Suppose we conduct independent Bernoulli experiments with probability of success p once every hour. We track the number of successes over time. Let T= {1,2,3,...}.
a) Define the state of this process at time t, Y(t).
b) What is the state space at time t?
a)
The state of this process at time t, Y(t) is the total number of successes from Bernoulli experiments till time t.
By definition of binomial distribution, Y(t) ~ Binomial(t, p)
b)
At time t, we can have from 0 to t successes.
The state space at time t is {0, 1, 2, 3, ..., t}
Suppose we conduct independent Bernoulli experiments with probability of success p once every hour. We track...
4. Suppose we conduct independent Bernoulli experiments with probability of success p once every hour. We track the number of successes over time. Let T 1,2,3,...). (a) Define the state of this process at time t, Y(t) (b) What is the state space at time t? (c) What distribution would each Y(t) have?
Suppose we conduct independent Bernoulli experiments with probability of success p once every hour. We track the number of successes over time. Let T = {1, 2, 3, . . .}. (a) Define the state of this process at time t, Y (t). (b) What is the state space at time t? (c) What distribution would each Y (t) have? (d) How are the random variables X(t) (from the Bernoulli process) and Y (t) related? (e) What would a plot...
4. Suppose we conduct independent Bernoulli experiments with probability of success p once every hour. We track the number of successes over time. Let T , 2, 3,...) (a) Define the state of this process at time t, Y(t) (b) What is the state space at time t? (c) What distribution would each Y(t) have? (d) How are the random variables X(t) (from the Bernouli process) and Y(t) related? (e) What would a plot of a realization of this process...
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