**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 |

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