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Section 2-3/Addition Rules     35


                         5"#-& t 2E-1  Average Frequencies and Operations in TPC-C
                        Transaction  Frequency    Selects    Updates     Inserts    Deletes   Nonunique     Joins
                                                                                                Selects
                      New order        43          23         11          12          0           0          0
                      Payment          44           4.2        3           1          0           0.6        0
                      Order status      4          11.4        0           0          0           0.6        0
                      Delivery          5         130        120           0         10           0          0
                      Stock level       4           0          0           0          0           0          1


                                                      (
                          (
                     (a)  P A∩ B)   (b) P A( ′)    (c)  P A∪ B)        2-79.  Similar to the hospital schedule in Example 2-11, suppose
                                        (
                          (
                     (d)  P A∪ )    (e) P A′ ∩ B′)                     that an oper ating room needs to schedule three knee, four hip,
                              B′
                                                                       and ive shoulder surgeries. Assume that all schedules are equally

                     2-75.  A Web ad can be designed from four different colors,   likely. Determine the probability for each of the following:
                     three font types, i ve font sizes, three images, and i ve  text   (a)  All hip surgeries are completed before another type of surgery.
                     phrases. A speciic design is randomly generated by the Web   (b) The schedule begins with a hip surgery.

                     server when you visit the site. If you visit the site i ve times,   (c) The irst and last surgeries are hip surgeries.

                     what is the probability that you will not see the same design?  (d) The irst two surgeries are hip surgeries.

                     2-76.  Consider the hospital emergency room data in Example
                     2-8. Let A denote the event that a visit is to hospital 4, and let B  2-80.  Suppose that a patient is selected randomly from the
                     denote the event that a visit results in LWBS (at any hospital).   those described in Exercise 2-57. Let A denote the event that
                     Determine the following probabilities.            the patient is in the group treated with interferon alfa, and let
                                                      (
                          (
                     (a)  P A∩ B)   (b) P A( )′     (c)  P A∪ B)       B denote the event that the patient has a complete response.
                          (
                                        (
                     (d)  P A∪ )    (e) P A′ ∩ B′)                     Determine the following probabilities.
                              B′
                     2-77.  Consider the well failure data in Exercise 2-53. Let A  (a)  P A( )     (b)  P B( )
                     denote the event that the geological formation has more than   (c)  P A( ∩  B)  (d) P A( ∪  B)  (e) P A( ′  B)
                     1000 wells, and let B denote the event that a well failed. Deter-  2-81.  A computer system uses passwords that contain
                     mine the following probabilities.                 exactly eight characters, and each character is one of 26 low-
                                                      (
                          (
                     (a)  P A∩ B)   (b) P A( )′     (c)  P A∪ B)       ercase letters (a–z) or 26 uppercase letters (A–Z) or 10 inte-
                     (d)  P A∪ )    (e) P A′ ∩ B′)                     gers (0–9). Let Ω  denote the set of all possible passwords,
                                        (
                          (
                              B′
                                                                       and let A and B denote the events that consist of passwords
                     2-78.  Consider the bar code in Example 2-12. Suppose that all
                     40 codes are equally likely (none is held back as a delimiter).   with only letters or only integers, respectively. Suppose that
                     Determine the probability for each of the following:  all passwords in Ω are equally likely. Determine the probabil-
                     (a)  A wide space occurs before a narrow space.   ity of each of the following:
                     (b) Two wide bars occur consecutively.            (a)  A               (b)  B
                     (c)  Two consecutive wide bars are at the start or end.  (c)  A password contains at least 1 integer.
                     (d) The middle bar is wide.                       (d)  A password contains exactly 2 integers.
                     2-3      Addition Rules
                                         Joint events are generated by applying basic set operations to individual events. Unions of events,
                                         such as A∪ B; intersections of events, such as A∩  B; and complements of events, such as A′—are
                                         commonly of interest. The probability of a joint event can often be determined from the probabili-
                                         ties of the individual events that it comprises. Basic set operations are also sometimes helpful in
                                         determining the probability of a joint event. In this section, the focus is on unions of events.
                     Example 2-19    Semiconductor Wafers  Table 2-1 lists the history of 940 wafers in a semiconductor manu-
                                     facturing process. Suppose that 1 wafer is selected at random. Let H denote the event that the
                     wafer contains high levels of contamination. Then, P H( ) = 358 940.
                                                                          /
                                                                                                        (
                                                                                              /
                        Let C denote the event that the wafer is in the center of a sputtering tool. Then, P C( ) = 626 940 . Also, P H ∩ C) is the
                     probability that the wafer is from the center of the sputtering tool and contains high levels of contamination. Therefore,
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