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