Which Excel function is used to fit a beta distribution in this material?

Enhance your skills with Monte Carlo Simulation in Business Risk Analysis. Study effectively with multiple-choice questions and detailed explanations. Prepare confidently for your exam!

Multiple Choice

Which Excel function is used to fit a beta distribution in this material?

Explanation:
The concept tested is how to generate Beta-distributed values from uniform random numbers using the inverse CDF method. To create samples that follow a Beta distribution, you map probabilities to outcomes with the inverse of the Beta CDF. The function that provides this inverse CDF is BETA.INV, which returns the value x for which the Beta CDF with given alpha and beta equals a specified probability p. In Monte Carlo style, you’d generate a uniform random p in (0,1) and then compute x = BETA.INV(p, alpha, beta) to obtain a Beta-distributed sample. This is why BETA.INV is the correct choice. Other functions either compute the forward CDF/PDF (like the Beta distribution’s CDF) or pertain to different distributions (for example, NORM.INV is for the normal distribution), so they don’t serve the purpose of generating Beta-distributed values from uniform inputs.

The concept tested is how to generate Beta-distributed values from uniform random numbers using the inverse CDF method. To create samples that follow a Beta distribution, you map probabilities to outcomes with the inverse of the Beta CDF. The function that provides this inverse CDF is BETA.INV, which returns the value x for which the Beta CDF with given alpha and beta equals a specified probability p. In Monte Carlo style, you’d generate a uniform random p in (0,1) and then compute x = BETA.INV(p, alpha, beta) to obtain a Beta-distributed sample. This is why BETA.INV is the correct choice. Other functions either compute the forward CDF/PDF (like the Beta distribution’s CDF) or pertain to different distributions (for example, NORM.INV is for the normal distribution), so they don’t serve the purpose of generating Beta-distributed values from uniform inputs.

Subscribe

Get the latest from Examzify

You can unsubscribe at any time. Read our privacy policy