no commit message

parent a5057cc4
...@@ -10,7 +10,8 @@ ...@@ -10,7 +10,8 @@
"## Contexte\n", "## Contexte\n",
"*En 1972-1974, à Whickham, une ville du nord-est de l'Angleterre, située à environ 6,5 kilomètres au sud-ouest de Newcastle upon Tyne, un sondage d'un sixième des électeurs a été effectué afin d'éclairer des travaux sur les maladies thyroïdiennes et cardiaques (Tunbridge et al. 1977). Une suite de cette étude a été menée vingt ans plus tard (Vanderpump et al. 1995). Certains des résultats avaient trait au tabagisme et cherchaient à savoir si les individus étaient toujours en vie lors de la seconde étude. Par simplicité, nous nous restreindrons aux femmes et parmi celles-ci aux 1314 qui ont été catégorisées comme \"fumant actuellement\" ou \"n'ayant jamais fumé\". Il y avait relativement peu de femmes dans le sondage initial ayant fumé et ayant arrêté depuis (162) et très peu pour lesquelles l'information n'était pas disponible (18). La survie à 20 ans a été déterminée pour l'ensemble des femmes du premier sondage.*\n", "*En 1972-1974, à Whickham, une ville du nord-est de l'Angleterre, située à environ 6,5 kilomètres au sud-ouest de Newcastle upon Tyne, un sondage d'un sixième des électeurs a été effectué afin d'éclairer des travaux sur les maladies thyroïdiennes et cardiaques (Tunbridge et al. 1977). Une suite de cette étude a été menée vingt ans plus tard (Vanderpump et al. 1995). Certains des résultats avaient trait au tabagisme et cherchaient à savoir si les individus étaient toujours en vie lors de la seconde étude. Par simplicité, nous nous restreindrons aux femmes et parmi celles-ci aux 1314 qui ont été catégorisées comme \"fumant actuellement\" ou \"n'ayant jamais fumé\". Il y avait relativement peu de femmes dans le sondage initial ayant fumé et ayant arrêté depuis (162) et très peu pour lesquelles l'information n'était pas disponible (18). La survie à 20 ans a été déterminée pour l'ensemble des femmes du premier sondage.*\n",
"\n", "\n",
"## Importation des données" "## Importation des données\n",
"Les données sont mises à disposition sur Github. Pour nous protéger contre une éventuelle disparition ou modification du jeux de données, nous faisons une copie locale de ce jeux de données que nous préservons avec notre analyse. Il est inutile et même risquée de télécharger les données à chaque exécution, car dans le cas d'une panne nous pourrions remplacer nos données par un fichier défectueux. Pour cette raison, nous téléchargeons les données seulement si la copie locale n'existe pas."
] ]
}, },
{ {
...@@ -140,7 +141,184 @@ ...@@ -140,7 +141,184 @@
"\n", "\n",
"- L'âge moyen au moment de la première étude est de 47 ans (min : 18 ans et max : 89 ans). \n", "- L'âge moyen au moment de la première étude est de 47 ans (min : 18 ans et max : 89 ans). \n",
"- Presque la moitié de la population étudiée fumait lors de la première étude.\n", "- Presque la moitié de la population étudiée fumait lors de la première étude.\n",
"- Environ 1/4 des femmes sont décédées au moment de la deuxième étude. " "- Environ 1/4 des femmes sont décédées au moment de la deuxième étude. \n",
"\n",
"### Calcul de l'effectif et du taux de mortalité général"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<thead><tr><th></th><th scope=col>Alive</th><th scope=col>Dead</th><th scope=col>Sum</th></tr></thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>No</th><td>502 </td><td>230 </td><td> 732</td></tr>\n",
"\t<tr><th scope=row>Yes</th><td>443 </td><td>139 </td><td> 582</td></tr>\n",
"\t<tr><th scope=row>Sum</th><td>945 </td><td>369 </td><td>1314</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"\\begin{tabular}{r|lll}\n",
" & Alive & Dead & Sum\\\\\n",
"\\hline\n",
"\tNo & 502 & 230 & 732\\\\\n",
"\tYes & 443 & 139 & 582\\\\\n",
"\tSum & 945 & 369 & 1314\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"| <!--/--> | Alive | Dead | Sum | \n",
"|---|---|---|\n",
"| No | 502 | 230 | 732 | \n",
"| Yes | 443 | 139 | 582 | \n",
"| Sum | 945 | 369 | 1314 | \n",
"\n",
"\n"
],
"text/plain": [
" \n",
" Alive Dead Sum \n",
" No 502 230 732\n",
" Yes 443 139 582\n",
" Sum 945 369 1314"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"global <- table(data$Smoker,data$Status)\n",
"addmargins(global)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nous avons un tableau de fréquence décrivant le nombre de femmes vivantes/décedées selon leur tabagisme.\n",
"\n",
"Calculons maintenant le taux de mortalité."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" \n",
" Alive Dead\n",
" No 0.6857923 0.3142077\n",
" Yes 0.7611684 0.2388316"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mortality <- prop.table(global, margin=1)\n",
"mortality"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Le taux de mortalité des fumeuses est de 31% et celui des non fumeuses de 24%. Ce résultat est surprenant car le tabagisme est un facteur de risque pour de nombreuses maladies cardio-vasculaires et respiratoires.\n",
"\n",
"### Représentation graphique"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Smoker Alive Dead Mortality_rate\n",
"1 1 443 139 0.3142077\n",
"2 0 502 230 0.2388316\n"
]
},
{
"data": {
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3msu8dhysm1vfe5viV+uSQhJMABQgIc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\ncICQAAcICXCAkAAH/h8d0pN87ss1HAAAAABJRU5ErkJggg==",
"text/plain": [
"Plot with title “Histogram of data_exo1$Mortality_rate”"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Smoker <- c(1,0)\n",
"Alive <- c(global[2,1],global[1,1])\n",
"Dead <- c(global[2,2], global[1,2])\n",
"Mortality_rate <- c(mortality[1,2], mortality[2,2])\n",
"\n",
"data_exo1 <- data.frame(Smoker, Alive, Dead, Mortality_rate)\n",
"print(data_exo1)\n",
"\n",
"#ggplot(xdata_exo1, aes(x=Smoker, y=Mortality_rate)) + geom_point(alpha=.3, size=3) + theme_bw()\n",
"plot (x=data_exo1$Smoker, y=data_exo1$Mortality_rate, ylim=c(0,0.5), type='h')\n",
"#mortality_smoking <- c(smoker, no_smoker)\n",
"#mortality_smoking\n",
"#bp <- barplot(mortality_smoking, ylim=c(0,0.5))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"ename": "ERROR",
"evalue": "Error in ggplot(data = mortality_smoking): could not find function \"ggplot\"\n",
"output_type": "error",
"traceback": [
"Error in ggplot(data = mortality_smoking): could not find function \"ggplot\"\nTraceback:\n"
]
}
],
"source": [
"p<-ggplot(data=mortality_smoking) +\n",
" geom_bar(stat=\"identity\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"ename": "ERROR",
"evalue": "Error in xy.coords(x, y, xlabel, ylabel, log): argument \"x\" is missing, with no default\n",
"output_type": "error",
"traceback": [
"Error in xy.coords(x, y, xlabel, ylabel, log): argument \"x\" is missing, with no default\nTraceback:\n",
"1. plot(data = mortality_smoking)",
"2. plot.default(data = mortality_smoking)",
"3. xy.coords(x, y, xlabel, ylabel, log)"
]
}
],
"source": [
"plot(data=mortality_smoking)"
] ]
}, },
{ {
......
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