LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034
B.Sc. DEGREE EXAMINATION – STATISTICS
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FOURTH SEMESTER – APRIL 2006
ST 4501 – DISTRIBUTION THEORY
(Also equivalent to STA 503)
Date & Time : 27-04-2006/9.00-12.00 Dept. No. Max. : 100 Marks
SECTION A
Answer ALL the Questions (10 ´ 2 = 20 Marks)
- Define Binomial distribution.
- Find the p.g.f. of Poisson distribution.
- Give any two applications of Geometric distribution.
- Write down the probability density function (p.d.f.) of Gamma distribution.
- State the mean of Beta distribution of II kind and the condition for it to exist.
- If X ~ N( 0, 1), what is the value of E(X4)?
- Write down the Mean deviation about median of a normal distribution.
- State the relation between c2 and F distributions.
- State the conditions under which Binomial distribution tends to a normal distribution.
- Define order statistics and give an example.
SECTION B
Answer any FIVE Questions (5 ´ 8 = 40 Marks)
- Let X have the distribution with p.m.f.
X : -1 0 1
Pr: 0.3 0.4 0.3
Find the distributions of (i) X2 (ii) 2X +3
- Find the mode of Binomial distribution.
- Derive the conditional distributions associated with a Trinomial distribution.
- Derive the mean and variance of Uniform distribution on (a,b).
- For N(m,s2) distribution, show that the even order central moments are given by m2n = 1.3…..(2n – 1) s2n ” n ³ 1.
- Show that the limiting form of Gamma distribution G(1, p ) as p ®µ, is normal distribution.
- Define Student’s t in terms of Normal and Chi-Squared variates and derive its p.d.f.
- Let
e– ( x – q ), x > q
f(x ; q) =
0, otherwise,
where q Î R. Suppose X1,X2,…,Xn denote a random sample of size n from the
above distribution find E(X(1)).
SECTION C
Answer any TWO Questions (2 ´ 20 = 40 Marks)
- (a)Let f(x, y) = 2, 0 < x < y < 1 be the joint p.d.f of (X,Y). Find the marginal and conditional distributions. Examine whether X and Y are independent.
(b) Derive the m.g.f of Trinomial distribution. (12 + 8)
- (a) Show that for a normal distribution Mean = Median = Mode.
(b) Show that, under certain conditions (to be stated), the limiting form of
Poisson distribution is Normal distribution. (15 +5)
- (a) Let the joint p.d.f of (X1, X2) be
f(, ) = exp(–), , > 0
Obtain the joint p.d.f. of Y1 = X1 + X2 and Y2 = X1 / (X1 + X2).
(b)Show that mean does not exist for Cauchy distribution. (12 +8)
- (a) Find the joint density function of i th and j th order statistics.
(b) Let X1,X2,…,Xn be a random sample of size n from a standard uniform
distribution. Find the covariance between X (1) and X (2). (6 + 14)