ChartDataSheet_
This worksheet contains values required for MegaStat charts.
Boxplot 12/5/2012 16:43.50
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Dotplot 12/5/2012 16:44.17
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2012 Season
Team League Opened Team Salary Attendance Wins ERA BA HR Year Average Salary
Arizona National 1998 65.80 2080145 79 4.04 0.264 154 2000 1.99
Atlanta National 1996 89.60 2001392 67 4.41 0.251 100 2001 2.26
Baltimore American 1992 118.90 2281202 81 4.05 0.25 217 2002 2.38
Boston American 1912 168.70 2880694 78 4.31 0.265 161 2003 2.56
Chicago Cubs National 1914 117.20 2959812 97 3.36 0.244 171 2004 2.49
Chicago White Sox American 1991 110.70 1755810 76 3.98 0.25 136 2005 2.63
Cincinnati National 2003 117.70 2419506 64 4.33 0.248 167 2006 2.87
Cleveland American 1994 87.70 1388905 81 3.67 0.256 141 2007 2.94
Colorado National 1995 98.30 2506789 68 5.04 0.265 186 2008 3.15
Detroit American 2000 172.80 2726048 74 4.64 0.27 151 2009 3.24
Houston American 2000 69.10 2153585 86 3.57 0.25 230 2010 3.3
Kansas City American 1973 112.90 2708549 95 3.73 0.269 139 2011 3.31
LA Angels American 1966 146.40 3012765 85 3.94 0.246 176 2012 3.44
LA Dodgers National 1962 230.40 3764815 92 3.44 0.25 187 2013 3.65
Miami National 2012 84.60 1752235 71 4.02 0.26 120 2014 3.95
Milwaukee National 2001 98.70 2542558 68 4.28 0.251 145 2015 4.25
Minnesota American 2010 108.30 2220054 83 4.07 0.247 156 2016 4.4
NY Mets National 2009 100.10 2569753 90 3.43 0.244 177
NY Yankees American 2009 213.50 3193795 87 4.05 0.251 212
Oakland American 1966 80.80 1768175 68 4.14 0.251 146
Philadelphia National 2004 133.00 1831080 63 4.69 0.249 130
Pittsburgh National 2001 85.90 2498596 98 3.21 0.26 140
San Diego National 2004 126.60 2459742 74 4.09 0.243 148
San Francisco National 2000 166.50 3375882 84 3.72 0.267 136
Seattle American 1999 123.20 2193581 76 4.16 0.249 198
St. Louis National 2006 120.30 3520889 100 2.94 0.253 137
Tampa Bay American 1990 74.80 1287054 80 3.74 0.252 167
Texas American 1994 144.80 2491875 88 2.24 0.257 172
Toronto American 1989 116.40 2794891 93 3.8 0.269 232
Washington National 2008 174.50 2619843 83 3.62 0.251 177
Key
Team = Team’s name
League = American or National League
Year Opened = First year the team’s stadium was used
Team Salary = Total team salary expressed in millions of dollars
Attendance = Total number of people attending regular season games
Wins = Number of regular season games won
ERA = Team earned run average
BA = Team batting average
HR = Team home runs
Year = Year of operation
Average salary = Average annual player salary in dollars
ChartDataSheet_
This worksheet contains values required for MegaStat charts.
Boxplot 1/28/2010 16:03.39
2 741
2 806
3 806
3 827
1 827
3 827
3 851.5
2 851.5
2 908
2 851.5
1 851.5
1 806
2 806
1 669.5
3 669.5
1 737.75
3 737.75
1 919.75
3 919.75
1 988
3 988
Boxplot 1/28/2010 16:06.08
2 741
2 806
3 806
3 827
1 827
3 827
3 851.5
2 851.5
2 908
2 851.5
1 851.5
1 806
2 806
1 669.5
3 669.5
1 737.75
3 737.75
1 919.75
3 919.75
1 988
3 988
Dotplot 1/28/2010 16:06.08
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Boxplot 1/28/2010 16:08.20
2 741
2 806
3 806
3 827
1 827
3 827
3 851.5
2 851.5
2 895
2 851.5
1 851.5
1 806
2 806
1 669.5
3 669.5
1 737.75
3 737.75
1 919.75
3 919.75
1 988
3 988
1.8 980
1.8 1008
Dotplot 1/28/2010 16:08.20
741 1
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Bus
Data Set 3 --Lincolnville School District Bus Data
ID Manufacturer Engine Type (0=diesel) Capacity Maintenance Cost Age Odometer Miles Miles
10 Keiser 1 14 4646 5 54375 11973
396 Thompson 0 14 1072 2 21858 11969
122 Bluebird 1 55 9394 10 116580 11967
751 Keiser 0 14 1078 2 22444 11948
279 Bluebird 0 55 1008 2 22672 11925
500 Bluebird 1 55 5329 5 50765 11922 Variables
520 Bluebird 0 55 4794 10 119130 11896
759 Keiser 0 55 3952 8 87872 11889 ID = Bus identification numbe
714 Bluebird 0 42 3742 7 73703 11837
875 Bluebird 0 55 4376 9 97947 11814 Manufacturer = Source of the bus (Bluebird, Keiser, or Thompson)
600 Bluebird 0 55 4832 10 119860 11800
953 Bluebird 0 55 5160 10 117700 11798 Engine type = If the engine is diesel then engine type = 0; if the engine is gasoline, then engine type = 1)
101 Bluebird 0 55 1955 4 41096 11789
358 Bluebird 0 55 2775 6 70086 11782 Capacity = number of seats on the bus
29 Bluebird 1 55 5352 6 69438 11781
365 Keiser 0 55 3065 6 63384 11778 Maintenance cost = dollars spent to maintain a bus last yea
162 Keiser 1 55 3143 3 31266 11757
686 Bluebird 0 55 1569 3 34674 11707 Age = number of years since the bus left the manufacture
370 Keiser 1 55 7766 8 86528 11704
887 Bluebird 0 55 3743 8 93672 11698 Odometer Miles = total number of miles traveled by a bus
464 Bluebird 1 55 2540 3 34530 11698
948 Keiser 0 42 4342 9 97956 11691 Miles = number of miles traveled since last maintenance
678 Keiser 0 55 3361 7 75229 11668
481 Keiser 1 6 3097 3 34362 11662
43 Bluebird 1 55 8263 9 102969 11615
704 Bluebird 0 55 4218 8 83424 11610
814 Bluebird 0 55 2028 4 40824 11576
39 Bluebird 1 55 5821 6 69444 11533
699 Bluebird 1 55 9069 9 98307 11518
75 Bluebird 0 55 3011 6 71970 11462
693 Keiser 1 55 9193 9 101889 11461
989 Keiser 0 55 4795 9 106605 11418
982 Bluebird 0 55 505 1 10276 11359
321 Bluebird 0 42 2732 6 70122 11358
724 Keiser 0 42 3754 8 91968 11344
732 Keiser 0 42 4640 9 101196 11342
880 Keiser 1 55 8410 9 97065 11336
193 Thompson 0 14 5922 11 128711 11248
884 Bluebird 0 55 4364 9 92457 11231
57 Bluebird 0 55 3190 7 79240 11222
731 Bluebird 0 42 3213 6 68526 11168
61 Keiser 0 55 4139 9 103536 11148
135 Bluebird 0 55 3560 7 76426 11127
833 Thompson 0 14 3920 8 90968 11112
671 Thompson 1 14 6733 8 89792 11100
692 Bluebird 0 55 3770 8 93248 11048
200 Bluebird 0 55 5168 10 103700 11018
754 Keiser 0 14 7380 14 146860 11003
540 Bluebird 1 55 3656 4 45284 10945
660 Bluebird 1 55 6213 6 64434 10911
353 Keiser 1 55 4279 4 45744 10902
482 Bluebird 1 55 10575 10 116534 10802
398 Thompson 0 6 4752 9 95922 10802
984 Bluebird 0 55 3809 8 87664 10760
977 Bluebird 0 55 3769 7 79422 10759
705 Keiser 0 42 2152 4 47596 10755
767 Keiser 0 55 2985 6 71538 10726
326 Bluebird 0 55 4563 9 107343 10724
120 Keiser 0 42 4723 10 110320 10674
554 Bluebird 0 42 1826 4 44604 10662
695 Bluebird 0 55 1061 2 23152 10633
9 Keiser 1 55 3527 4 46848 10591
861 Bluebird 1 55 9669 10 106040 10551
603 Keiser 0 14 2116 4 44384 10518
156 Thompson 0 14 6212 12 140460 10473
427 Keiser 1 55 6927 7 73423 10355
883 Bluebird 1 55 1881 2 20742 10344
168 Thompson 1 14 7004 7 83006 10315
954 Bluebird 0 42 5284 10 101000 10235
768 Bluebird 0 42 3173 7 71778 10227
490 Bluebird 1 55 10133 10 106240 10210
725 Bluebird 0 55 2356 5 57065 10209
45 Keiser 0 55 3124 6 60102 10167
38 Keiser 1 14 5976 6 61662 10140
314 Thompson 0 6 5408 11 128117 10128
507 Bluebird 0 55 3690 7 72849 10095
40 Bluebird 1 55 9573 10 118470 10081
918 Bluebird 0 55 2470 5 53620 10075
387 Bluebird 1 55 6863 8 89960 10055
418 Bluebird 0 55 4513 9 104715 10000
Chapter 11 – Problem 14
The null and alternate hypotheses are:
H0: μ1 ≤ μ2
H1: μ1 > μ2
A random sample of 20 items from the first population showed a mean of 100 and a standard deviation of 15. A sample of 16 items for the second population showed a mean of 94 and a standard deviation of 8. Use the .05 significant level.
https:
www.slader.com/discussion/question/the-null-and-alternate-hypotheses-area-random-sample-of-20-items-from-the-first-population-showed-a
Chapter 11 – Problem 41
Operating Room
A B C D E F H H
Before 6.6 6.5 9 10.3 11.2 8.1 6.3 11.6
After 6.8 2.4 7.4 8.5 8.1 6.1 3.4 2
An investigation of the effectiveness of an antibacterial soap in reducing operating room contamination resulted in the accompanying table. The new soap was tested in a sample of eight operating rooms in the greater Seattle area during the last year. The following table reports the contamination levels before and after the use of the soap for each operating room.
At the .05 significance level, can we conclude the contamination measurements are lower after use of the new soap?
Chapter 11 – Problem 48
Refer to the Baseball 2016 data, which report information on the 30 Major League Baseball teams for the 2016 season.
a. At the .05 significance level, can we conclude that there is a difference in the mean salary of teams in the American League versus teams in the National League?
. At the .05 significance level, can we conclude that there is a difference in the mean home attendance of teams in the American League versus teams in the National League?
c. Compute the mean and the standard deviation of the number of wins for the 10Â teams with the highest salaries. Do the same for the 10 teams with the lowest salaries. At the .05 significance level, is there a difference in the mean number of wins for the two groups? At the .05 significance level, is there a difference in the mean attendance for the two groups?
Chapter 11 – Problem 49
Refer to the Lincolnville School District bus data. Is there a difference in the mean maintenance cost for the diesel versus the gasoline buses? Use the .05 significance level.
Chapter 12 Case A – Century Nat
A. Century National BankRefer to the description of Century National Bank on page 129 at the end of the Review of Chapters 1–4. With many other options available, customers no lon-ger let their money sit in a checking account. For many years the mean checking balance has been $1,600. Do the sample data indicate that the mean account balance has declined from this value? Recent years have also seen an increase in the use of ATM machines. When Mr. Selig took over the bank, the mean number of transactions per month per customer was 8; now he believes it has increased to more than 10. In fact, the advertising agency that prepares TV commercials for Century would like to use this on the new commercial being designed. Is there sufficient evidence to conclude that the mean number of transac-tions per customer is more than 10 per month? Could the advertising agency say the mean is more than 9 per month? The bank has
anch offices in four different cities: Cincinnati, Ohio; Atlanta, Georgia; Louisville, Kentucky; and Erie, Pennsylvania. Mr. Selig would like to know whether there is a difference in the mean checking ac-count balances among the four
anches. If there are differences, between which
anches do these differences occur? Mr. Selig is also interested in the bank’s ATMs. Is there a difference in ATM use among the
anches? Also, do customers who have debit cards tend to use ATMs differently from those who do not have debit cards? Is there a difference in ATM use by those with checking accounts that pay interest versus those that do not? Prepare a report for Mr. Selig answering these questions.