12.07.2015 Views

Fundamentals of Probability and Statistics for Engineers

Fundamentals of Probability and Statistics for Engineers

Fundamentals of Probability and Statistics for Engineers

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

96 <strong>Fundamentals</strong> <strong>of</strong> <strong>Probability</strong> <strong>and</strong> <strong>Statistics</strong> <strong>for</strong> <strong>Engineers</strong>Ex ample 4. 11. Problem: an inspection is made <strong>of</strong> a group <strong>of</strong> n televisionpicture tubes. If each passes the inspection with probability p <strong>and</strong> fails withprobability q (p ‡ q ˆ 1), calculate the average number <strong>of</strong> tubes in n tubes thatpass the inspection.Answer: this problem may be easily solved if we introduce a r<strong>and</strong>om variableX j to represent the outcome <strong>of</strong> the jth inspection <strong>and</strong> defineX j ˆ 1;0;Then r<strong>and</strong>om variable Y, defined byif the jth tube passes inspection;if the jth tube does not pass inspection.has the desired property that its value is the total number <strong>of</strong> tubes passing theinspection. The mean <strong>of</strong> X j isThere<strong>for</strong>e, as seen from Equation (4.38), the desired average number is given byWe can also calculate the variance <strong>of</strong> Y. If X 1 ,...,X n are assumed to beindependent, the variance <strong>of</strong> X j is given byEquation (4.41) then givesY ˆ X 1 ‡ X 2 ‡‡X n ;EfX j gˆ0…q†‡1…p† ˆp:m Y ˆ EfX 1 g‡‡EfX n gˆnp: 2 j ˆ Ef…X j p† 2 gˆ…0 p† 2 …q†‡…1 p† 2 p ˆ pq: 2 Y ˆ 2 1 ‡‡2 n ˆ npq:Ex ample 4. 12. Problem: let X 1 ,...,X n be a set <strong>of</strong> mutually independentr<strong>and</strong>om variables with a common distribution, each having mean m. Showthat, <strong>for</strong> every ">0, <strong>and</strong> as n !1,PY nm " ! 0; where Y ˆ X 1 ‡‡X n : …4:44†Note: this is a statement <strong>of</strong> the law <strong>of</strong> large numbers. The r<strong>and</strong>om variable Y / ncan be interpreted as an average <strong>of</strong> n independently observed r<strong>and</strong>om variablesfrom the same distribution. Equation (4.44) then states that the probability thatthis average will differ from the mean by greater than an arbitrarily prescribedTLFeBOOK

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!