By A. Agresti and B. Finlay, Prentice Hall, 4th edition, 2008
This file contains most of the larger data sets from the fourth
edition of Statistical Methods for the Social Sciences. Many
of these data files are also available in
comma-separated text files
(.csv) csv
data files, thanks to Andrew C. Thomas at Harvard
University.
"Student Survey" Data File:
This data file consists of
responses of graduate students in the social sciences enrolled in STA
6126 in a recent term at the University of Florida. 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 (0 = never,
1 = occasionally, 2 = most weeks, 3 = 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
"2005 Statewide Crime" Data File:
The variables for this data set are VI = violent crime rate (number of violent crimes per 100,000 population), VI2 = violent crime rate (number of violent crimes per 10,000 population), MU = murder rate, ME = percent in metropolitan areas, WH = percent white, HS = percent high school graduates, PO = percent below the poverty level. The data are from Statistical Abstract of the United States.
STATE VI VI2 MU ME WH HS PO AK 593 59 6 65.6 70.8 90.2 8.0 AL 430 43 7 55.4 71.4 82.4 13.7 AR 456 46 6 52.5 81.3 79.2 12.1 AZ 513 51 8 88.2 87.6 84.4 11.9 CA 579 58 7 94.4 77.2 81.3 10.5 CO 345 34 4 84.5 90.3 88.3 7.3 CT 308 31 3 87.7 85.1 88.8 6.4 DE 658 66 3 80.1 75.3 86.5 5.8 FL 730 73 5 89.3 80.6 85.9 9.7 GA 454 45 8 71.6 66.4 85.2 10.8 HI 270 27 2 91.5 26.5 88.0 7.4 ID 243 24 2 66.4 95.5 87.9 9.8 IL 557 56 7 87.8 79.4 86.8 8.5 IN 353 35 6 70.8 88.7 87.2 7.5 IO 272 27 2 61.1 95.0 89.8 6.9 KS 396 40 5 71.4 89.4 89.6 7.1 KY 262 26 5 55.8 90.4 81.8 14.2 LA 646 65 13 72.6 64.1 78.7 16.6 MA 469 47 2 91.4 87.0 86.9 7.5 MD 704 70 10 86.1 64.5 87.4 6.1 ME 109 11 1 40.2 97.0 87.1 7.6 MI 511 51 6 74.7 81.4 87.9 8.6 MN 263 26 3 70.9 89.8 92.3 5.6 MO 473 47 5 69.4 85.4 87.9 8.6 MS 326 33 9 48.8 61.3 83.0 16.4 MT 365 36 3 54.1 91.0 91.9 9.9 NC 455 46 6 60.2 74.1 80.9 10.7 ND 78 8 2 55.9 92.4 89.5 8.4 NE 289 29 3 69.8 92.1 91.3 8.2 NH 149 15 1 59.3 96.2 90.8 5.1 NJ 366 37 5 94.4 76.9 87.6 6.6 NM 665 66 6 75.0 84.7 82.9 14.8 NV 614 61 9 91.5 82.5 86.3 8.7 NY 465 46 5 87.5 73.9 85.4 10.7 OH 333 33 5 77.4 85.2 88.1 9.4 OK 506 51 6 65.3 78.6 85.2 12.4 OR 296 30 2 78.7 90.9 87.4 9.7 PA 398 40 5 77.1 86.2 86.5 8.2 RI 286 29 2 90.9 89.0 81.1 8.2 SC 794 79 7 60.5 68.3 83.6 11.3 SD 173 17 1 51.9 88.7 87.5 7.2 TN 688 69 7 63.6 80.7 82.9 10.6 TX 553 55 6 82.5 83.3 78.3 13.1 UT 249 25 3 88.2 93.8 91.0 7.6 VA 276 28 6 73.0 73.8 88.4 6.6 VT 110 11 2 38.2 96.9 90.8 6.4 WA 347 35 3 82.0 85.3 89.7 7.9 WI 221 22 3 68.3 90.2 88.8 7.2 WV 258 26 4 46.1 95.2 80.9 15.5 WY 262 26 3 65.1 94.7 91.9 7.3 DC 1608 161 44 100.0 37.4 86.4 18.5
"Statewide Crime 2" Data File (Table 9.1):
These data are in Table 9.1 of the 3rd edition, and some of them appear in Table 9.1 of the 4th edition. In the following table, VR = violent crime rate (per 100,000 people in population), MR = murder rate (per 100,000 people in population), M = percent in metropolitan areas, W = percent white, H = percent high school graduates, P = percent with income below the poverty level, S = percent of families headed by a single parent. The data are from Statistical Abstract of the United States and most variables were measured in 1993.
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
"OECD Data" File (Table 3.11), see Exercise 3.6:
nation GDP Unemploy Inequal Health Phys C02 Parlia FemEcon Norway 38454 4.6 6.1 8.6 313 9.9 37.9 87 Iceland 33051 2.5 I 8.8 362 7.6 33.3 87 Australia 30331 5.1 12.5 6.4 247 18 28.3 79 Ireland 38827 4.3 9.4 5.8 279 10.3 14.2 72 Sweden 29541 5.6 6.2 8 328 5.9 45.3 87 Canada 31263 6.8 9.4 6.9 214 17.9 24.3 83 Japan 29251 4.4 4.5 6.4 198 9.7 10.7 65 United States 39676 5.1 15.9 6.8 256 19.8 15 81 Switzerland 33040 4.1 9 6.7 361 5.6 24.8 79 Netherlands 31789 6.2 9.2 6.1 315 8.7 34.2 76 Finland 29951 8.6 5.6 5.7 316 13 37.5 86 Luxembourg 69961 4.6 I 6.2 266 22 23.3 68 Belgium 31096 8.4 8.2 6.3 449 8.3 35.7 72 Austria 32276 5.8 6.9 5.1 338 8.6 32.2 75 Denmark 31914 4.9 8.1 7.5 293 10.1 36.9 84 France 29300 10.0 9.1 7.7 337 6.2 13.9 79 Italy 28180 7.7 11.6 6.3 420 7.7 16.1 61 United Kingdom 30821 4.8 13.8 6.9 230 9.4 18.5 79 Spain 25047 9.1 10.3 5.5 330 7.3 30.5 65 New Zealand 23413 3.6 12.5 6.3 237 8.8 32.2 81 Germany 28303 9.3 6.9 8.7 337 9.8 30.5 76 Greece 22205 10.6 10.2 5.1 438 8.7 13 66 Portugal 19629 7.5 15 6.7 342 5.6 21.3 79
"Zagat restaurant rating of Italian restaurants" Data File (See Exercises 3.59, 3.60, and 9.38):
City Restaurant Food Decor Service Cost Boston Al_Dente 21 14 21 30 Boston Anchovies 18 14 18 20 Boston Antico_Forno 22 16 18 28 Boston Antonio's_Cucina_Italian 22 14 21 24 Boston Armani 19 20 17 39 Boston Artu 22 15 19 27 Boston Assagio 23 21 22 31 Boston Bacco 21 20 20 35 Boston Bertucci's 17 14 16 19 Boston Bricco 23 22 21 45 Boston Caliterra 19 20 21 35 Boston Canestero's 21 14 19 18 Boston Cantina_Italiana 23 16 22 30 Boston Carmen 27 22 22 39 Boston Ciao_Bella 17 16 17 34 Boston Cibo 23 15 21 26 Boston Daily_Catch 24 10 18 27 Boston Davide 22 18 21 44 Boston Davio's 23 23 22 48 Boston Dom's 25 17 23 35 Boston Euno 21 24 22 36 Boston Figs 22 17 18 26 Boston Filippo 20 19 23 33 Boston Five_North_Square 20 17 19 35 Boston Florentine_Cafe 19 21 18 33 Boston Galleria_Umberto 26 7 16 9 Boston Giacomo's 25 16 20 28 Boston Grotto 25 18 22 37 Boston Il_Panino 20 11 15 14 Boston Joe_Tecce's 17 15 17 30 Boston L'Osteria 22 15 19 28 Boston La_Famiglia_Giorgio 18 12 18 22 Boston La_Summa 22 17 21 31 Boston Limoncello 21 18 20 35 Boston Lucca 24 23 23 42 Boston Maggiano's 19 18 19 30 Boston Mamma_Maria 25 23 23 49 Boston Massimino's 23 16 21 27 Boston Maurizio's 24 15 21 36 Boston Monica's 24 19 22 33 Boston Mother_Anna's 21 13 19 27 Boston No_9_Park 27 24 26 61 Boston Pagliuca's 22 14 20 27 Boston Papa_Razzi 18 17 18 28 Boston Piattini 23 19 20 31 Boston Piccolo_Venezia 21 18 18 25 Boston Piccolo_Nido 20 16 22 33 Boston Pomodoro 24 12 17 30 Boston Prezza 26 23 24 49 Boston Ristorante_Fiore 21 21 19 38 Boston Ristorante_Lucia 21 17 20 32 Boston Ristorante_Toscano 20 17 19 40 Boston Ristorante_Villa_Francesca 20 18 20 36 Boston Saraceno 22 21 22 37 Boston Scoozi 17 11 15 20 Boston Sorento's 21 17 16 24 Boston Strega_Ristorante 23 20 22 36 Boston Taranta 24 21 23 37 Boston Teatro 24 21 21 40 Boston Terramia_Ristorante 25 18 21 42 Boston Trattoria_di_Monica's 24 19 22 33 Boston Trattoria_Il_Panino 23 17 20 32 Boston Umbria 24 23 23 45 Boston Via_Matta 23 22 22 50 London Al_Duca 18 15 18 80 London Alloro 22 17 20 94 London Aperitivo 17 13 16 60 London Ark 21 21 20 86 London Bertorelli 17 16 17 64 London Brunello 20 26 20 124 London Buona_Sera 17 15 19 46 London Caldesi 22 18 21 78 London Camerino 20 17 23 82 London Cantina_del_Ponte 16 13 14 66 London Caraffini 21 16 21 80 London Caravaggio 17 13 15 84 London Carluccio's 18 14 15 46 London Carpaccio 19 17 18 90 London Cecconi's 22 20 21 108 London Cipriani 20 20 18 134 London Ciro's_Pizza 16 14 15 42 London Clos_Maggiore 24 24 24 86 London Como_Lario 18 13 19 92 London Daphne's 22 20 20 96 London Diverso 20 18 18 78 London Elena's_l'Etoile 22 18 22 80 London Elistano 18 13 17 66 London Essenza 21 14 19 68 London Fiore 24 21 25 96 London Franco's 17 15 19 80 London Frankie's_Italian_Bar 14 14 14 66 London Friends 20 15 19 54 London Getti 18 13 19 66 London Giardinetto 21 16 23 110 London Giovanni's 21 16 20 66 London Harry's_Bar 23 24 25 122 London Il_Convivio 23 21 22 94 London Il_Portico 23 17 25 64 London l'Incontro 19 20 16 102 London La_Famiglia 21 14 20 84 London La_Genova 23 19 26 76 London La_Porchetta_Pizzeria 20 12 17 34 London Latium 22 17 20 80 London Little_Italy 18 11 15 58 London Locanda_Locatelli 25 23 23 108 London Locanda_Ottoemezzo 23 17 21 84 London Luciano 20 17 12 100 London Lucio 25 23 23 94 London Made_in_Italy 20 14 14 50 London Manicomio 21 17 16 78 London Mediterraneo 20 15 17 70 London Mimmo_D'Ischia 21 16 21 90 London Montepeliano 18 17 19 86 London Monza 19 14 18 74 London Oliveto 20 13 16 66 London Olivo 23 16 21 74 London Orso 21 17 20 78 London Osteria_Basilico 23 18 19 66 London Osteria_dell'Arancio 23 22 23 78 London Passione 23 15 20 92 London Pellicano 18 17 18 72 London Pizza_Express 16 13 15 34 London Quirinale 26 20 25 92 London Quo_Vadis 21 21 20 84 London Riccardo's 16 10 14 66 London River_Cafe 26 21 24 120 London Rosmarino 20 18 17 88 London Sale_e_Pepe 23 17 22 78 London San_Lorenzo 20 18 18 104 London Santini 2 19 22 104 London Sardo 21 14 19 76 London Sartoria 20 21 19 94 London Scalini 20 15 18 100 London Signor_Sassi 23 18 23 82 London Spago 21 13 18 74 London Spiga 17 13 14 54 London Spighetta 17 10 17 48 London Strada 18 14 16 42 London Timo 23 16 22 86 London Toto's 23 20 23 102 London Vasco 24 16 22 74 London Verbanella 19 16 21 80 London Volt 17 20 15 88 London Zafferano 25 20 23 112 London Ziani 22 17 21 82 London Zilli_Fish 23 15 19 72 London Zizzi 15 15 14 42 NY Angelo's 23 15 19 43 NY Da_Nico 20 17 18 35 NY Ferrara 22 15 15 18 NY Grotta_Azzurra 17 16 16 47 NY Il_Cortile 23 20 19 50 NY Il_Fornaio 23 14 19 30 NY Il_Palazzo 21 17 20 42 NY La_Mela 18 11 17 35 NY Pellegrino's 22 17 21 40 NY Positano 20 14 18 36 NY Sal_Anthony's 18 17 18 38 NY Taormina 22 19 20 42 NY Umberto's 19 14 17 35 NY Vincent's 21 13 18 33 NY 'ino 24 14 18 25 NY Arturo's_Pizzeria 21 12 16 24 NY Babbo 27 23 25 74 NY Bar_Pitti 22 14 16 36 NY Bellavitae 22 18 19 49 NY Borgo_Antico 17 16 19 40 NY Da_Silvano 20 15 17 60 NY Ennio_&_Michael 19 16 21 44 NY Gonzo 22 17 18 41 NY Gradisca 20 17 17 41 NY Gusto 21 20 18 52 NY Il_Cantinori 22 21 22 59 NY Il_Mulino 27 18 23 83 NY Joe's_Pizza 23 5 12 8 NY John's_Pizzeria 22 12 15 21 NY La_Lanterna_di_Vittorio 19 20 16 27 NY Lupa 25 18 21 50 NY Marinella 23 16 23 41 NY Maurizio_Trattoria 20 16 19 46 NY Minetta_Tavern 18 16 17 41 NY Monte's 19 14 19 37 NY Osso_Buco 17 14 17 35 NY Otto 21 19 19 37 NY Patsy's_Pizzeria 20 12 15 23 NY Piadina 21 18 16 31 NY Piola 19 15 19 24 NY Po 25 16 21 47 NY Risotteria 21 10 18 23 NY Rocco 19 14 18 38 NY Trattoria_Pesce_&_Pasta 18 13 18 31 NY Uno_Chicago_Grill 14 12 13 22 NY Villa_Mosconi 19 15 21 44
UN Data File (Table 9.13):
These data are from the Human Development report of 2005. Note however that the values given are from 2003 except for CO2 which is 2002. website: http://hdr.undp.org/statistics/data/rc_2005.cfm HDI: HDI value; Fert: Total Fertility rate (births/woman); Cont: Contraceptive prevalence rate (%); Cell: Cellular subscribers (per 1000 people); Inter: Internet users (per 1000 people); GDP: GDP per capita (US$); CO2: Carbon dioxide emissions per capita (metric tons); Life: Life expectancy at birth, female (years); Liter: Adult literacy rate (female rate % ages 15 and above); FemEc: Female economic activity rate (% of male rate, ages 15 and above); Nation HDI Fert Cont Cell Inter GDP CO2 Life Liter FemEc Algeria 0.72 2.5 64 45 .. 2090 2.9 72.4 60.1 41 Argentina 0.86 2.4 .. .. .. 3524 3.5 78.2 97.2 48 Australia 0.96 1.7 76 719 567 26275 18.3 82.8 .. 79 Austria 0.94 1.4 51 879 462 31289 7.8 81.8 .. 66 Belgium 0.95 1.7 78 793 386 29096 6.8 82 .. 67 Brazil 0.79 2.3 77 264 .. 2788 1.8 74.6 88.6 52 Canada 0.95 1.5 75 419 .. 27079 16.5 82.4 .. 83 Chile 0.85 2 .. 511 272 4591 3.6 80.9 95.6 50 China 0.76 1.7 84 215 63 1100 2.7 73.5 86.5 86 Denmark 0.94 1.8 78 883 541 39332 8.9 79.4 .. 85 Egypt 0.66 3.3 60 84 44 1220 2.1 72.1 43.6 46 Finland 0.94 1.7 77 910 534 31058 12 81.7 .. 87 France 0.94 1.9 75 696 366 29410 6.2 83 .. 78 Germany 0.93 1.3 75 785 473 29115 9.8 81.5 .. 71 Greece 0.91 1.3 .. 902 150 15608 8.5 80.9 88.3 60 India 0.60 3.1 48 25 17 564 1.2 65 47.8 50 Iran 0.74 2.1 73 51 72 2066 5.3 71.9 70.4 39 Ireland 0.95 1.9 .. 880 317 38487 11 80.3 .. 54 Israel 0.92 2.9 68 961 .. 16481 11 81.7 95.6 69 Japan 0.94 1.3 56 679 483 33713 9.4 85.4 .. 68 Malaysia 0.80 2.9 55 442 344 4187 6.3 75.6 85.4 62 Mexico 0.81 2.4 68 295 120 6121 3.7 77.5 88.7 49 Netherlands 0.94 1.7 79 768 522 31532 9.4 81.1 .. 68 New Zealand 0.93 2 75 648 526 19847 8.7 81.3 .. 81 Nigeria 0.45 5.8 13 26 6 428 0.4 43.6 59.4 56 Norway 0.96 1.8 74 909 346 48412 12.2 81.9 .. 86 Pakistan 0.53 4.3 28 18 .. 555 0.7 63.2 35.2 44 Philippines 0.76 3.2 49 270 .. 989 0.9 72.5 92.7 62 Russian Fed. 0.80 1.3 73 249 .. 3018 9.9 72.1 99.2 83 Saudi Arabia 0.77 4.1 32 321 67 9532 15 73.9 69.3 29 South Africa 0.66 2.8 56 364 .. 3489 7.4 50.2 80.9 59 Spain 0.93 1.3 81 916 239 20404 7.3 83.2 .. 58 Sweden 0.95 1.6 78 980 .. 33676 5.8 82.4 .. 90 Switzerland 0.95 1.4 82 843 398 43553 5.7 83.2 .. 67 Turkey 0.75 2.5 64 394 85 3399 3 71.1 81.1 63 United Kingdom 0.94 1.7 84 912 .. 30253 9.2 80.6 .. 76 United States 0.94 2 76 546 556 37648 20.1 80 .. 83 Viet Nam 0.70 2.3 79 34 43 482 0.8 72.6 86.9 91 Yemen 0.49 6.2 21 35 .. 565 0.7 61.9 28.5 37
"House Selling Price" Data File (Excerpt in Table 9.4):
Selling price of homes in Gainesville, Florida, fall 2006, from Alachua County public records. The following table contains data on Price = selling price (dollars), Size = size of home (square feet), Beds = number of bedrooms, Baths = number of bathrooms, New = whether new (1 = yes, 0 = no), and Taxes = annual tax bill (dollars).
case Taxes Beds Baths New Price Size 1 3104 4 2 0 279900 2048 2 1173 2 1 0 146500 912 3 3076 4 2 0 237700 1654 4 1608 3 2 0 200000 2068 5 1454 3 3 0 159900 1477 6 2997 3 2 1 499900 3153 7 4054 3 2 0 265500 1355 8 3002 3 2 1 289900 2075 9 6627 5 4 0 587000 3990 10 320 3 2 0 70000 1160 11 630 3 2 0 64500 1220 12 1780 3 2 0 167000 1690 13 1630 3 2 0 114600 1380 14 1530 3 2 0 103000 1590 15 930 3 1 0 101000 1050 16 590 2 1 0 70000 770 17 1050 3 2 0 85000 1410 18 20 3 1 0 22500 1060 19 870 2 2 0 90000 1300 20 1320 3 2 0 133000 1500 21 1350 2 1 0 90500 820 22 5616 4 3 1 577500 3949 23 680 2 1 0 142500 1170 24 1840 3 2 0 160000 1500 25 3680 4 2 0 240000 2790 26 1660 3 1 0 87000 1030 27 1620 3 2 0 118600 1250 28 3100 3 2 0 140000 1760 29 2070 2 3 0 148000 1550 30 830 3 2 0 69000 1120 31 2260 4 2 0 176000 2000 32 1760 3 1 0 86500 1350 33 2750 3 2 1 180000 1840 34 2020 4 2 0 179000 2510 35 4900 3 3 1 338000 3110 36 1180 4 2 0 130000 1760 37 2150 3 2 0 163000 1710 38 1600 2 1 0 125000 1110 39 1970 3 2 0 100000 1360 40 2060 3 1 0 100000 1250 41 1980 3 1 0 100000 1250 42 1510 3 2 0 146500 1480 43 1710 3 2 0 144900 1520 44 1590 3 2 0 183000 2020 45 1230 3 2 0 69900 1010 46 1510 2 2 0 60000 1640 47 1450 2 2 0 127000 940 48 970 3 2 0 86000 1580 49 150 2 2 0 50000 860 50 1470 3 2 0 137000 1420 51 1850 3 2 0 121300 1270 52 820 2 1 0 81000 980 53 2050 4 2 0 188000 2300 54 710 3 2 0 85000 1430 55 1280 3 2 0 137000 1380 56 1360 3 2 0 145000 1240 57 830 3 2 0 69000 1120 58 800 3 2 0 109300 1120 59 1220 3 2 0 131500 1900 60 3360 4 3 0 200000 2430 61 210 3 2 0 81900 1080 62 380 2 1 0 91200 1350 63 1920 4 3 0 124500 1720 64 4350 3 3 0 225000 4050 65 1510 3 2 0 136500 1500 66 4154 3 3 0 381000 2581 67 1976 3 2 1 250000 2120 68 3605 3 3 1 354900 2745 69 1400 3 2 0 140000 1520 70 790 2 2 0 89900 1280 71 1210 3 2 0 137000 1620 72 1550 3 2 0 103000 1520 73 2800 3 2 0 183000 2030 74 2560 3 2 0 140000 1390 75 1390 4 2 0 160000 1880 76 5443 3 2 0 434000 2891 77 2850 2 1 0 130000 1340 78 2230 2 2 0 123000 940 79 20 2 1 0 21000 580 80 1510 4 2 0 85000 1410 81 710 3 2 0 69900 1150 82 1540 3 2 0 125000 1380 83 1780 3 2 1 162600 1470 84 2920 2 2 1 156900 1590 85 1710 3 2 1 105900 1200 86 1880 3 2 0 167500 1920 87 1680 3 2 0 151800 2150 88 3690 5 3 0 118300 2200 89 900 2 2 0 94300 860 90 560 3 1 0 93900 1230 91 2040 4 2 0 165000 1140 92 4390 4 3 1 285000 2650 93 690 3 1 0 45000 1060 94 2100 3 2 0 124900 1770 95 2880 4 2 0 147000 1860 96 990 2 2 0 176000 1060 97 3030 3 2 0 196500 1730 98 1580 3 2 0 132200 1370 99 1770 3 2 0 88400 1560 100 1430 3 2 0 127200 1340
"Florida crime" data file (Table 9.16 or 9.17):
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
"Mental Impairment" Data File (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
"Anorexia Study" Data File (Table 12.21):
Weights of Anorexic girls, before and after receiving one
of three possible therapies - b = cognitive behavioural, f = family
therapy, or c = 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
"Income, Education, and Racial-Ethnic Status" Data File (Table 13.1 of 4th edition):
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 16 10 b 1 0 18 7 b 1 0 26 9 b 1 0 16 11 b 1 0 34 14 b 1 0 22 12 b 1 0 42 16 b 1 0 42 16 b 1 0 16 9 b 1 0 20 10 b 1 0 66 16 b 1 0 26 12 b 1 0 20 10 b 1 0 30 15 b 1 0 20 10 b 1 0 30 19 b 1 0 32 16 h 0 1 16 11 h 0 1 20 10 h 0 1 58 16 h 0 1 30 12 h 0 1 26 10 h 0 1 20 8 h 0 1 40 12 h 0 1 32 10 h 0 1 22 11 h 0 1 20 10 h 0 1 56 14 h 0 1 32 12 h 0 1 30 11 h 0 1 30 14 w 0 0 48 14 w 0 0 40 7 w 0 0 84 18 w 0 0 50 10 w 0 0 38 12 w 0 0 30 12 w 0 0 76 16 w 0 0 48 16 w 0 0 36 11 w 0 0 40 11 w 0 0 44 12 w 0 0 30 10 w 0 0 60 15 w 0 0 24 9 w 0 0 88 17 w 0 0 46 16 w 0 0 50 16 w 0 0 50 14 w 0 0 22 11 w 0 0 26 12 w 0 0 46 16 w 0 0 22 9 w 0 0 24 9 w 0 0 64 14 w 0 0 62 16 w 0 0 24 10 w 0 0 50 13 w 0 0 32 10 w 0 0 34 16 w 0 0 52 18 w 0 0 24 12 w 0 0 22 14 w 0 0 20 13 w 0 0 30 14 w 0 0 24 13 w 0 0 120 18 w 0 0 22 10 w 0 0 82 16 w 0 0 18 12 w 0 0 26 12 w 0 0 104 14 w 0 0 28 12 w 0 0 32 12 w 0 0 38 14 w 0 0 44 12 w 0 0 22 12 w 0 0 18 10 w 0 0 24 12 w 0 0 56 20 w 0 0
"Fertility and GDP" Data File (Table 14.6):
Nation Fertility GDP Algeria 2.5 2090 Australia 1.7 26275 Austria 1.4 31289 Belgium 1.7 29096 Brazil 2.3 2788 Canada 1.5 27079 Chile 2.0 4591 China 1.7 1100 Denmark 1.8 39332 Egypt 3.3 1220 Finland 1.7 31058 France 1.9 29410 Germany 1.3 29115 Greece 1.3 15608 India 3.1 564 Iran 2.1 2066 Ireland 1.9 38487 Israel 2.9 16481 Japan 1.3 33713 Malaysia 2.9 4187 Mexico 2.4 6121 Netherlands 1.7 31532 NewZealand 2.0 19847 Nigeria 5.8 428 Norway 1.8 48412 Pakistan 4.3 555 Philippines 3.2 989 Russia 1.3 3018 SaudiaArabia 4.1 9532 SouthAfrica 2.8 3489 Spain 1.3 20404 Sweden 1.6 33676 Switzerland 1.4 43553 Turkey 2.5 3399 UnitKing 1.7 30253 US 2.0 37648 VietNam 2.3 482 Yemen 6.2 565
"U.S. Population Size" Data File (Table 14.8):
decade population
0 62.95
1 75.99
2 91.97
3 105.71
4 122.78
5 131.67
6 151.33
7 179.32
8 203.30
9 226.54
10 248.71
11 281.42
"Income and Credit Card Possession" Data File (Table 15.1):
Data on annual income (euros), number of subjects at that income
level, and number possessing a travel credit
card.
Source: Based on data in "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 credit 12 1 0 13 1 0 14 8 2 15 14 2 16 9 0 17 8 2 19 5 1 20 7 0 21 2 0 22 1 1 24 2 0 25 10 2 26 1 0 29 1 0 30 5 2 32 6 6 34 3 3 35 5 3 39 1 0 40 1 0 42 1 0 47 1 0 60 6 6 65 1 1
"Maine motor vehicle accident" data file (Table 15.23):
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
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 of third edition:
Birth rates in several countries. This table lists
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 -- -- --
aa@stat.ufl.edu