Which of the following best describes the role of a 'generative model' in probabilistic programming?
Question 2
In probabilistic programming, what is the primary role of a 'stochastic' variable?
Question 3
Consider a probabilistic program designed to model the success rate of a marketing campaign. If the program defines a variable $S$ representing the number of successful conversions out of $N$ total attempts, which distribution is most appropriate for $S$?
Question 4
Which of the following statements accurately describes the concept of 'model checking' in probabilistic programming?
Question 5
In the context of automated inference for complex probabilistic models, what is the primary benefit of using techniques like Markov Chain Monte Carlo (MCMC)?
