Estimating Activity Durations

Correct Answer: Monte Carlo Simulation

Monte Carlo Simulation is the best method to estimate the duration of construction tasks that seem to take a random amount of time each time they are performed. This is because Monte Carlo Simulation allows you to model the probability of different outcomes in a process where the outcome is uncertain, such as in these tasks. It does this through the use of random variables and iterations, providing a range of possible outcomes and the probabilities that they will occur for any choice of action On the other hand, Analogous Estimating involves using the actual duration of a similar previous task as the basis for estimating the duration of the current task. It wouldn't be as effective in this case because we are dealing with tasks that take a random amount of time each time they're performed Parametric Estimating would also not be the best fit. It relies on statistical relationships between historical data and other variables to calculate an estimate for activity parameters, such as cost, budget, and duration Lastly, Three-Point Estimating relies on multiple estimates (e.g., optimistic, pessimistic, and most likely) to derive an estimate. While it could theorically be used given that you have an idea of the range, the random nature of the task durations makes Monte Carlo Simulation a better estimation method in this case.

Correct Answer: Analogous Estimating

The most appropriate technique in this situation would be Analogous Estimating, as it's a technique that estimates the cost of project tasks using the actual cost of previous, similar tasks. Considering the fact that the tasks have been performed regularly in prior projects, Analogous Estimating can provide quick and reasonably accurate results. Monte Carlo Analysis, on the other hand, is used for risk analysis and not great for cost estimations. 3-point Estimating requires ample information about the possible variation in the task's performance, which may not always be accessible quickly. Lastly, Parametric Estimating uses statistical modeling and requires a lot of specific data, making it more time-consuming and less suited for quick estimates.

Correct Answer: Monte Carlo Analysis

The best technique to use in this scenario is Monte Carlo Analysis (id 152750). This technique is designed for risk analysis by creating models of possible results by substituting a range of values, a probability distribution, for any factor that has inherent uncertainty. It then calculates results over and over, each time using a different set of random values from the probability functions. The other techniques mentioned: 3-point Estimating, Analogous Estimating and Parametric Estimating, while useful in their own contexts, do not handle the situation of presenting various scenarios based on different estimates and their probabilities as effectively as Monte Carlo Analysis does. Therefore, they are not the optimal choices in this situation.