Page 274 - DMTH404_STATISTICS

Statistics

Notes M   M  M 

5. The .................. E(X )  EX   as M, so EX  E(X ) E(X )   and we have lim
i i i i i
inf S /n   which imlies the desired result.
n n
6. If EX =    then as t  , N /t  1/ a.s. ..................
1 t
19.5 Review Questions

1. Discuss the strong law of large number.

2. Discuss examples related to large number.
Answers: Self Assessment

1. Probability Theory 2. X n 3. 4E|X |  4. 2y  k y k  2  4

1
5. monotone convergence theorem implies 6. (1/ = 0)

19.6 Further Readings

Books Sheldon M. Ross, Introduction to Probability Models, Ninth Edition, Elsevier
Inc., 2007.
Jan Pukite, Paul Pukite, Modeling for Reliability Analysis, IEEE Press on
Engineering of Complex Computing Systems, 1998.

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