By A. Agresti and B. Finlay, Prentice Hall, 1997
This file contains many of the larger data sets from the third edition
of Statistical Methods for the Social Sciences. It also
contains a data set based on a student questionnaire administered in
STA 6126 at the University of Florida in August, 1996.
Survey Data:
The first data file consists of responses of graduate students in the
social sciences enrolled in STA 6126 at the University of Florida,
fall term 1996. The headings at the top of this file refer to the
variables, GE = gender, AG = age in years, HI = high
school GPA (on a four-point scale), CO = college GPA, DH =
distance (in miles) of the campus from your home town, DR =
distance (in miles) of the classroom from your current residence, TV = average number of hours per week that you watch TV, SP =
average number of hours per week that you participate in sports or
have other physical exercise,NE = number of times a week you
read a newspaper, AH = number of people you know who have died
from AIDS or who are HIV+, VE = whether you are a vegetarian
(yes, no), PA = political affiliation (D = Democrat, R =
Republican, I = independent), PI = political ideology (1 =
very liberal, 2 = liberal, 3 = slightly liberal, 4 = moderate, 5
= slightly conservative, 6 = conservative, 7 = very conservative),
RE = how often you attend religious services (never,
occasionally, most weeks, every week), AB = opinion about
whether abortion should be legal in the first three months of
pregnancy (yes, no), AA = support affirmative action (yes, no),
LD = belief in life after death (yes, no),
subj ge ag hi co dh dr tv sp ne ah ve pa pi re ab aa ld 1 m 32 2.2 3.5 0 5.0 3 5 0 0 n r 6 2 n n y 2 f 23 2.1 3.5 1200 0.3 15 7 5 6 y d 2 1 y y u 3 f 27 3.3 3.0 1300 1.5 0 4 3 0 y d 2 2 y y u 4 f 35 3.5 3.2 1500 8 5 5 6 3 n i 4 1 y y n 5 m 23 3.1 3.5 1600 10 6 6 3 0 n i 1 0 y n n 6 m 39 3.5 3.5 350 3 4 5 7 0 y d 2 1 y y u 7 m 24 3.6 3.7 0 .2 5 12 4 2 n i 2 1 y y y 8 f 31 3.0 3.0 5000 1.5 5 3 3 1 n i 2 1 y y y 9 m 34 3.0 3.0 5000 2 7 5 3 0 n i 1 1 y y u 10 m 28 4.0 3.1 900 2 1 1 2 1 y i 3 0 n y y 11 m 23 2.3 2.6 253 1.5 10 15 1 1 n r 5 1 n y y 12 f 27 3.5 3.6 190 3 14 3 7 0 n d 2 1 y y u 13 m 36 3.3 3.5 245 1.5 6 15 12 5 n d 1 1 y y y 14 m 28 3.2 3.2 500 6 3 10 1 2 n i 4 1 y n y 15 f 28 3.0 3.5 3500 1 4 3 1 0 n d 1 0 y y y 16 f 25 3.8 3.3 210 10 7 6 1 0 y i 2 3 y y y 17 f 41 4.0 3.0 1000 15 6 7 3 10 n i 3 3 n u y 18 m 50 3.8 3.8 0 3 5 9 6 10 n d 2 0 y n n 19 m 71 4.0 3.5 5000 3 6 12 2 2 n i 2 0 y n n 20 f 28 3.0 3.8 120 1 25 0 0 2 y d 1 1 y y y 21 f 26 3.7 3.7 8000 8 4 4 4 1 n i 4 1 y y y 22 f 27 4.0 3.7 2 2.5 4 2 7 0 n i 2 1 y y y 23 m 31 2.7 3.5 1700 5 7 7 2 0 n r 7 3 n n y 24 f 23 3.7 3.7 2 2 7 4 2 0 n i 4 0 y y y 25 m 23 3.2 3.8 450 4 0 7 7 3 n i 1 0 y y y 26 f 44 3.0 3.0 0 2 2 3 2 3 y i 3 2 y y y 27 m 26 3.7 3.0 1000 3 8 2 7 0 n d 2 1 y y u 28 f 31 3.7 3.8 850 10 10 3 7 0 n r 5 2 y n y 29 m 24 3.3 3.1 420 2 10 6 5 0 n d 4 1 y y u 30 f 26 3.3 3.3 1200 .75 10 0 3 0 n r 2 1 y y u 31 m 26 3.3 3.5 1000 1.5 0 3 3 3 y d 2 1 y y n 32 f 32 3.5 3.9 150 12 10 2 0 0 n d 2 1 n n y 33 m 26 3.4 3.4 2000 1.5 2 7 14 0 n d 2 0 y y n 34 f 22 3.2 2.8 316 2 10 3 5 2 n i 2 1 y y u 35 f 24 3.5 3.9 900 1.75 8 0 0 1 n d 1 1 y y u 36 m 24 3.6 3.3 250 2 4 6 3 1 n r 5 3 n y y 37 m 23 3.8 3.7 180 .5 10 5 7 0 n i 2 0 y n u 38 m 33 3.4 3.4 6000 1.5 8 5 6 2 n i 2 0 y y n 39 m 23 2.8 3.2 950 2 37 10 5 0 n r 5 2 y n y 40 m 31 3.8 3.5 1100 .75 .5 3 5 2 n r 6 2 y n u 41 m 26 3.4 3.4 1300 1.2 0 8 2 0 n i 2 1 n y n 42 m 28 2.0 3.0 360 .25 10 8 3 0 n d 3 0 y y u 43 f 24 3.8 3.9 1800 2 2 5 4 1 n r 6 3 n y y 44 m 23 3.0 3.6 900 15 12 0 5 0 n r 5 0 y n n 45 f 25 3.0 4.0 5000 5 1.5 0 4 0 n i 4 1 y y n 46 f 24 3.0 3.5 300 1 10 5 5 0 n d 2 0 y y n 47 f 27 3.0 3.8 2000 20 28 7 14 2 y r 3 1 y y y 48 m 24 3.3 3.8 630 1.3 2 3 5 0 n r 7 3 n n y 49 f 26 3.8 4.0 1200 1 0 4 3 1 n d 2 0 y y n 50 f 27 3.0 4.0 580 2 5 15 1 2 n d 1 1 y y n 51 m 32 3.0 3.0 2000 5 5 5 2 1 n r 5 3 n y y 52 f 41 4.0 4.0 0 8 8 4 2 2 n r 4 1 n n y 53 f 29 3.0 3.9 300 3.7 2 5 1 11 n d 2 1 y y y 54 f 50 3.5 3.8 6 6 7 3 7 0 n d 2 1 y y u 55 f 22 3.4 3.7 80 7 10 1 2 2 n i 2 0 y y u 56 f 23 3.6 3.2 375 1.5 5 10 5 0 n r 6 3 n n y 57 m 26 3.5 3.6 2000 .3 16 8 3 0 n d 4 1 y y u 58 m 30 3.0 3.0 1 1.1 1 4 3 0 n i 3 3 y n y 59 f 23 3.0 3.0 112 .5 15 3 3 0 n i 4 2 y y y 60 f 22 3.4 3.0 650 4 8 16 7 1 n i 4 1 y y y
Tables 3.1 and 9.1:
The variables for this data set are described at the beginning of Chapter 9. In the following table, VR = violent crime rate, MR = murder rate, M = percent in metropolitan areas, W = percent white, H = percent high school graduates, P = percent below the poverty level, S = percent of families headed by a single parent. The data are from Statistical Abstract of the United States.
State VR MR M W H P S AK 761 9.0 41.8 75.2 86.6 9.1 14.3 AL 780 11.6 67.4 73.5 66.9 17.4 11.5 AR 593 10.2 44.7 82.9 66.3 20.0 10.7 AZ 715 8.6 84.7 88.6 78.7 15.4 12.1 CA 1078 13.1 96.7 79.3 76.2 18.2 12.5 CO 567 5.8 81.8 92.5 84.4 9.9 12.1 CT 456 6.3 95.7 89.0 79.2 8.5 10.1 DE 686 5.0 82.7 79.4 77.5 10.2 11.4 FL 1206 8.9 93.0 83.5 74.4 17.8 10.6 GA 723 11.4 67.7 70.8 70.9 13.5 13.0 HI 261 3.8 74.7 40.9 80.1 8.0 9.1 IA 326 2.3 43.8 96.6 80.1 10.3 9.0 ID 282 2.9 30.0 96.7 79.7 13.1 9.5 IL 960 11.4 84.0 81.0 76.2 13.6 11.5 IN 489 7.5 71.6 90.6 75.6 12.2 10.8 KS 496 6.4 54.6 90.9 81.3 13.1 9.9 KY 463 6.6 48.5 91.8 64.6 20.4 10.6 LA 1062 20.3 75.0 66.7 68.3 26.4 14.9 MA 805 3.9 96.2 91.1 80.0 10.7 10.9 MD 998 12.7 92.8 68.9 78.4 9.7 12.0 ME 126 1.6 35.7 98.5 78.8 10.7 10.6 MI 792 9.8 82.7 83.1 76.8 15.4 13.0 MN 327 3.4 69.3 94.0 82.4 11.6 9.9 MO 744 11.3 68.3 87.6 73.9 16.1 10.9 MS 434 13.5 30.7 63.3 64.3 24.7 14.7 MT 178 3.0 24.0 92.6 81.0 14.9 10.8 NC 679 11.3 66.3 75.2 70.0 14.4 11.1 ND 82 1.7 41.6 94.2 76.7 11.2 8.4 NE 339 3.9 50.6 94.3 81.8 10.3 9.4 NH 138 2.0 59.4 98.0 82.2 9.9 9.2 NJ 627 5.3 100.0 80.8 76.7 10.9 9.6 NM 930 8.0 56.0 87.1 75.1 17.4 13.8 NV 875 10.4 84.8 86.7 78.8 9.8 12.4 NY 1074 13.3 91.7 77.2 74.8 16.4 12.7 OH 504 6.0 81.3 87.5 75.7 13.0 11.4 OK 635 8.4 60.1 82.5 74.6 19.9 11.1 OR 503 4.6 70.0 93.2 81.5 11.8 11.3 PA 418 6.8 84.8 88.7 74.7 13.2 9.6 RI 402 3.9 93.6 92.6 72.0 11.2 10.8 SC 1023 10.3 69.8 68.6 68.3 18.7 12.3 SD 208 3.4 32.6 90.2 77.1 14.2 9.4 TN 766 10.2 67.7 82.8 67.1 19.6 11.2 TX 762 11.9 83.9 85.1 72.1 17.4 11.8 UT 301 3.1 77.5 94.8 85.1 10.7 10.0 VA 372 8.3 77.5 77.1 75.2 9.7 10.3 VT 114 3.6 27.0 98.4 80.8 10.0 11.0 WA 515 5.2 83.0 89.4 83.8 12.1 11.7 WI 264 4.4 68.1 92.1 78.6 12.6 10.4 WV 208 6.9 41.8 96.3 66.0 22.2 9.4 WY 286 3.4 29.7 95.9 83.0 13.3 10.8 DC 2922 78.5 100.0 31.8 73.1 26.4 22.1
Table 9.4:
Selling price of homes in Gainesville, Florida, January 1996. The following table contains data on P = selling price, S = size of home, BE = number of bedrooms, BA = number of bathrooms, New = whether new (1 = yes, 0 = no). Data provided by Jane Myers, Coldwell-Banker Realty.
P S Be Ba New 48.5 1.10 3 1 0 55.0 1.01 3 2 0 68.0 1.45 3 2 0 137.0 2.40 3 3 0 309.4 3.30 4 3 1 17.5 .40 1 1 0 19.6 1.28 3 1 0 24.5 .74 3 1 0 34.8 .78 2 1 0 32.0 .97 3 1 0 28.0 .84 3 1 0 49.9 1.08 2 2 0 59.9 .99 2 1 0 61.5 1.01 3 2 0 60.0 1.34 3 2 0 65.9 1.22 3 1 0 67.9 1.28 3 2 0 68.9 1.29 3 2 0 69.9 1.52 3 2 0 70.5 1.25 3 2 0 72.9 1.28 3 2 0 72.5 1.28 3 1 0 72.0 1.36 3 2 0 71.0 1.20 3 2 0 76.0 1.46 3 2 0 72.9 1.56 4 2 0 73.0 1.22 3 2 0 70.0 1.40 2 2 0 76.0 1.15 2 2 0 69.0 1.74 3 2 0 75.5 1.62 3 2 0 76.0 1.66 3 2 0 81.8 1.33 3 2 0 84.5 1.34 3 2 0 83.5 1.40 3 2 0 86.0 1.15 2 2 1 86.9 1.58 3 2 1 86.9 1.58 3 2 1 86.9 1.58 3 2 1 87.9 1.71 3 2 0 88.1 2.10 3 2 0 85.9 1.27 3 2 0 89.5 1.34 3 2 0 87.4 1.25 3 2 0 87.9 1.68 3 2 0 88.0 1.55 3 2 0 90.0 1.55 3 2 0 96.0 1.36 3 2 1 99.9 1.51 3 2 1 95.5 1.54 3 2 1 98.5 1.51 3 2 0 100.1 1.85 3 2 0 99.9 1.62 4 2 1 101.9 1.40 3 2 1 101.9 1.92 4 2 0 102.3 1.42 3 2 1 110.8 1.56 3 2 1 105.0 1.43 3 2 1 97.9 2.00 3 2 0 106.3 1.45 3 2 1 106.5 1.65 3 2 0 116.0 1.72 4 2 1 108.0 1.79 4 2 1 107.5 1.85 3 2 0 109.9 2.06 4 2 1 110.0 1.76 4 2 0 120.0 1.62 3 2 1 115.0 1.80 4 2 1 113.4 1.98 3 2 0 114.9 1.57 3 2 0 115.0 2.19 3 2 0 115.0 2.07 4 2 0 117.9 1.99 4 2 0 110.0 1.55 3 2 0 115.0 1.67 3 2 0 124.0 2.40 4 2 0 129.9 1.79 4 2 1 124.0 1.89 3 2 0 128.0 1.88 3 2 1 132.4 2.00 4 2 1 139.3 2.05 4 2 1 139.3 2.00 4 2 1 139.7 2.03 3 2 1 142.0 2.12 3 3 0 141.3 2.08 4 2 1 147.5 2.19 4 2 0 142.5 2.40 4 2 0 148.0 2.40 5 2 0 149.0 3.05 4 2 0 150.0 2.04 3 3 0 172.9 2.25 4 2 1 190.0 2.57 4 3 1 280.0 3.85 4 3 0
Table 9.13:
Birth rates in several countries. This table lists recent
values for several nations on B = crude birth rate (number of births
per 1000 population size), W = women's economic activity (female labor
force as percent of male), C = percent women using contraception, LI =
female adult literacy rate, LE = female life expectancy, HDI = human
development index (which has components referring to life expectancy
at birth, educational attainment, and income per capita), GNP = gross
national product (per capita, in thousands of dollars), N = daily
newspaper circulation per 100 people, and TV = number of televisions
per 100 people.
Sources: Statistical Abstract of the
United States, 1995
and Human Development Report, 1995, Oxford University Press.
Nation B W C LI LE HDI GNP N TV Algeria 29.0 11 47 73 68 44 1.6 5 7 Argentina 19.5 38 -- 88 76 96 4.0 12 22 Australia 14.1 61 76 93 81 99 16.6 25 48 Brazil 21.2 38 66 80 69 81 2.6 5 21 Canada 13.7 63 -- 95 81 99 20.8 23 64 China 17.8 81 83 59 70 70 1.3 5 3 Cuba 14.5 50 70 77 77 94 1.6 17 16 Denmark 12.4 77 78 92 78 99 24.2 35 54 Egypt 28.7 12 46 61 65 36 .5 6 12 France 13.0 64 81 93 81 99 24.1 21 41 Germany 11.0 -- 75 92 79 99 19.8 59 56 India 27.8 34 43 44 60 35 .3 3 4 Iraq 43.6 29 14 62 67 41 .7 4 7 Israel 20.4 49 -- 91 78 95 13.6 26 27 Japan 10.7 64 64 94 82 99 27.3 59 61 Malaysia 28.0 55 48 75 73 82 2.5 14 15 Mexico 26.6 37 53 84 74 86 3.1 13 15 Nigeria 43.3 51 6 41 52 42 .2 -- -- Pakistan 41.8 16 12 48 63 63 .4 2 2 Philippines 30.4 44 40 68 68 94 .7 5 4 Russia 12.6 70 -- 85 74 99 8.6 -- -- South Africa 33.4 54 50 -- 66 70 2.6 4 10 Spain 11.2 31 -- 98 80 93 13.4 8 40 United Kingdom 13.2 60 81 92 79 99 17.4 39 43 United States 15.2 65 74 94 79 99 22.6 25 81 Vietnam 26.3 82 53 89 67 54 -- -- --
Table 9.16:
Data for Florida counties. The variables are county, C =
crime rate, I = median income, HS = percent completing high school, U
= percent urban.
Source: Dr. Larry Winner, University of
Florida.
County C I HS U ALACHUA 104 22.1 82.7 73.2 BAKER 20 25.8 64.1 21.5 BAY 64 24.7 74.7 85.0 BRADFORD 50 24.6 65.0 23.2 BREVARD 64 30.5 82.3 91.9 BROWARD 94 30.6 76.8 98.9 CALHOUN 8 18.6 55.9 0.0 CHARLOTTE 35 25.7 75.7 80.2 CITRUS 27 21.3 68.6 31.0 CLAY 41 34.9 81.2 65.8 COLLIER 55 34.0 79.0 77.6 COLUMBIA 69 22.0 69.0 31.1 DADE 128 26.9 65.0 98.8 DESOTO 69 21.0 54.5 44.6 DIXIE 49 15.4 57.7 0.0 DUVAL 97 28.5 76.9 98.8 ESCAMBIA 70 25.2 76.2 85.9 FLAGLER 34 28.6 78.7 63.1 FRANKLIN 37 17.2 59.5 30.2 GADSDEN 52 20.0 59.9 28.8 GILCHRIST 15 20.6 63.0 0.0 GLADES 62 20.7 57.4 0.0 GULF 19 21.9 66.4 35.2 HAMILTON 6 18.7 58.4 0.0 HARDEE 57 22.1 54.8 16.7 HENDRY 47 24.9 56.6 44.7 HERNANDO 44 22.7 70.5 61.3 HIGHLANDS 56 21.1 68.2 24.8 HILLSBOR. 110 28.5 75.6 89.2 HOLMES 5 17.2 57.1 16.8 INDIAN R. 58 29.0 76.5 83.0 JACKSON 32 19.5 61.6 21.7 JEFFERSON 36 21.8 64.1 22.3 LAFAYETTE 0 20.7 58.2 0.0 LAKE 42 23.4 70.6 43.2 LEE 59 28.4 76.9 86.1 LEON 107 27.3 84.9 82.5 LEVY 45 18.8 62.8 0.0 LIBERTY 8 22.3 56.7 0.0 MADISON 26 18.2 56.5 20.3 MANATEE 79 26.0 75.6 88.7 MARION 64 22.5 69.6 39.6 MARTIN 53 31.8 79.7 83.2 MONROE 89 29.4 79.7 73.2 NASSAU 42 30.2 71.2 44.9 OKALOOSA 37 27.9 83.8 84.0 OKEECH. 51 21.4 59.1 30.1 ORANGE 93 30.3 78.8 93.1 OSCEOLA 78 27.3 73.7 66.4 PALM B. 90 32.5 78.8 94.7 PASCO 42 21.5 66.9 67.4 PINELLAS 70 26.3 78.1 99.6 POLK 84 25.2 68.0 70.3 PUTNAM 83 20.2 64.3 15.7 SANTA R. 43 27.6 79.9 57.2 SARASOTA 58 29.9 71.7 92.1 SEMINOLE 56 35.6 78.5 44.4 ST JOHNS 54 29.9 81.3 93.2 ST LUCIE 58 27.7 84.6 92.8 SUMTER 37 19.6 64.3 19.3 SUWANEE 37 19.8 63.8 23.6 TAYLOR 76 21.4 62.1 41.8 UNION 6 22.8 67.7 0.0 VOLUSIA 62 24.8 75.4 83.9 WAKULLA 29 25.0 71.6 0.0 WALTON 18 21.9 66.5 20.9 WASHING. 21 18.3 60.9 22.9
Table 11.1:
This table refers to Y = mental impairment, X1 = life
events, and X2 = SES, for a sample from Alachua County, Florida.
(Source: Dr. Charles Holzer)
Y X1 X2 17 46 84 19 39 97 20 27 24 20 3 85 20 10 15 21 44 55 21 37 78 22 35 91 22 78 60 23 32 74 24 33 67 24 18 39 25 81 87 26 22 95 26 50 40 26 48 52 26 45 61 27 21 45 27 55 88 27 45 56 27 60 70 28 97 89 28 37 50 28 30 90 28 13 56 28 40 56 29 5 40 30 59 72 30 44 53 31 35 38 31 95 29 31 63 53 31 42 7 32 38 32 33 45 55 34 70 58 34 57 16 34 40 29 41 49 3 41 89 75
Table 12.19:
Weights of Anorexic girls, before and after receiving one
of three possible therapies - cognitive behavioural, family therapy,
or control. (Thanks to Prof. Brian Everitt, Institute of Psychiatry,
London, for supplying these data.)
subj therapy before after 1 b 80.5 82.2 2 b 84.9 85.6 3 b 81.5 81.4 4 b 82.6 81.9 5 b 79.9 76.4 6 b 88.7 103.6 7 b 94.9 98.4 8 b 76.3 93.4 9 b 81.0 73.4 10 b 80.5 82.1 11 b 85.0 96.7 12 b 89.2 95.3 13 b 81.3 82.4 14 b 76.5 72.5 15 b 70.0 90.9 16 b 80.4 71.3 17 b 83.3 85.4 18 b 83.0 81.6 19 b 87.7 89.1 20 b 84.2 83.9 21 b 86.4 82.7 22 b 76.5 75.7 23 b 80.2 82.6 24 b 87.8 100.4 25 b 83.3 85.2 26 b 79.7 83.6 27 b 84.5 84.6 28 b 80.8 96.2 29 b 87.4 86.7 30 f 83.8 95.2 31 f 83.3 94.3 32 f 86.0 91.5 33 f 82.5 91.9 34 f 86.7 100.3 35 f 79.6 76.7 36 f 76.9 76.8 37 f 94.2 101.6 38 f 73.4 94.9 39 f 80.5 75.2 40 f 81.6 77.8 41 f 82.1 95.5 42 f 77.6 90.7 43 f 83.5 92.5 44 f 89.9 93.8 45 f 86.0 91.7 46 f 87.3 98.0 47 c 80.7 80.2 48 c 89.4 80.1 49 c 91.8 86.4 50 c 74.0 86.3 51 c 78.1 76.1 52 c 88.3 78.1 53 c 87.3 75.1 54 c 75.1 86.7 55 c 80.6 73.5 56 c 78.4 84.6 57 c 77.6 77.4 58 c 88.7 79.5 59 c 81.3 89.6 60 c 78.1 81.4 61 c 70.5 81.8 62 c 77.3 77.3 63 c 85.2 84.2 64 c 86.0 75.4 65 c 84.1 79.5 66 c 79.7 73.0 67 c 85.5 88.3 68 c 84.4 84.7 69 c 79.6 81.4 70 c 77.5 81.2 71 c 72.3 88.2 72 c 89.0 78.8
Table 13.1:
This table contains data on annual income (thousands
of dollars), number of years of education (where 12 = high
school graduate, 16 = college graduate), and Z = racial-ethnic
group (Black, Hispanic, White), first expressed as a letter and
then with dummy variables for black and Hispanic.
inc educ race z1 z2 8 10 b 1 0 9 7 b 1 0 13 9 b 1 0 8 11 b 1 0 17 14 b 1 0 11 12 b 1 0 21 16 b 1 0 21 16 b 1 0 8 9 b 1 0 10 10 b 1 0 33 16 b 1 0 13 12 b 1 0 10 10 b 1 0 15 15 b 1 0 10 10 b 1 0 15 19 b 1 0 16 16 h 0 1 8 11 h 0 1 10 10 h 0 1 29 16 h 0 1 15 12 h 0 1 13 10 h 0 1 10 8 h 0 1 20 12 h 0 1 16 10 h 0 1 11 11 h 0 1 10 10 h 0 1 28 14 h 0 1 16 12 h 0 1 15 11 h 0 1 15 14 w 0 0 24 14 w 0 0 20 7 w 0 0 42 18 w 0 0 25 10 w 0 0 19 12 w 0 0 15 12 w 0 0 38 16 w 0 0 24 16 w 0 0 18 11 w 0 0 20 11 w 0 0 22 12 w 0 0 15 10 w 0 0 30 15 w 0 0 12 9 w 0 0 44 17 w 0 0 23 16 w 0 0 25 16 w 0 0 25 14 w 0 0 11 11 w 0 0 13 12 w 0 0 23 16 w 0 0 11 9 w 0 0 12 9 w 0 0 32 14 w 0 0 31 16 w 0 0 12 10 w 0 0 25 13 w 0 0 16 10 w 0 0 17 16 w 0 0 26 18 w 0 0 12 12 w 0 0 11 14 w 0 0 10 13 w 0 0 15 14 w 0 0 12 13 w 0 0 60 18 w 0 0 11 10 w 0 0 41 16 w 0 0 9 12 w 0 0 13 12 w 0 0 52 14 w 0 0 14 12 w 0 0 16 12 w 0 0 19 14 w 0 0 22 12 w 0 0 11 12 w 0 0 9 10 w 0 0 12 12 w 0 0 28 20 w 0 0
Table 15.1:
Data on annual income (millions of Italian lira), number
of subjects at that income level, and number possessing
a travel credit card.
Source: ``Categorical Data Analysis,''
Quaderni del Corso Estivo
di Statistica e Calcolo delle Probabilita;, n. 4., Istituto di
Metodi Quantitativi, Universita; Luigi Bocconi, a cura di
R. Piccarreta (1993).
Income n no. yes 24 1 0 27 1 0 28 5 2 29 3 0 30 9 1 31 5 1 32 8 0 33 1 0 34 7 1 35 1 1 38 3 1 39 2 0 40 5 0 41 2 0 42 2 0 45 1 1 48 1 0 49 1 0 50 10 2 52 1 0 59 1 0 60 5 2 65 6 6 68 3 3 70 5 3 79 1 0 80 1 0 84 1 0 94 1 0 120 6 6 130 1 1
Table 15.19:
Results of accidents in Maine, 1991. The table
classifies subjects by gender, location of accident, seat-belt use,
and a response variable having categories (1) not injured, (2) injured
but not transported by emergency medical services, (3) injured and
transported by emergency medical services but not hospitalized, (4)
injured and hospitalized but did not die, (5) injured and died.
Source: Dr. Cristanna Cook, Medical Care Development,
Augusta, Maine.
Gender Location Seat-Belt 1 2 3 4 5
Female Urban No 7287 175 720 91 10
Yes 11587 126 577 48 8
Rural No 3246 73 710 159 31
Yes 6134 94 564 82 17
Male Urban No 10381 136 566 96 14
Yes 10969 83 259 37 1
Rural No 6123 141 710 188 45
Yes 6693 74 353 74 12