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