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Chapter 3

88. Refer to the Baseball 2005 data, which reports information on the 30 major league teams for the 2005 baseball season.

a. Select the variable team salary and find the mean, median, and the standard deviation.

b. Select the variable that refers to the age the stadium was built. (Hint: Subtract the year in which the stadium was built from the current year to find the stadium age and work with that variable.) Find the mean, median, and the standard deviation.

c. Select the variable that refers to the seating capacity of the stadium. Find the mean, median, and the standard deviation.

Variables

x1 _ Team

x2 _ League (American _ 1, National _ 0)

x3 _ Built (year stadium was built)

x4 _ Size (stadium capacity)

x5 _ Surface (natural _ 0, artificial _ 1)

x6 _ Salary (total 2005 team salary $ Mil)

x7 _ Wins

x8 _ Attendance (total annual for team)

x9 _ Batting

x10 _ ERA (earned run average)

x11 _ HR (home runs)

x12 _ Errors

x13 _ SB (stolen bases)

x14 _ Year

x15 _ Average player salary ($)

30 Teams

Team League, Built, Size, Surface, Salary, Wins, Attendance, Batting, ERA, HR, Errors, SB, Year, Average,

x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15

Boston 1 1912 33,871 0 123.5 95.0 2,847,798 0.281 4.74 199 XXX XX XXXX 512,930

New York Yankees 1 1923 57,746 0 208.3 95.0 4,090,440 0.276 4.52 229 95 84 1990 578,930

Oakland 1 1966 43,662 0 55.4 88.0 2,108,818 0.262 3.69 155 88 31 1991 891,188

Baltimore 1 1992 48,262 0 73.9 74.0 2,623,904 0.269 4.56 189 XXX XX XXXX 1,084,408

Los Angeles Angels 1 1966 45,050 0 97.7 95.0 3,404,636 0.270 3.68 147 87 XXX XXXX X,120,254

Cleveland 1 1994 43,368 0 41.5 93.0 2,014,220 0.271 3.61 207 XXX XX XXXX 1,188,679

Chicago White Sox 1 1991 44,321 0 75.2 99.0 2,342,804 0.262 3.61 200 94 XXX XXXX X,071,029

Toronto 1 1989 50,516 1 45.7 80.0 2,014,995 0.265 4.06 136 95 72 1996 1,176,967

Minnesota 1 1982 48,678 1 56.2 83.0 2,034,243 0.259 3.71 134 XXX XXX XXXX X,383,578

Tampa Bay 1 1990 44,027 1 29.7 67.0 1,141,915 0.274 5.39 157 XXX XXX XXXX X,441,406

Texas 1 1994 52,000 0 55.8 79.0 2,525,259 0.267 4.96 260 XXX XX XXXX 1,720,050

Detroit 1 2000 40,000 0 69.1 71.0 2,024,505 0.272 4.51 168 XXX XX XXXX 1,988,034

Seattle 1 1999 45,611 0 87.8 69.0 2,724,859 0.256 4.49 130 86 XXX XXXX X,264,403

Kansas City 1 1973 40,529 0 36.9 56.0 1,371,181 0.263 5.49 126 XXX XX XXXX 2,383,235

Atlanta 0 1993 50,062 0 86.5 90.0 2,520,904 0.265 3.98 184 86 92 2003 2,555,476

Arizona 0 1998 49,075 0 62.3 77.0 2,059,327 0.256 4.84 191 94 67 2004 2,486,609

Houston 0 2000 42,000 0 76.8 89.0 2,805,060 0.256 3.51 161 89 XXX XXXX X,632,655

Cincinnati 0 2003 42,059 0 61.9 73.0 1,923,254 0.261 5.15 222 104 72

New York Mets 0 1964 55,775 0 101.3 83.0 2,827,549 0.258 3.76 175 106 153

Pittsburgh 0 2001 38,127 0 38.1 67.0 1,817,245 0.259 4.42 139 117 73

Los Angeles Dodgers 0 1962 56,000 0 83.0 71.0 3,603,680 0.253 4.38 149 106 58

San Diego 0 2004 42,445 0 63.3 82.0 2,869,787 0.257 4.13 130 109 99

Washington 0 1961 56,000 0 48.6 81.0 2,730,352 0.252 3.87 117 92 45

San Francisco 0 2000 40,800 0 90.2 75.0 3,181,020 0.261 4.33 128XXXXX Louis 0 1966 49,625 0 92.1 100.0 3,542,271 0.270 3.49 170 100 83

Florida 0 1987 42,531 0 60.4 83.0 1,852,608 0.272 4.16 128 103 96

Philadelphia 0 2004 43,500 0 95.5 88.0 2,665,304 0.270 4.21 167 90 116

Milwaukee 0 2001 42,400 0 39.9 81.0 2,211,323 0.259 3.97 175 119 79

Chicago Cubs 0 1914 38,957 0 87.0 79.0 3,100,092 0.270 4.19 194 101 65

Colorado 0 1995 50,381 0 48.2 67.0 1,914,385 0.267 5.13 150 118 65

Chapter 5

56. Assume the likelihood that any flight on Northwest Airlines arrives within 15 minutes of the scheduled time is .90. We select four flights from yesterday for study.

a. What is the likelihood all four of the selected flights arrived within 15 minutes of the scheduled time?

b. What is the likelihood that none of the selected flights arrived within 15 minutes of the scheduled time?

c. What is the likelihood at least one of the selected flights did not arrive within 15 minutes of the scheduled time?

Chapter 6

64. An internal study by the Technology Services department at Lahey Electronics revealed company employees receive an average of two emails per hour. Assume the arrival of these emails is approximated by the Poisson distribution.

a. What is the probability Linda Lahey, company president, received exactly 1 email between 4 P.M. and 5 P.M. yesterday?

b. What is the probability she received 5 or more email during the same period?

c. What is the probability she did not receive any email during the period?

Chapter 7

50. Fast Service Truck Lines uses the Ford Super Duty F-750 exclusively. Management made a study of the maintenance costs and determined the number of miles traveled during the year followed the normal distribution. The mean of the distribution was 60,000 miles and the standard deviation 2,000 miles.

a. What percent of

Chapter 3

88. Refer to the Baseball 2005 data, which reports information on the 30 major league teams for the 2005 baseball season.

a. Select the variable team salary and find the mean, median, and the standard deviation.

b. Select the variable that refers to the age the stadium was built. (Hint: Subtract the year in which the stadium was built from the current year to find the stadium age and work with that variable.) Find the mean, median, and the standard deviation.

c. Select the variable that refers to the seating capacity of the stadium. Find the mean, median, and the standard deviation.

Variables

x1 _ Team

x2 _ League (American _ 1, National _ 0)

x3 _ Built (year stadium was built)

x4 _ Size (stadium capacity)

x5 _ Surface (natural _ 0, artificial _ 1)

x6 _ Salary (total 2005 team salary $ Mil)

x7 _ Wins

x8 _ Attendance (total annual for team)

x9 _ Batting

x10 _ ERA (earned run average)

x11 _ HR (home runs)

x12 _ Errors

x13 _ SB (stolen bases)

x14 _ Year

x15 _ Average player salary ($)

30 Teams

Team League, Built, Size, Surface, Salary, Wins, Attendance, Batting, ERA, HR, Errors, SB, Year, Average,

x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15

Boston 1 1912 33,871 0 123.5 95.0 2,847,798 0.281 4.74 199 XXX XX XXXX 512,930

New York Yankees 1 1923 57,746 0 208.3 95.0 4,090,440 0.276 4.52 229 95 84 1990 578,930

Oakland 1 1966 43,662 0 55.4 88.0 2,108,818 0.262 3.69 155 88 31 1991 891,188

Baltimore 1 1992 48,262 0 73.9 74.0 2,623,904 0.269 4.56 189 XXX XX XXXX 1,084,408

Los Angeles Angels 1 1966 45,050 0 97.7 95.0 3,404,636 0.270 3.68 147 87 XXX XXXX X,120,254

Cleveland 1 1994 43,368 0 41.5 93.0 2,014,220 0.271 3.61 207 XXX XX XXXX 1,188,679

Chicago White Sox 1 1991 44,321 0 75.2 99.0 2,342,804 0.262 3.61 200 94 XXX XXXX X,071,029

Toronto 1 1989 50,516 1 45.7 80.0 2,014,995 0.265 4.06 136 95 72 1996 1,176,967

Minnesota 1 1982 48,678 1 56.2 83.0 2,034,243 0.259 3.71 134 XXX XXX XXXX X,383,578

Tampa Bay 1 1990 44,027 1 29.7 67.0 1,141,915 0.274 5.39 157 XXX XXX XXXX X,441,406

Texas 1 1994 52,000 0 55.8 79.0 2,525,259 0.267 4.96 260 XXX XX XXXX 1,720,050

Detroit 1 2000 40,000 0 69.1 71.0 2,024,505 0.272 4.51 168 XXX XX XXXX 1,988,034

Seattle 1 1999 45,611 0 87.8 69.0 2,724,859 0.256 4.49 130 86 XXX XXXX X,264,403

Kansas City 1 1973 40,529 0 36.9 56.0 1,371,181 0.263 5.49 126 XXX XX XXXX 2,383,235

Atlanta 0 1993 50,062 0 86.5 90.0 2,520,904 0.265 3.98 184 86 92 2003 2,555,476

Arizona 0 1998 49,075 0 62.3 77.0 2,059,327 0.256 4.84 191 94 67 2004 2,486,609

Houston 0 2000 42,000 0 76.8 89.0 2,805,060 0.256 3.51 161 89 XXX XXXX X,632,655

Cincinnati 0 2003 42,059 0 61.9 73.0 1,923,254 0.261 5.15 222 104 72

New York Mets 0 1964 55,775 0 101.3 83.0 2,827,549 0.258 3.76 175 106 153

Pittsburgh 0 2001 38,127 0 38.1 67.0 1,817,245 0.259 4.42 139 117 73

Los Angeles Dodgers 0 1962 56,000 0 83.0 71.0 3,603,680 0.253 4.38 149 106 58

San Diego 0 2004 42,445 0 63.3 82.0 2,869,787 0.257 4.13 130 109 99

Washington 0 1961 56,000 0 48.6 81.0 2,730,352 0.252 3.87 117 92 45

San Francisco 0 2000 40,800 0 90.2 75.0 3,181,020 0.261 4.33 128XXXXX Louis 0 1966 49,625 0 92.1 100.0 3,542,271 0.270 3.49 170 100 83

Florida 0 1987 42,531 0 60.4 83.0 1,852,608 0.272 4.16 128 103 96

Philadelphia 0 2004 43,500 0 95.5 88.0 2,665,304 0.270 4.21 167 90 116

Milwaukee 0 2001 42,400 0 39.9 81.0 2,211,323 0.259 3.97 175 119 79

Chicago Cubs 0 1914 38,957 0 87.0 79.0 3,100,092 0.270 4.19 194 101 65

Colorado 0 1995 50,381 0 48.2 67.0 1,914,385 0.267 5.13 150 118 65

Chapter 5

56. Assume the likelihood that any flight on Northwest Airlines arrives within 15 minutes of the scheduled time is .90. We select four flights from yesterday for study.

a. What is the likelihood all four of the selected flights arrived within 15 minutes of the scheduled time?

b. What is the likelihood that none of the selected flights arrived within 15 minutes of the scheduled time?

c. What is the likelihood at least one of the selected flights did not arrive within 15 minutes of the scheduled time?

Chapter 6

64. An internal study by the Technology Services department at Lahey Electronics revealed company employees receive an average of two emails per hour. Assume the arrival of these emails is approximated by the Poisson distribution.

a. What is the probability Linda Lahey, company president, received exactly 1 email between 4 P.M. and 5 P.M. yesterday?

b. What is the probability she received 5 or more email during the same period?

c. What is the probability she did not receive any email during the period?

Chapter 7

50. Fast Service Truck Lines uses the Ford Super Duty F-750 exclusively. Management made a study of the maintenance costs and determined the number of miles traveled during the year followed the normal distribution. The mean of the distribution was 60,000 miles and the standard deviation 2,000 miles.

a. What percent of

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