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How can you calculate the probability of outcomes in risk analysis?

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Risk analysis is a process of identifying and assessing the potential impacts of uncertain events on a project, decision, or system. It can help you evaluate the trade-offs between different alternatives, optimize your resources, and mitigate the negative consequences of risks. One of the key steps in risk analysis is to calculate the probability of outcomes, which is the likelihood of a certain result occurring given a set of assumptions and inputs. In this article, you will learn how to calculate the probability of outcomes using different methods and tools, such as probability distributions, Monte Carlo simulation, and sensitivity analysis.

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Sreenath S

Data Science | Optimization | Machine Learning | IIT Bombay
Tácito Augusto Silva Leite

MSc. Risk Management | Executive Security Corp. & Inf. | Structuring & Restructuring Companies | Startup | CRO, ERM…
Charles Weko

Organization Analyst

1 Probability distributions

A probability distribution is a mathematical function that describes how likely a random variable is to take on different values. It can be represented by a table, a graph, or a formula. For example, a normal distribution is a bell-shaped curve that shows how often a variable deviates from its mean. A binomial distribution is a discrete function that shows how many successes or failures occur in a fixed number of trials. A uniform distribution is a flat line that shows that all values are equally likely. To calculate the probability of outcomes using a probability distribution, you need to identify the type of distribution that best fits your data, and then use the corresponding formula or tool to find the probability of a specific value or range of values. For example, if you want to find the probability that a project will be completed within 30 days, given that the average duration is 25 days and the standard deviation is 5 days, you can use a normal distribution and apply the z-score formula or a calculator to find the answer.

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Charles Weko

Organization Analyst
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I'm going to suggest that you can't really "calculate the probability" of most risk factors. In most cases, you just don't have sufficient data. So what do you do? Apply sensitivity analysis to the probability. What happens if the probability of an event is 20%? What if its 40%? Does it matter? If it matters, then you can try harder to determine a good estimate. But if it doesn't matter...well, don't worry. If you can't get a good estimate, get a good mitigation plan. In fact, the only real reason the probability matters is to soothe leadership's nerves when they don't have a mitigation strategy.

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2 Monte Carlo simulation

Monte Carlo simulation is a technique that uses random sampling to generate multiple scenarios and outcomes based on the probability distributions of the input variables. It can help you account for the uncertainty and variability in your data, and estimate the range and likelihood of possible results. To calculate the probability of outcomes using Monte Carlo simulation, you need to define the input variables and their distributions, specify the output variables and their relationships, and run the simulation for a large number of iterations. For example, if you want to find the probability that a project will be profitable, given that the revenue, cost, and demand are uncertain, you can use Monte Carlo simulation to generate random values for these variables and calculate the profit for each iteration. Then, you can analyze the distribution and statistics of the profit values and find the probability that the profit will be positive or exceed a certain threshold.

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3 Sensitivity analysis

Sensitivity analysis is a method that measures how the output variables change when the input variables vary within a certain range. It can help you identify the critical factors that affect your results, and evaluate the robustness and stability of your model or solution. To calculate the probability of outcomes using sensitivity analysis, you need to select the input variables and their ranges, vary one variable at a time or in combination, and observe the changes in the output variables. For example, if you want to find the probability that a project will meet its objectives, given that the scope, schedule, and quality are interdependent, you can use sensitivity analysis to adjust these variables and monitor the impact on the performance indicators. Then, you can determine the probability of achieving the desired outcomes under different scenarios and assumptions.

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4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Sreenath S

Data Science | Optimization | Machine Learning | IIT Bombay
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There are metrics like Value at Risk (VaR) and Conditional Value at Risk (CVaR). Value-at-risk (VaR) is generally used in finance to measure the risk in portfolios. It measures the minimum loss within an interval period at a given probability. CVaR is determined by using the weighted average of the “extreme” losses in the tail of the distribution of possible returns, beyond the value at risk (VaR) cutoff point. CVaR is also called expected shortfall. Though these metrics are popular in finance, these can also be extended to other domains and models can be built to minimize CVaR.

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Tácito Augusto Silva Leite

MSc. Risk Management | Executive Security Corp. & Inf. | Structuring & Restructuring Companies | Startup | CRO, ERM, DSE, ASE, CISO, CSO, AEO
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Calcular a probabilidade de resultados na análise de risco envolve quantificar a chance de um evento específico ocorrer. Isso pode ser feito usando dados históricos, informa??es de especialistas, análise estatística, ou modelos preditivos. Em termos simples, a probabilidade pode ser calculada dividindo-se o número de ocorrências de um evento pelo número total de observa??es possíveis. Para calcular a probabilidade de resultados na análise de risco, seguindo as diretrizes da ISO 31000 e ISO 31010, você precisa primeiro identificar os riscos e depois analisá-los. A plataforma t-Risk, oferece métodos como o Mosler, que analisa os riscos com base em 6 critérios pré-definidos. A ISO 31010 fornece várias técnicas para avalia??o de riscos.

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How can you calculate the probability of outcomes in risk analysis?

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1 Probability distributions

2 Monte Carlo simulation

3 Sensitivity analysis

4 Here’s what else to consider

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How can you calculate the probability of outcomes in risk analysis?

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1 Probability distributions

2 Monte Carlo simulation

3 Sensitivity analysis

4 Here’s what else to consider

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