LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034
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B.Sc. DEGREE EXAMINATION – STATISTICS
FOURTH SEMESTER – April 2009
ST 4501 – DISTRIBUTION THEORY
Date & Time: 24/04/2009 / 9:00 – 12:00 Dept. No. Max. : 100 Marks
PART – A
Answer ALL Questions (10 x 2 =20)
- Show that the function is a probability density function.
- Define : Conditional Variance with reference to a bivariate distribution.
- Write the density function of discrete uniform distribution and obtain its mean.
- Find the mean of binomial distribution using its moment generating function.
- Find the maximum value of normal distribution with mean and variance.
- Write down the density function of bivariate normal distribution.
- Define : t Statistic.
- Find the density function of the random variable where is the distribution function of the continuous random variable .
- State central limit theorem for iid random variables.
- Obtain the density function of first order statistic in.
PART – B
Answer any FIVE Questions (5 x 8 =40)
- Let be iid RVs with common PDF . Write . Show that and are pairwise independent but not independent.
- Let be independent RVs with common density given by
Find the distribution of .
- Derive the characteristic function of Poisson distribution. Using the same find the first three central moments of Poisson distribution
- Establish the lack of memory property of geometric distribution
- Obtain the marginal distribution of X if (X,Y) follows bivariate normal distribution
- Obtain the moment generating function of chi-square distribution and hence establish its additive property
- Show that if , then
- Derive the formula for the density function of rth order statistic
PART – C
Answer any TWO Questions (2 x 20 =40)
- Let (X,Y) be jointly distributed with density
Find
- (a) Obtain the moment generating function of Normal distribution and hence find its
mean and variance
(b) Show that, if X and Y are independent poisson variates with parameters and
, then the conditional distribution of X given X+Y is binomial.
- Derive the density function of t distribution and obtain its mean.
- Write descriptive notes on the following :
- Stochastic independence
- Multinomial distribution
- Transformation of variables
- Stochastic Convergence
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