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# MA8402 Important Questions Probability And Queuing Theory

MA8402 Important Questions Probability And Queuing Theory Regulation 2017 Anna University free download. Probability And Queuing Theory Important Questions MA8402 pdf free download.

## Sample MA8402 Important Questions Probability And Queuing Theory:

1. Define Random process. (Pg – 337)
Solution: A random process is a collection of random variables
{X(s,t)} that are functions of a real variable, namely t where s∈ (sample space) and t∈T(parameter set). MA8402 Important Questions Probability And Queuing Theory

2. Give the classification of Random Processes.(Pg – 338)
Solution: Discrete random sequence, Continuous random sequence,
Discrete random process, Continuous random process.

3. Define Stationary processes. (Pg – 339)
Solution: If certain probability distribution or averages do not depend
on t, then the random process {X(t)} is called stationary. MA8402 Important Questions Probability And Queuing Theory

4. Define SSS process.(Pg – 340)
Solution: A random process is called a strongly stationary process or
strict sense stationary process, if all its finite dimensional distributions
are invariant under translation of time parameter.

5. Define WSS process.(Pg – 341)
Solution: A random process {X(t)} with finite first and second order
moments is called a weakly stationary process or covariance
stationary process or wide-sense stationary process, if its mean is a
constant and the auto correlation depends only on the time difference.

6. Is Poisson process covariance stationary? Justify.(Pg – 343)
Solution: No. Mean of poisson process = λt ≠ a constant. MA8402 Important Questions Probability And Queuing Theory

7. Show that the random process X(t)=A cos(w0t + θ) is WSS,
if A and w0 are constants and θ is a uniformly distributed RV in (0 , 2π).
(Pg – 344)
Solution: Mean = 0 = a constant.
Autocorrelation = (A2/2)cosw0 (t1 – t2).
Hence WSS process.

8. If {X(t)} is a wss process with autocorrelation R(τ)=Ae-α|τ| ,
determine the second-order moment of the RV X(8) – X(5).
Solution: 2A(1 – e-3α) MA8402 Important Questions Probability And Queuing Theory

9. Define Markov process. (Pg – 446)
Solution: Markov process is one in which the future value is
independent of the past values, given the present value

 Subject name Probability And Queuing Theory Short Name PQT Semester 4 Subject Code MA8402 Regulation 2017 regulation

MA8402 Probability And Queuing Theory Important 16 mark Questions

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