Lecture 2 Flashcards
What is a probability density function?
A probability density function (PDF) describes the likelihood of a continuous random variable taking on a specific value, where the area under the curve over an interval represents the probability of the variable falling within that interval.
What is a probability distribution? What is the difference between continuous and discrete distributions?
What is a CDF?
What is the SCV?
What are the three main cases of SCV and what do they imply?
What is the memoryless property?
What is the minimum property (of exponential distribution)?
What is the exponential distribution? (no formula’s, but concept)
What is the Poisson distribution?
The Poisson distribution is a discrete probability distribution that models the number of events occurring in a fixed interval of time or space, assuming the events occur independently and at a constant average rate.
What are the two requirements of the Inter Arrival Times of a Poisson process?
What is the superposition property?
What is the Thinning-out Property?
How are Possion and exponential related?
The Poisson distribution models the number of events in a fixed interval, while the exponential distribution models the time between consecutive events in the same Poisson process.
What is a Continuous-Time Markov Chain?
What is a Discrete-Time Markov chain?
What is a basic birth-and-death process?
What is the Insensitivity Property?
What are the steps for solving blocking probabilities (name 5)?
What are the components that need to be written down for a Continuous-Time Markov chain?
- N(t) := what does this imply in this case (likely buzy lines at time t)
- S := {0, 1, 2, …, N) (what is the possible state space)
- What are the transition rates for each increase and decrease (see image)
What is the Erlang B formula? What are the different parameters?
beta = mean call time, lambda = mean call arrival time, s or k number of channels available
What is the PASTA property?
How to set up the balance equations?
What is Little’s formula?
