribution can be displayed on a graph in the form of probability density functions (PDFs) or corresponding cumulative distribution functions (CDFs). A well-known example of a random variable is the number of points in a trade show launch. die. This number can be 1, 2, 3, 4, 5 or 6 and all six values ​​are equally probable, that is, they all have the same probability, 1/6. If such a die is rolled a large number of times, this implies, for example, that in about a sixth of all rolls a "6" will appear. Random variables are therefore completely characterized by a so-called "probability distribution". This specifies the probability of occurrence for each value the variable can take. In the case of continuous random variables, the corresponding probability distribution becomes a continuous function and... halfway down the paper... people have been given the right weight and multiplied by a seniority factor. I also incorporated the minimum length of stay and the results of a technical quiz. The cumulative factor was divided by the number of nights spent abroad. This has produced a figure of merit which also automatically ensures that the same people are not itemized over and over again. Finally, and most importantly, there was a lack of communication that needs to be addressed regarding this mechanism. So, I came up with a dashboard and displayed it in the assembly areas. This led to people knowing their turn. Since the system was a mathematical formula, there was no unfair bias that could creep in. Furthermore, I once gave an open opportunity for everyone to come and discuss any anomalies. This resulted in people being motivated and the conflict was resolved in a very legitimate way.