ANALYSE STATISTIQUE 1ère ETUDE
> desql(SEXE)
Effectifs Proportions
F 248 55.111
M 202 44.889
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
> desql(CLANGLE)
Effectifs Proportions
1 90 20.1340000
2 197 44.0720000
2.1 78 17.4500000
2.2 37 8.2770000
3 45 10.0670000
Total 447 100.0000000
Non Manquants 447 99.3333333
MANQUANTS 3 0.6666667
> desql(BRACKETS)
Effectifs Proportions
0 211 46.889
1 239 53.111
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
> desql(COLLAGE)
Effectifs Proportions
A 50 11.111
B 6 1.333
C 25 5.556
D 58 12.889
E 6 1.333
F 45 10.000
G 50 11.111
H 10 2.222
I 50 11.111
J 100 22.222
K 50 11.111
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
> desql(COLLAGE1)
Effectifs Proportions
A 205 45.556
B 200 44.444
C 45 10.000
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
> desql(COLLAGE2)
Effectifs Proportions
A 149 72.68300
B 6 2.92700
C 50 24.39000
Total 205 100.00000
Non Manquants 205 45.55556
MANQUANTS 245 54.44444
> desql(APPAREIL)
Effectifs Proportions
A 37 8.222
B 10 2.222
C 13 2.889
E 28 6.222
F 47 10.444
G 2 0.444
H 1 0.222
I 1 0.222
J 4 0.889
K 50 11.111
L 46 10.222
M 11 2.444
N 12 2.667
O 39 8.667
P 7 1.556
Q 46 10.222
R 4 0.889
S 72 16.000
T 11 2.444
U 4 0.889
V 5 1.111
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
> desql(APPAREIL1)
Effectifs Proportions
A 335 74.444
B 48 10.667
C 67 14.889
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
> desql(APPAREIL2)
Effectifs Proportions
A 73 16.222
B 377 83.778
Total 450 100.000
Non Manquants 450 100.000
MANQUANTS 0 0.000
>
>
> descr1(AGEPOSE,Tàp=TRUE)
$Descriptif
AGEPOSE
Effectifs présents 450.0000
Proportions de présents % 100.0000
Effectifs manquants 0.0000
Proportions de manquants % 0.0000
Moyenne 14.0489
Ecart-type 5.9968
Variance 35.9619
Erreur standard (s.e.m) 0.2827
Minimum 8.3000
Maximum 58.7000
Percentile 2,5 10.1000
Percentile 5 10.5000
Q1 11.8000
Médiane 12.7000
Q3 14.1000
Percentile 95 21.3500
Percentile 97,5 36.4575
Ecart inter-quartiles 2.3000
IC valeurs borne inf 2.2636
IC valeurs borne sup 25.8342
IC moyenne borne inf 13.4927
IC moyenne borne sup 14.6051
$TestNormalité
Test de normalité de Shapiro-Wilk : p = 0
Test de normalité de Kolmogorov-Smirnov : p = 0
$Triàplat
Eff. Eff. cum. Prop. Prop. cum
8.3 1 1 0.22 0.22
8.7 1 2 0.22 0.44
9.2 1 3 0.22 0.67
9.4 1 4 0.22 0.89
9.5 1 5 0.22 1.11
9.6 2 7 0.44 1.56
9.7 1 8 0.22 1.78
9.8 2 10 0.44 2.22
9.9 1 11 0.22 2.44
10.1 5 16 1.11 3.56
10.2 1 17 0.22 3.78
10.3 4 21 0.89 4.67
10.4 1 22 0.22 4.89
10.5 6 28 1.33 6.22
10.6 4 32 0.89 7.11
10.7 4 36 0.89 8.00
10.8 5 41 1.11 9.11
10.9 5 46 1.11 10.22
11 7 53 1.56 11.78
11.1 10 63 2.22 14.00
11.2 11 74 2.44 16.44
11.3 6 80 1.33 17.78
11.4 6 86 1.33 19.11
11.5 9 95 2.00 21.11
11.6 8 103 1.78 22.89
11.7 9 112 2.00 24.89
11.8 13 125 2.89 27.78
11.9 11 136 2.44 30.22
12 12 148 2.67 32.89
12.1 19 167 4.22 37.11
12.2 14 181 3.11 40.22
12.3 9 190 2.00 42.22
12.4 10 200 2.22 44.44
12.5 6 206 1.33 45.78
12.6 13 219 2.89 48.67
12.7 7 226 1.56 50.22
12.8 10 236 2.22 52.44
12.9 10 246 2.22 54.67
13 11 257 2.44 57.11
13.1 10 267 2.22 59.33
13.2 5 272 1.11 60.44
13.3 10 282 2.22 62.67
13.4 7 289 1.56 64.22
13.5 11 300 2.44 66.67
13.6 12 312 2.67 69.33
13.7 6 318 1.33 70.67
13.8 4 322 0.89 71.56
13.9 7 329 1.56 73.11
14 5 334 1.11 74.22
14.1 7 341 1.56 75.78
14.2 5 346 1.11 76.89
14.3 9 355 2.00 78.89
14.4 4 359 0.89 79.78
14.5 5 364 1.11 80.89
14.6 1 365 0.22 81.11
14.7 5 370 1.11 82.22
14.8 4 374 0.89 83.11
14.9 2 376 0.44 83.56
15 2 378 0.44 84.00
15.1 7 385 1.56 85.56
15.2 3 388 0.67 86.22
15.3 7 395 1.56 87.78
15.4 2 397 0.44 88.22
15.5 2 399 0.44 88.67
15.6 3 402 0.67 89.33
15.7 2 404 0.44 89.78
15.9 5 409 1.11 90.89
16 2 411 0.44 91.33
16.2 2 413 0.44 91.78
16.3 3 416 0.67 92.44
16.4 2 418 0.44 92.89
16.6 1 419 0.22 93.11
16.9 1 420 0.22 93.33
17.3 1 421 0.22 93.56
17.9 1 422 0.22 93.78
18.2 1 423 0.22 94.00
18.7 1 424 0.22 94.22
18.9 1 425 0.22 94.44
19 1 426 0.22 94.67
19.7 1 427 0.22 94.89
22.7 1 428 0.22 95.11
23.6 1 429 0.22 95.33
24.1 1 430 0.22 95.56
24.7 1 431 0.22 95.78
26.4 1 432 0.22 96.00
27.2 1 433 0.22 96.22
28.5 1 434 0.22 96.44
31 1 435 0.22 96.67
32 1 436 0.22 96.89
33.4 1 437 0.22 97.11
33.9 1 438 0.22 97.33
37.2 1 439 0.22 97.56
38.3 1 440 0.22 97.78
39.4 1 441 0.22 98.00
39.6 1 442 0.22 98.22
40.9 1 443 0.22 98.44
41.2 1 444 0.22 98.67
41.6 1 445 0.22 98.89
46.7 1 446 0.22 99.11
48.3 1 447 0.22 99.33
52.8 1 448 0.22 99.56
53.9 1 449 0.22 99.78
58.7 1 450 0.22 100.00
Message d'avis :
In ks.test(Y, pnorm) : cannot compute correct p-values with ties
> descr1(DT,Tàp=TRUE)
$Descriptif
DT
Effectifs présents 337.0000
Proportions de présents % 74.8889
Effectifs manquants 113.0000
Proportions de manquants % 25.1111
Moyenne 24.4184
Ecart-type 9.3376
Variance 87.1905
Erreur standard (s.e.m) 0.5087
Minimum 4.0000
Maximum 73.0000
Percentile 2,5 7.4000
Percentile 5 10.0000
Q1 18.0000
Médiane 24.0000
Q3 30.0000
Percentile 95 39.2000
Percentile 97,5 44.2000
Ecart inter-quartiles 12.0000
IC valeurs borne inf 6.0509
IC valeurs borne sup 42.7859
IC moyenne borne inf 23.4164
IC moyenne borne sup 25.4204
$TestNormalité
Test de normalité de Shapiro-Wilk : p = 0
Test de normalité de Kolmogorov-Smirnov : p = 0
$Triàplat
Eff. Eff. cum. Prop. Prop. cum
4 1 1 0.22 0.22
5 1 2 0.22 0.44
6 5 7 1.11 1.56
7 2 9 0.44 2.00
8 1 10 0.22 2.22
9 4 14 0.89 3.11
10 6 20 1.33 4.44
11 1 21 0.22 4.67
12 5 26 1.11 5.78
13 9 35 2.00 7.78
14 4 39 0.89 8.67
15 14 53 3.11 11.78
16 8 61 1.78 13.56
17 12 73 2.67 16.22
18 18 91 4.00 20.22
19 19 110 4.22 24.44
20 14 124 3.11 27.56
21 9 133 2.00 29.56
22 11 144 2.44 32.00
23 13 157 2.89 34.89
24 20 177 4.44 39.33
25 18 195 4.00 43.33
26 15 210 3.33 46.67
27 7 217 1.56 48.22
28 19 236 4.22 52.44
29 8 244 1.78 54.22
30 14 258 3.11 57.33
31 22 280 4.89 62.22
32 8 288 1.78 64.00
33 5 293 1.11 65.11
34 3 296 0.67 65.78
35 4 300 0.89 66.67
36 7 307 1.56 68.22
37 4 311 0.89 69.11
38 4 315 0.89 70.00
39 5 320 1.11 71.11
40 3 323 0.67 71.78
41 1 324 0.22 72.00
42 2 326 0.44 72.44
43 2 328 0.44 72.89
45 1 329 0.22 73.11
48 1 330 0.22 73.33
49 3 333 0.67 74.00
51 1 334 0.22 74.22
53 1 335 0.22 74.44
58 1 336 0.22 74.67
73 1 337 0.22 74.89
Message d'avis :
In ks.test(Y, pnorm) : cannot compute correct p-values with ties
> descr1(DT2,Tàp=TRUE)
$Descriptif
DT2
Effectifs présents 450.0000
Proportions de présents % 100.0000
Effectifs manquants 0.0000
Proportions de manquants % 0.0000
Moyenne 22.8402
Ecart-type 9.9006
Variance 98.0223
Erreur standard (s.e.m) 0.4667
Minimum 2.9897
Maximum 100.8624
Percentile 2,5 6.5133
Percentile 5 9.7183
Q1 16.7310
Médiane 21.8480
Q3 28.0821
Percentile 95 38.4016
Percentile 97,5 42.7269
Ecart inter-quartiles 11.3511
IC valeurs borne inf 3.3829
IC valeurs borne sup 42.2976
IC moyenne borne inf 21.9220
IC moyenne borne sup 23.7585
$TestNormalité
Test de normalité de Shapiro-Wilk : p = 0
Test de normalité de Kolmogorov-Smirnov : p = 0
$Triàplat
Eff. Eff. cum. Prop. Prop. cum
2.98973306 1 1 0.22 0.22
3.58110883 1 2 0.22 0.44
4.13963039 1 3 0.22 0.67
4.369609856 1 4 0.22 0.89
4.402464066 1 5 0.22 1.11
5.059548255 1 6 0.22 1.33
5.519507187 2 8 0.44 1.78
5.749486653 1 9 0.22 2.00
5.880903491 1 10 0.22 2.22
5.979466119 1 11 0.22 2.44
6.439425051 1 12 0.22 2.67
6.767967146 1 13 0.22 2.89
7.852156057 1 14 0.22 3.11
8.147843943 2 16 0.44 3.56
8.640657084 1 17 0.22 3.78
8.673511294 1 18 0.22 4.00
8.772073922 1 19 0.22 4.22
8.969199179 1 20 0.22 4.44
9.067761807 1 21 0.22 4.67
9.396303901 1 22 0.22 4.89
9.659137577 1 23 0.22 5.11
9.790554415 1 24 0.22 5.33
9.823408624 2 26 0.44 5.78
9.856262834 1 27 0.22 6.00
9.889117043 1 28 0.22 6.22
10.11909651 1 29 0.22 6.44
10.15195072 3 32 0.67 7.11
10.25051335 3 35 0.67 7.78
10.28336756 1 36 0.22 8.00
10.94045175 1 37 0.22 8.22
11.03901437 1 38 0.22 8.44
11.07186858 2 40 0.44 8.89
11.17043121 2 42 0.44 9.33
11.40041068 1 43 0.22 9.56
11.63039014 1 44 0.22 9.78
11.72895277 1 45 0.22 10.00
11.76180698 1 46 0.22 10.22
11.86036961 3 49 0.67 10.89
11.89322382 1 50 0.22 11.11
11.92607803 1 51 0.22 11.33
11.95893224 1 52 0.22 11.56
11.99178645 1 53 0.22 11.78
12.1889117 1 54 0.22 12.00
12.32032854 2 56 0.44 12.44
12.35318275 1 57 0.22 12.67
12.55030801 1 58 0.22 12.89
12.64887064 2 60 0.44 13.33
12.8788501 1 61 0.22 13.56
12.91170431 1 62 0.22 13.78
12.97741273 2 64 0.44 14.22
13.01026694 2 66 0.44 14.67
13.50308008 2 68 0.44 15.11
13.5687885 1 69 0.22 15.33
13.60164271 2 71 0.44 15.78
14.16016427 1 72 0.22 16.00
14.19301848 1 73 0.22 16.22
14.2587269 2 75 0.44 16.67
14.39014374 1 76 0.22 16.89
14.48870637 4 80 0.89 17.78
14.6201232 1 81 0.22 18.00
14.65297741 1 82 0.22 18.22
14.71868583 1 83 0.22 18.44
14.85010267 4 87 0.89 19.33
14.98151951 2 89 0.44 19.78
15.17864476 1 90 0.22 20.00
15.21149897 1 91 0.22 20.22
15.27720739 1 92 0.22 20.44
15.34291581 1 93 0.22 20.67
15.37577002 2 95 0.44 21.11
15.40862423 1 96 0.22 21.33
15.70431211 2 98 0.44 21.78
15.86858316 1 99 0.22 22.00
16.06570842 1 100 0.22 22.22
16.13141684 3 103 0.67 22.89
16.16427105 1 104 0.22 23.11
16.22997947 1 105 0.22 23.33
16.29568789 1 106 0.22 23.56
16.32854209 1 107 0.22 23.78
16.49281314 1 108 0.22 24.00
16.55852156 3 111 0.67 24.67
16.72279261 2 113 0.44 25.11
16.75564682 1 114 0.22 25.33
16.78850103 2 116 0.44 25.78
16.88706366 1 117 0.22 26.00
16.91991786 2 119 0.44 26.44
16.98562628 1 120 0.22 26.67
17.01848049 1 121 0.22 26.89
17.14989733 2 123 0.44 27.33
17.28131417 1 124 0.22 27.56
17.31416838 1 125 0.22 27.78
17.34702259 1 126 0.22 28.00
17.3798768 1 127 0.22 28.22
17.41273101 1 128 0.22 28.44
17.47843943 2 130 0.44 28.89
17.54414784 1 131 0.22 29.11
17.60985626 2 133 0.44 29.56
17.7412731 3 136 0.67 30.22
17.77412731 1 137 0.22 30.44
17.80698152 1 138 0.22 30.67
17.83983573 1 139 0.22 30.89
17.93839836 3 142 0.67 31.56
18.00410678 1 143 0.22 31.78
18.0698152 2 145 0.44 32.22
18.1026694 1 146 0.22 32.44
18.23408624 1 147 0.22 32.67
18.29979466 2 149 0.44 33.11
18.39835729 1 150 0.22 33.33
18.46406571 2 152 0.44 33.78
18.49691992 2 154 0.44 34.22
18.52977413 3 157 0.67 34.89
18.62833676 2 159 0.44 35.33
18.69404517 1 160 0.22 35.56
18.72689938 1 161 0.22 35.78
18.75975359 1 162 0.22 36.00
18.82546201 1 163 0.22 36.22
18.95687885 3 166 0.67 36.89
18.98973306 1 167 0.22 37.11
19.08829569 3 170 0.67 37.78
19.18685832 1 171 0.22 38.00
19.21971253 2 173 0.44 38.44
19.31827515 7 180 1.56 40.00
19.44969199 2 182 0.44 40.44
19.54825462 1 183 0.22 40.67
19.58110883 1 184 0.22 40.89
19.64681725 1 185 0.22 41.11
19.67967146 2 187 0.44 41.56
19.77823409 1 188 0.22 41.78
19.90965092 1 189 0.22 42.00
20.1724846 1 190 0.22 42.22
20.27104723 1 191 0.22 42.44
20.36960986 2 193 0.44 42.89
20.43531828 1 194 0.22 43.11
20.46817248 1 195 0.22 43.33
20.50102669 1 196 0.22 43.56
20.63244353 2 198 0.44 44.00
20.69815195 1 199 0.22 44.22
20.79671458 2 201 0.44 44.67
20.82956879 1 202 0.22 44.89
20.92813142 1 203 0.22 45.11
20.96098563 1 204 0.22 45.33
21.05954825 2 206 0.44 45.78
21.09240246 2 208 0.44 46.22
21.12525667 1 209 0.22 46.44
21.15811088 1 210 0.22 46.67
21.25667351 1 211 0.22 46.89
21.28952772 1 212 0.22 47.11
21.32238193 1 213 0.22 47.33
21.38809035 2 215 0.44 47.78
21.51950719 1 216 0.22 48.00
21.5523614 1 217 0.22 48.22
21.68377823 1 218 0.22 48.44
21.74948665 2 220 0.44 48.89
21.81519507 3 223 0.67 49.56
21.84804928 3 226 0.67 50.22
21.88090349 1 227 0.22 50.44
22.07802875 1 228 0.22 50.67
22.14373717 1 229 0.22 50.89
22.17659138 1 230 0.22 51.11
22.20944559 1 231 0.22 51.33
22.24229979 1 232 0.22 51.56
22.30800821 1 233 0.22 51.78
22.37371663 1 234 0.22 52.00
22.50513347 1 235 0.22 52.22
22.66940452 3 238 0.67 52.89
22.80082136 3 241 0.67 53.56
22.83367556 1 242 0.22 53.78
22.99794661 3 245 0.67 54.44
23.09650924 1 246 0.22 54.67
23.19507187 2 248 0.44 55.11
23.22792608 2 250 0.44 55.56
23.32648871 2 252 0.44 56.00
23.35934292 1 253 0.22 56.22
23.45790554 2 255 0.44 56.67
23.49075975 1 256 0.22 56.89
23.58932238 2 258 0.44 57.33
23.62217659 2 260 0.44 57.78
23.68788501 2 262 0.44 58.22
23.78644764 2 264 0.44 58.67
23.91786448 1 265 0.22 58.89
24.0164271 2 267 0.44 59.33
24.04928131 2 269 0.44 59.78
24.08213552 2 271 0.44 60.22
24.14784394 2 273 0.44 60.67
24.21355236 1 274 0.22 60.89
24.24640657 2 276 0.44 61.33
24.27926078 1 277 0.22 61.56
24.41067762 1 278 0.22 61.78
24.47638604 1 279 0.22 62.00
24.50924025 1 280 0.22 62.22
24.57494867 1 281 0.22 62.44
24.60780287 2 283 0.44 62.89
24.83778234 1 284 0.22 63.11
24.90349076 1 285 0.22 63.33
24.93634497 2 287 0.44 63.78
25.00205339 1 288 0.22 64.00
25.0349076 1 289 0.22 64.22
25.06776181 2 291 0.44 64.67
25.10061602 1 292 0.22 64.89
25.13347023 1 293 0.22 65.11
25.29774127 2 295 0.44 65.56
25.49486653 1 296 0.22 65.78
25.52772074 2 298 0.44 66.22
25.62628337 2 300 0.44 66.67
25.724846 2 302 0.44 67.11
25.85626283 1 303 0.22 67.33
25.98767967 1 304 0.22 67.56
26.05338809 1 305 0.22 67.78
26.11909651 2 307 0.44 68.22
26.34907598 2 309 0.44 68.67
26.38193018 1 310 0.22 68.89
26.4476386 1 311 0.22 69.11
26.48049281 1 312 0.22 69.33
26.54620123 1 313 0.22 69.56
26.64476386 1 314 0.22 69.78
26.94045175 1 315 0.22 70.00
26.97330595 1 316 0.22 70.22
27.07186858 1 317 0.22 70.44
27.137577 1 318 0.22 70.67
27.17043121 1 319 0.22 70.89
27.23613963 2 321 0.44 71.33
27.36755647 1 322 0.22 71.56
27.4661191 1 323 0.22 71.78
27.49897331 1 324 0.22 72.00
27.53182752 1 325 0.22 72.22
27.59753593 2 327 0.44 72.67
27.69609856 1 328 0.22 72.89
27.72895277 3 331 0.67 73.56
27.79466119 1 332 0.22 73.78
27.86036961 1 333 0.22 74.00
27.89322382 1 334 0.22 74.22
27.92607803 1 335 0.22 74.44
27.95893224 1 336 0.22 74.67
28.05749487 1 337 0.22 74.89
28.09034908 1 338 0.22 75.11
28.15605749 2 340 0.44 75.56
28.1889117 2 342 0.44 76.00
28.48459959 1 343 0.22 76.22
28.64887064 1 344 0.22 76.44
28.68172485 1 345 0.22 76.67
28.74743326 1 346 0.22 76.89
28.97741273 1 347 0.22 77.11
29.2073922 1 348 0.22 77.33
29.47022587 1 349 0.22 77.56
29.5687885 2 351 0.44 78.00
29.66735113 1 352 0.22 78.22
29.76591376 1 353 0.22 78.44
29.8973306 2 355 0.44 78.89
29.9301848 1 356 0.22 79.11
29.99589322 4 360 0.89 80.00
30.02874743 1 361 0.22 80.22
30.06160164 1 362 0.22 80.44
30.09445585 2 364 0.44 80.89
30.12731006 5 369 1.11 82.00
30.19301848 1 370 0.22 82.22
30.22587269 1 371 0.22 82.44
30.2587269 2 373 0.44 82.89
30.45585216 1 374 0.22 83.11
30.58726899 1 375 0.22 83.33
30.65297741 1 376 0.22 83.56
30.71868583 3 379 0.67 84.22
30.78439425 2 381 0.44 84.67
30.81724846 1 382 0.22 84.89
30.9486653 1 383 0.22 85.11
30.98151951 1 384 0.22 85.33
31.01437372 1 385 0.22 85.56
31.17864476 1 386 0.22 85.78
31.27720739 1 387 0.22 86.00
31.37577002 1 388 0.22 86.22
31.47433265 1 389 0.22 86.44
31.50718686 1 390 0.22 86.67
31.73716632 2 392 0.44 87.11
31.93429158 1 393 0.22 87.33
31.96714579 1 394 0.22 87.56
32 1 395 0.22 87.78
32.49281314 1 396 0.22 88.00
32.55852156 1 397 0.22 88.22
32.65708419 1 398 0.22 88.44
32.72279261 1 399 0.22 88.67
32.75564682 1 400 0.22 88.89
32.82135524 1 401 0.22 89.11
32.98562628 1 402 0.22 89.33
33.11704312 1 403 0.22 89.56
33.90554415 1 404 0.22 89.78
34.03696099 1 405 0.22 90.00
34.52977413 1 406 0.22 90.22
34.75975359 1 407 0.22 90.44
34.82546201 1 408 0.22 90.67
34.85831622 1 409 0.22 90.89
35.41683778 2 411 0.44 91.33
35.87679671 2 413 0.44 91.78
35.90965092 1 414 0.22 92.00
35.94250513 1 415 0.22 92.22
36.00821355 1 416 0.22 92.44
36.10677618 1 417 0.22 92.67
36.1724846 1 418 0.22 92.89
36.23819302 1 419 0.22 93.11
36.59958932 1 420 0.22 93.33
37.42094456 2 422 0.44 93.78
37.65092402 1 423 0.22 94.00
37.74948665 1 424 0.22 94.22
37.81519507 1 425 0.22 94.44
38.24229979 1 426 0.22 94.67
38.275154 1 427 0.22 94.89
38.50513347 1 428 0.22 95.11
38.73511294 1 429 0.22 95.33
38.89938398 1 430 0.22 95.56
39.03080082 1 431 0.22 95.78
39.62217659 1 432 0.22 96.00
39.78644764 1 433 0.22 96.22
39.91786448 1 434 0.22 96.44
40.93634497 1 435 0.22 96.67
41.16632444 1 436 0.22 96.89
42.05338809 1 437 0.22 97.11
42.21765914 1 438 0.22 97.33
42.87474333 1 439 0.22 97.56
44.58316222 1 440 0.22 97.78
46.22587269 1 441 0.22 98.00
47.70431211 1 442 0.22 98.22
48.39425051 1 443 0.22 98.44
48.45995893 1 444 0.22 98.67
48.91991786 1 445 0.22 98.89
50.46406571 1 446 0.22 99.11
52.92813142 1 447 0.22 99.33
57.82340862 1 448 0.22 99.56
72.24640657 1 449 0.22 99.78
100.862423 1 450 0.22 100.00
Message d'avis :
In ks.test(Y, pnorm) : cannot compute correct p-values with ties
> descr1(NBRACKETS,Tàp=TRUE)
$Descriptif
NBRACKETS
Effectifs présents 450.0000
Proportions de présents % 100.0000
Effectifs manquants 0.0000
Proportions de manquants % 0.0000
Moyenne 1.4289
Ecart-type 2.4295
Variance 5.9025
Erreur standard (s.e.m) 0.1145
Minimum 0.0000
Maximum 18.0000
Percentile 2,5 0.0000
Percentile 5 0.0000
Q1 0.0000
Médiane 1.0000
Q3 2.0000
Percentile 95 6.0000
Percentile 97,5 9.0000
Ecart inter-quartiles 2.0000
IC valeurs borne inf -3.3457
IC valeurs borne sup 6.2035
IC moyenne borne inf 1.2036
IC moyenne borne sup 1.6542
$TestNormalité
Test de normalité de Shapiro-Wilk : p = 0
Test de normalité de Kolmogorov-Smirnov : p = 0
$Triàplat
Eff. Eff. cum. Prop. Prop. cum
0 211 211 46.89 46.89
1 115 326 25.56 72.44
2 46 372 10.22 82.67
3 24 396 5.33 88.00
4 19 415 4.22 92.22
5 10 425 2.22 94.44
6 3 428 0.67 95.11
7 5 433 1.11 96.22
8 3 436 0.67 96.89
9 4 440 0.89 97.78
10 3 443 0.67 98.44
11 2 445 0.44 98.89
12 1 446 0.22 99.11
13 1 447 0.22 99.33
14 1 448 0.22 99.56
16 1 449 0.22 99.78
18 1 450 0.22 100.00
Message d'avis :
In ks.test(Y, pnorm) : cannot compute correct p-values with ties
> descr1(XHBD,Tàp=TRUE)
$Descriptif
XHBD
Effectifs présents 449.0000
Proportions de présents % 99.7778
Effectifs manquants 1.0000
Proportions de manquants % 0.2222
Moyenne 2.0674
Ecart-type 0.9974
Variance 0.9948
Erreur standard (s.e.m) 0.0471
Minimum 1.0000
Maximum 5.0000
Percentile 2,5 1.0000
Percentile 5 1.0000
Q1 1.0000
Médiane 2.0000
Q3 3.0000
Percentile 95 4.0000
Percentile 97,5 5.0000
Ecart inter-quartiles 2.0000
IC valeurs borne inf 0.1073
IC valeurs borne sup 4.0276
IC moyenne borne inf 1.9748
IC moyenne borne sup 2.1601
$TestNormalité
Test de normalité de Shapiro-Wilk : p = 0
Test de normalité de Kolmogorov-Smirnov : p = 0
$Triàplat
Eff. Eff. cum. Prop. Prop. cum
1 134 134 29.78 29.78
1.090909091 1 135 0.22 30.00
1.117647059 1 136 0.22 30.22
1.142857143 1 137 0.22 30.44
1.2 2 139 0.44 30.89
1.214285714 1 140 0.22 31.11
1.25 3 143 0.67 31.78
1.272727273 1 144 0.22 32.00
1.3 1 145 0.22 32.22
1.307692308 2 147 0.44 32.67
1.333333333 3 150 0.67 33.33
1.363636364 1 151 0.22 33.56
1.4 2 153 0.44 34.00
1.428571429 1 154 0.22 34.22
1.461538462 1 155 0.22 34.44
1.5 9 164 2.00 36.44
1.555555556 1 165 0.22 36.67
1.5625 1 166 0.22 36.89
1.588235294 1 167 0.22 37.11
1.6 2 169 0.44 37.56
1.625 1 170 0.22 37.78
1.636363636 1 171 0.22 38.00
1.642857143 1 172 0.22 38.22
1.666666667 7 179 1.56 39.78
1.705882353 1 180 0.22 40.00
1.714285714 1 181 0.22 40.22
1.722222222 1 182 0.22 40.44
1.8 4 186 0.89 41.33
1.833333333 4 190 0.89 42.22
1.857142857 1 191 0.22 42.44
1.909090909 2 193 0.44 42.89
1.916666667 2 195 0.44 43.33
1.933333333 1 196 0.22 43.56
2 79 275 17.56 61.11
2.1 1 276 0.22 61.33
2.111111111 1 277 0.22 61.56
2.142857143 1 278 0.22 61.78
2.153846154 2 280 0.44 62.22
2.166666667 2 282 0.44 62.67
2.2 3 285 0.67 63.33
2.230769231 1 286 0.22 63.56
2.235294118 1 287 0.22 63.78
2.25 2 289 0.44 64.22
2.266666667 1 290 0.22 64.44
2.285714286 2 292 0.44 64.89
2.333333333 1 293 0.22 65.11
2.375 1 294 0.22 65.33
2.384615385 2 296 0.44 65.78
2.4 1 297 0.22 66.00
2.416666667 1 298 0.22 66.22
2.428571429 3 301 0.67 66.89
2.444444444 1 302 0.22 67.11
2.461538462 2 304 0.44 67.56
2.5 4 308 0.89 68.44
2.523809524 1 309 0.22 68.67
2.571428571 1 310 0.22 68.89
2.6 4 314 0.89 69.78
2.642857143 1 315 0.22 70.00
2.692307692 1 316 0.22 70.22
2.733333333 1 317 0.22 70.44
2.75 1 318 0.22 70.67
2.769230769 1 319 0.22 70.89
2.8 3 322 0.67 71.56
2.909090909 1 323 0.22 71.78
2.923076923 2 325 0.44 72.22
3 84 409 18.67 90.89
3.1 1 410 0.22 91.11
3.2 1 411 0.22 91.33
3.222222222 2 413 0.44 91.78
3.266666667 1 414 0.22 92.00
3.307692308 3 417 0.67 92.67
3.333333333 1 418 0.22 92.89
3.444444444 1 419 0.22 93.11
3.933333333 1 420 0.22 93.33
4 16 436 3.56 96.89
5 13 449 2.89 99.78
Message d'avis :
In ks.test(Y, pnorm) : cannot compute correct p-values with ties
> descr1(XHBDINT,Tàp=TRUE)
$Descriptif
XHBDINT
Effectifs présents 449.0000
Proportions de présents % 99.7778
Effectifs manquants 1.0000
Proportions de manquants % 0.2222
Moyenne 2.0646
Ecart-type 1.0013
Variance 1.0025
Erreur standard (s.e.m) 0.0473
Minimum 1.0000
Maximum 5.0000
Percentile 2,5 1.0000
Percentile 5 1.0000
Q1 1.0000
Médiane 2.0000
Q3 3.0000
Percentile 95 4.0000
Percentile 97,5 5.0000
Ecart inter-quartiles 2.0000
IC valeurs borne inf 0.0968
IC valeurs borne sup 4.0323
IC moyenne borne inf 1.9716
IC moyenne borne sup 2.1576
$TestNormalité
Test de normalité de Shapiro-Wilk : p = 0
Test de normalité de Kolmogorov-Smirnov : p = 0
$Triàplat
Eff. Eff. cum. Prop. Prop. cum
1 155 155 34.44 34.44
2 153 308 34.00 68.44
3 111 419 24.67 93.11
4 17 436 3.78 96.89
5 13 449 2.89 99.78
Message d'avis :
In ks.test(Y, pnorm) : cannot compute correct p-values with ties
> table(BRACKETS,SEXE)
SEXE
BRACKETS F M
0 125 86
1 123 116
> table(BRACKETS,CLANGLE)
CLANGLE
BRACKETS 1 2 2.1 2.2 3
0 52 83 37 13 23
1 38 114 41 24 22
> table(BRACKETS,COLLAGE1)
COLLAGE1
BRACKETS A B C
0 90 108 13
1 115 92 32
> table(BRACKETS,COLLAGE2)
COLLAGE2
BRACKETS A B C
0 68 2 20
1 81 4 30
> table(BRACKETS,APPAREIL1)
APPAREIL1
BRACKETS A B C
0 153 18 40
1 182 30 27
> table(BRACKETS,APPAREIL2)
APPAREIL2
BRACKETS A B
0 36 175
1 37 202
> table(BRACKETS,PRAT)
PRAT
BRACKETS 1 2 3 4 5 6 7 8 9
0 29 16 28 16 20 23 31 26 22
1 21 34 22 34 30 27 19 24 28
>
>
> chisq.test(BRACKETS,SEXE)
Pearson's Chi-squared test with Yates' continuity correction
data: BRACKETS and SEXE
X-squared = 2.4346, df = 1, p-value = 0.1187
> chisq.test(BRACKETS,CLANGLE)
Pearson's Chi-squared test
data: BRACKETS and CLANGLE
X-squared = 8.4443, df = 4, p-value = 0.0766
> chisq.test(BRACKETS,COLLAGE1)
Pearson's Chi-squared test
data: BRACKETS and COLLAGE1
X-squared = 10.65, df = 2, p-value = 0.004868
> chisq.test(BRACKETS,COLLAGE2)
Pearson's Chi-squared test
data: BRACKETS and COLLAGE2
X-squared = 0.7635, df = 2, p-value = 0.6827
Message d'avis :
In chisq.test(BRACKETS, COLLAGE2) :
l'approximation du Chi-2 est peut-être incorrecte
> chisq.test(BRACKETS,APPAREIL1)
Pearson's Chi-squared test
data: BRACKETS and APPAREIL1
X-squared = 6.3151, df = 2, p-value = 0.04253
> chisq.test(BRACKETS,APPAREIL2)
Pearson's Chi-squared test with Yates' continuity correction
data: BRACKETS and APPAREIL2
X-squared = 0.1061, df = 1, p-value = 0.7446
> chisq.test(BRACKETS,PRAT)
Pearson's Chi-squared test
data: BRACKETS and PRAT
X-squared = 19.2925, df = 8, p-value = 0.01337
>
> summary(glm(BRACKETS~SEXE,family="binomial")) REGRESSION LOGISTIQUE
Call:
glm(formula = BRACKETS ~ SEXE, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.307 -1.171 1.053 1.184 1.184
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.01613 0.12700 -0.127 0.8989
SEXEM 0.31537 0.19073 1.654 0.0982 . =ln(OR)+son écart-type
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 622.09 on 449 degrees of freedom
Residual deviance: 619.34 on 448 degrees of freedom
AIC: 623.34
Number of Fisher Scoring iterations: 3
> summary(glm(BRACKETS~AGEPOSE,family="binomial"))
Call:
glm(formula = BRACKETS ~ AGEPOSE, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.231 -1.231 1.125 1.125 1.129
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.1283935 0.2408110 0.533 0.594
AGEPOSE -0.0002696 0.0157664 -0.017 0.986
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 622.09 on 449 degrees of freedom
Residual deviance: 622.09 on 448 degrees of freedom
AIC: 626.09
Number of Fisher Scoring iterations: 3
> summary(glm(BRACKETS~DT,family="binomial"))
Call:
glm(formula = BRACKETS ~ DT, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.8209 -1.2006 0.8929 1.0933 1.3936
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.67820 0.32237 -2.104 0.03540 *
DT 0.03663 0.01263 2.901 0.00372 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 463.54 on 336 degrees of freedom
Residual deviance: 454.56 on 335 degrees of freedom
(113 observations deleted due to missingness)
AIC: 458.56
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~DT2,family="binomial"))
Call:
glm(formula = BRACKETS ~ DT2, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.9063 -1.1666 0.8444 1.1134 1.4932
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.84591 0.26508 -3.191 0.001417 **
DT2 0.04298 0.01108 3.879 0.000105 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 622.09 on 449 degrees of freedom
Residual deviance: 605.18 on 448 degrees of freedom
AIC: 609.18
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~as.factor(CLANGLE),family="binomial"))
Call:
glm(formula = BRACKETS ~ as.factor(CLANGLE), family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.4464 -1.2213 0.9304 1.0459 1.3132
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.3137 0.2134 -1.470 0.1416
as.factor(CLANGLE)2 0.6310 0.2576 2.449 0.0143 *
as.factor(CLANGLE)2.1 0.4163 0.3114 1.337 0.1812
as.factor(CLANGLE)2.2 0.9268 0.4051 2.288 0.0222 *
as.factor(CLANGLE)3 0.2692 0.3667 0.734 0.4629
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 617.52 on 446 degrees of freedom
Residual deviance: 609.04 on 442 degrees of freedom
(3 observations deleted due to missingness)
AIC: 619.04
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~XHBD,family="binomial"))
Call:
glm(formula = BRACKETS ~ XHBD, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-2.2492 -1.0333 0.5873 1.1281 1.4671
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.4358 0.2475 -5.801 6.60e-09 ***
XHBD 0.7765 0.1158 6.705 2.02e-11 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 620.57 on 448 degrees of freedom
Residual deviance: 566.72 on 447 degrees of freedom
(1 observation deleted due to missingness)
AIC: 570.72
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~COLLAGE1,family="binomial"))
Call:
glm(formula = BRACKETS ~ COLLAGE1, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.5759 -1.1101 0.8257 1.0752 1.2462
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.2451 0.1407 1.742 0.0816 .
COLLAGE1B -0.4055 0.1998 -2.029 0.0425 *
COLLAGE1C 0.6557 0.3577 1.833 0.0668 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 622.09 on 449 degrees of freedom
Residual deviance: 611.22 on 447 degrees of freedom
AIC: 617.22
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~COLLAGE2,family="binomial"))
Call:
glm(formula = BRACKETS ~ COLLAGE2, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.482 -1.253 1.011 1.104 1.104
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.1749 0.1645 1.064 0.287
COLLAGE2B 0.5182 0.8815 0.588 0.557
COLLAGE2C 0.2305 0.3322 0.694 0.488
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 281.13 on 204 degrees of freedom
Residual deviance: 280.36 on 202 degrees of freedom
(245 observations deleted due to missingness)
AIC: 286.36
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~APPAREIL1,family="binomial"))
Call:
glm(formula = BRACKETS ~ APPAREIL1, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.4006 -1.2520 0.9695 1.1046 1.3482
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.1736 0.1097 1.582 0.1135
APPAREIL1B 0.3373 0.3177 1.062 0.2884
APPAREIL1C -0.5666 0.2722 -2.082 0.0373 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 622.09 on 449 degrees of freedom
Residual deviance: 615.75 on 447 degrees of freedom
AIC: 621.75
Number of Fisher Scoring iterations: 4
> summary(glm(BRACKETS~APPAREIL2,family="binomial"))
Call:
glm(formula = BRACKETS ~ APPAREIL2, family = "binomial")
Deviance Residuals:
Min 1Q Median 3Q Max
-1.239 -1.239 1.117 1.117 1.166
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0274 0.2341 0.117 0.907
APPAREIL2B 0.1161 0.2559 0.454 0.650
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 622.09 on 449 degrees of freedom
Residual deviance: 621.88 on 448 degrees of freedom
AIC: 625.88
Number of Fisher Scoring iterations: 3