counting-probablity 2-independent and dependent events

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  • 8/13/2019 Counting-Probablity 2-Independent and Dependent Events

    1/3

    Recap: Independent Events

    Example 1: I travel by bus and train on my journey to work. Given that P(bus late) is .! and

    independently P(train late) is ."# $al$ulate the probability that:a) both the bus and the train are late%

    b) either the bus or the train (or both) are late.

    &e $an answer this 'uestion by drawin a tree diaram. et * + bus late# , + train late.

    a) P(* and ,) + .! - ." + .

    b) P(* /0 ,) + 1 P(neither are late) + 1 .2 - .3 + .44.

    Example ": 5aroline plays a ame with a 6air $oin. 7he keeps throwin the $oin until a head is

    obtained# at whi$h point she stops. 5al$ulate the probability that:

    a) the ame 6inishes on the !rdthrow%

    b) the ame 6inishes in less than 8 attempts%

    $) the ame $ontinues 6or more than 1 throws.

    a) P(ame 6inishes on !rd

    o) + P(,ail ,9E ,ail ,9E 9ead) +

    1 1 1 1

    " " " 3 =b) P(ame 6inishes in less than 8 attempts) + P(6inishes on 1stor "nd or !rd or 4th o)

    *ut# P(ame 6inishes on 1sto) + P(9ead) +1

    "

    P(ame 6inishes on "ndo) + P(, ;< 9) +1 1 1

    " " 4 =

    P(ame 6inishes on 4th o) + P(,# ,# ,# 9) +1 1 1 1 1

    " " " " 1 =

    7o P(ame 6inishes in less than 8 oes) +1 1 1 1 18

    " 4 3 1 1

    + + + =

    $) P(ame $ontinues 6or more than 1 throws) + P(6irst 1 throws are tails) +

    1

    1 1

    " 1"4

    =

  • 8/13/2019 Counting-Probablity 2-Independent and Dependent Events

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    Dependent Events and Conditional Probability

    Introdu$tory example: ,he probability that it will be sunny tomorrow is1

    !. I6 it is sunny# the

    probability that 7usan plays tennis is4

    8. I6 it is not sunny# the probability that 7usan plays tennis is

    "

    8. =ind the probability that 7usan plays tennis.

    P(tennis) + P(sunny ;< tennis) > P(not sunny ;< tennis)

    +1 4 " " 3

    ! 8 ! 8 18 + =

  • 8/13/2019 Counting-Probablity 2-Independent and Dependent Events

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    Example ": /n averae I et up early ! days out o6 1# and et up late one day in 1.

    I 6oret somethin on " out o6 every 8 days on whi$h I am late and on one third o6 the days on whi$h

    I am early. I do not 6oret anythin on the days when I et up on time.

    (a) =ind the probability that I 6oret somethin.

    (b) 5on6irm that 6or 3? o6 the time I am neither 6oret6ul nor late.

    et E + et up early, + et up on time

    + et up late

    = + 6oret somethin

    =@ + don@t 6oret anythin

    ,he tree diaram then looks as 6ollows:

    a) P(6oret somethin) + P(E and =) > P(, and =) > P( and =)

    +! 1 1 " 2

    1 ! 1 1 8 8

    + + =

    b) ,he two situations where I am neither 6oret6ul nor late have been indi$ated on the tree diaram:7o P(neither 6oret6ul o6 late) +

    ! " 41

    1 ! 1 8 + =

    ,here6ore# on 3? o6 o$$asions I will neither 6oret anythin nor be late.

    A part (b)

    A part (b)