FRM 2026 Part I Quantitative Analysis Probability Distributions Free Quiz 2

Practice FRM 2026 Part I Quantitative Analysis MCQs from Probability Distributions. Get instant results with Explanation.

General10 MCQs

1. What does the binomial distribution model?

A. Binomial distribution models the number of successes in n trialsB. Binomial distribution models the number of failures in n trialsC. Binomial distribution models the time to successD. Binomial distribution is continuous

2. What is the beta distribution?

A. Beta distribution is defined on the interval (-∞, ∞)B. Beta distribution is used for unbounded variablesC. Beta distribution is the same as normalD. Beta distribution is defined on [0,1] and models proportions

3. What is the gamma distribution?

A. Gamma distribution is discreteB. Gamma distribution models waiting times and includes exponential as a special caseC. Gamma distribution is symmetricD. Gamma distribution is used for proportions

4. What is the shape of the uniform distribution?

A. Uniform distribution has a bell-shaped densityB. Uniform distribution has a decreasing densityC. Uniform distribution has a constant density over [a, b]D. Uniform distribution has an increasing density

5. What is the relationship between Bernoulli and binomial distributions?

A. Bernoulli distribution is binomial with n=1B. Bernoulli distribution is Poisson with λ=1C. Bernoulli distribution is normal with μ=1D. Bernoulli distribution is exponential with λ=1

General10 MCQs

6. What does the geometric distribution model?

A. Geometric distribution models the number of successes in n trialsB. Geometric distribution models the number of failures before the first successC. Geometric distribution is the same as binomialD. Geometric distribution models the number of trials to get the first success

7. What does the negative binomial distribution model?

A. Negative binomial distribution models the number of successes before a specified number of failuresB. Negative binomial distribution models the number of trials to achieve r successesC. Negative binomial distribution is the same as PoissonD. Negative binomial distribution is used for normal data

8. What are the characteristics of the Cauchy distribution?

A. Cauchy distribution has a finite mean and varianceB. Cauchy distribution is symmetric and has thin tailsC. Cauchy distribution has heavy tails and no finite mean or varianceD. Cauchy distribution is the same as normal

9. What is a mixture distribution?

A. Mixture distribution combines multiple distributionsB. Mixture distribution is a single distributionC. Mixture distribution is only used for discrete dataD. Mixture distribution is the same as normal

10. What defines a multivariate normal distribution?

A. Multivariate normal distribution has a single parameterB. Multivariate normal distribution is used for univariate dataC. Multivariate normal distribution is defined by a mean and varianceD. Multivariate normal distribution is defined by a mean vector and covariance matrix

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