LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034
M.Sc. DEGREE EXAMINATION – STATISTICS
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FIRST SEMESTER – NOV 2006
ST 1810 – ADVANCED DISTRIBUTION THEORY
(Also equivalent to ST 1806/1803)
Date & Time : 31-10-2006/1.00-4.00 Dept. No. Max. : 100 Marks
SECTION – A
Answer all the questions (10 x 2 = 20)
- Define truncated distribution and give an example.
- Show that geometric distribution satisfies lack of memory property.
- Define bivariate binomial distribution.
- If (X1,X 2) is bivariate Poisson, find the marginal distributions.
- If (X1,X 2) is bivariate normal, find the distribution of X1 – X 2 .
- Define bivariate exponential distribution of Marshall – Olkin.
- Find the mean of non-central chi-square distribution.
- Explain compound distribution.
- Let X 1 ,X2 ,X 3 be independent N(0,1) random variables. Examine whether
X12 + X2 2 + 2X3 2 – X1X2 + 2X2X3 has a chi-square distribution.
- Let X 1 ,X2 ,X 3,X4 be independent N(0,1) random variables. Find the MGF of X1X2+ X3X4.
SECTION – B
Answer any five questions (5 x 8 = 40)
- For a power series distribution, state and establish a recurrence relation satisfied by the
cumulants.
- For a lognormal distribution, show that mean > median > mode.
- State and establish the additive property for bivariate binomial distribution.
- Derive the conditional distributions associated with bivariate Poisson distribution.
- If X = (X1,X 2)/ is bivariate normal with mean vector m and dispersion matrix S , then show that
a/ X and b/ X are independent if and only if a/ S b = 0.
- If X = (X1,X 2)/ is bivariate exponential, find the distribution of Min{ X1,X 2}.
- State and establish the additive property for noncentral chi-square distribution.
- If X has Np(m , S) distribution, then show that ( X – m )/ S -1(X – m ) is distributed as chi-square.
SECTION – C
Answer any two questions (2 x 20 = 40)
19 a) State and establish a characterization of exponential distribution.
- b) Let X1, X2, …,Xn denote a random sample from IG(m, l). Show that
- = S Xi /n follows IG distribution
- ii) lV = l (S 1/Xi – 1/ ) follows chi-square distribution
and iii) and V are independent.
20 a) State and establish a relation between bivariate binomial and bivariate Poisson distributios.
- b) Define bivariate beta distribution.Derive its probability density function.
21 a) State and establish a characterization of bivariate exponential distribution.
- b) Define non-central F distribution and derive its mean and variance.
22 a) State and prove Cochran theorem.
- b) Given a random sample from normal distribution, using the theory of quadratic forms, show
that the sample mean and the sample variance are independent.
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