Proposed Syllabus for the courses of Ph.D. Programme in Mathematics under VTU for 2012-13
GROUP I
Sl.
No
Name of the subject
GROUP II
Sl.
No
Name of the subject
GROUP III
Sl.
No
Name of the subject
GROUP IV
Sl.
N
o
Name of the subject
1
Algebraic graph th

1
Probability, conditional probability and independence event
MGM563
CHAPTER 1:
Probability, Conditional Probability and Independence
Introduction:
Statistics involve collecting, classifying, summarizing, organizing, analyzing and interpreting
data. Due t

MGM563 STATISTICAL INFERENCE
GROUP ASSIGNMENT
GROUP 1:
A1a.
For three events A, B, and C, we know that
A and C are independent,
B and C are independent,
A and B are disjoint,
,
Find
,
2
11
3
P AC
P B C
P A B C
3
4
12
,
P A P( B)
and
P(C )
.
A1b.
You ta

Independent event versus dependent event
Events can be "Independent", meaning each event is not affected by any other events.
Example 1:
Each toss of a coin is a perfect isolated thing.
What it did in the past will not affect the current toss.
But events

Chapter 3: Exponential Distribution
&Poisson Process
Definitions
Properties
Modeling and Parameters
Applications
OR372-Dr.Khalid Al-Nowibet
1
3.1 Exponential Distribution
Definition
A random variable T follows the exponential distribution with
rate >

MGM 563
STATISTICAL INFERENCE
VENUE: BT204
LECTURE: FRIDAY(3.00 6 P.M.)
INSTRUCTOR: DR. SEK SIOK KUN
OVERVIEW
Aims
The main objective of this course is to introduce
students to basic statistical theory at an
advanced level.
Description
The course will cov

Common Derivatives and Integrals
Derivatives
Basic Properties/Formulas/Rules
d
( cf ( x ) ) = cf ( x ) , c is any constant. ( f ( x ) g ( x ) ) = f ( x ) g ( x )
dx
d n
d
x ) = nx n-1 , n is any number.
( c ) = 0 , c is any constant.
(
dx
dx
f f g - f g