A) A random process evolving over time. B) A process that remains constant over time. C) A process that only occurs in discrete steps. D) A deterministic process with fixed outcomes.
A) Average value of the process over time. B) Exact value of the process at a given time. C) Maximum value the process can attain. D) Set of all possible values that the process can take.
A) Exponential distribution B) Bernoulli distribution C) Normal distribution D) Uniform distribution
A) Measure of correlation between values at different time points. B) Exact form of the process at a given time. C) Maximum correlation possible for the process. D) Average of the process over time.
A) Markov process B) Geometric process C) Deterministic process D) Brownian motion
A) Behavior is completely random. B) Short-term analysis is sufficient for understanding long-term behavior. C) No inference can be made about long-term behavior. D) Long-term average behavior can be inferred from a single realization.
A) As the number of observations increases, sample averages converge to expected values. B) Expected values change with the number of observations. C) Sample averages diverge from expected values. D) Randomness decreases with more observations.
A) Calculates the average time spent in each state. B) Specifies the final state of the process. C) Determines the initial state of the process. D) Describes probabilities of moving to different states. |