diff --git a/module3/exo3/exercice_fr.ipynb b/module3/exo3/exercice_fr.ipynb index 7145f60ccdc6c5decb34883c80d36921a6916c61..393c804ea7df15168ed56ff97c5e3ec49a4ff611 100644 --- a/module3/exo3/exercice_fr.ipynb +++ b/module3/exo3/exercice_fr.ipynb @@ -242,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -256,9 +256,9 @@ }, { "data": { - "image/png": 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80ON+8RUiIQUhz+0JhjhGQGf2hMM0Iygz80phkhmcEfGtOMkMzgD41pRkhm8IfG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\nQgIcICTAAUICHCAkwAFCAhwgJMABQgIcICTAAUICHCAkwAFCAhw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"text/plain": [ - "Plot with title “Histogram of data_exo1$Mortality_rate”" + "plot without title" ] }, "metadata": {}, @@ -267,7 +267,7 @@ ], "source": [ "Smoker <- c(1,0)\n", - "Alive <- c(global[2,1],global[1,1])\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", @@ -281,44 +281,276 @@ "#bp <- barplot(mortality_smoking, ylim=c(0,0.5))" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Question 2\n", + "### Enoncé\n", + "*Reprenez la question 1 (effectifs et taux de mortalité) en rajoutant une nouvelle catégorie liée à la classe d'âge. On considérera par exemple les classes suivantes : 18-34 ans, 34-54 ans, 55-64 ans, plus de 65 ans. En quoi ce résultat est-il surprenant ? Arrivez-vous à expliquer ce paradoxe ? De même, vous pourrez proposer une représentation graphique de ces données pour étayer vos explications.*\n", + "\n", + "### Calcul de l'effectif et du taux de mortalité selon le groupe d'âge\n", + "#### Groupe des fumeuses\n", + "Nous étudions dans un premier temps le taux de mortalité des fumeuses selon leur groupe d'âge." + ] + }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 39, "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" - ] + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
AliveDeadSum
[18,34)174 5179
[34,54)198 41239
[54,64) 64 51115
[64,100] 7 42 49
Sum443139582
\n" + ], + "text/latex": [ + "\\begin{tabular}{r|lll}\n", + " & Alive & Dead & Sum\\\\\n", + "\\hline\n", + "\t{[}18,34) & 174 & 5 & 179\\\\\n", + "\t{[}34,54) & 198 & 41 & 239\\\\\n", + "\t{[}54,64) & 64 & 51 & 115\\\\\n", + "\t{[}64,100{]} & 7 & 42 & 49\\\\\n", + "\tSum & 443 & 139 & 582\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "| | Alive | Dead | Sum | \n", + "|---|---|---|---|---|\n", + "| [18,34) | 174 | 5 | 179 | \n", + "| [34,54) | 198 | 41 | 239 | \n", + "| [54,64) | 64 | 51 | 115 | \n", + "| [64,100] | 7 | 42 | 49 | \n", + "| Sum | 443 | 139 | 582 | \n", + "\n", + "\n" + ], + "text/plain": [ + " \n", + "smoker_age_group Alive Dead Sum\n", + " [18,34) 174 5 179\n", + " [34,54) 198 41 239\n", + " [54,64) 64 51 115\n", + " [64,100] 7 42 49\n", + " Sum 443 139 582" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "p<-ggplot(data=mortality_smoking) +\n", - " geom_bar(stat=\"identity\")" + "smoker_age <-subset(data, Smoker==\"Yes\", select=c(Smoker, Status, Age))\n", + "smoker_age_group <- cut(smoker_age$Age,c(18,34,54,64,100),right=FALSE, include.lowest=TRUE)\n", + "smoker_age_prop <- table(smoker_age_group,smoker_age$Status)\n", + "addmargins(smoker_age_prop)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 40, "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)" - ] + "data": { + "text/plain": [ + " \n", + "smoker_age_group Alive Dead\n", + " [18,34) 0.97206704 0.02793296\n", + " [34,54) 0.82845188 0.17154812\n", + " [54,64) 0.55652174 0.44347826\n", + " [64,100] 0.14285714 0.85714286" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mortality_smoker <-prop.table(smoker_age_prop,margin=1)\n", + "mortality_smoker" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Groupe des non fumeuses\n", + "Nous étudions dans un second temps le taux de mortalité des non fumeuses selon leur groupe d'âge." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
AliveDeadSum
[18,34)213 6219
[34,54)180 19199
[54,64) 80 39119
[64,100] 29166195
Sum502230732
\n" + ], + "text/latex": [ + "\\begin{tabular}{r|lll}\n", + " & Alive & Dead & Sum\\\\\n", + "\\hline\n", + "\t{[}18,34) & 213 & 6 & 219\\\\\n", + "\t{[}34,54) & 180 & 19 & 199\\\\\n", + "\t{[}54,64) & 80 & 39 & 119\\\\\n", + "\t{[}64,100{]} & 29 & 166 & 195\\\\\n", + "\tSum & 502 & 230 & 732\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "| | Alive | Dead | Sum | \n", + "|---|---|---|---|---|\n", + "| [18,34) | 213 | 6 | 219 | \n", + "| [34,54) | 180 | 19 | 199 | \n", + "| [54,64) | 80 | 39 | 119 | \n", + "| [64,100] | 29 | 166 | 195 | \n", + "| Sum | 502 | 230 | 732 | \n", + "\n", + "\n" + ], + "text/plain": [ + " \n", + "no_smoker_age_group Alive Dead Sum\n", + " [18,34) 213 6 219\n", + " [34,54) 180 19 199\n", + " [54,64) 80 39 119\n", + " [64,100] 29 166 195\n", + " Sum 502 230 732" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "no_smoker_age <-subset(data, Smoker==\"No\", select=c(Smoker, Status, Age))\n", + "no_smoker_age_group <- cut(no_smoker_age$Age,c(18,34,54,64,100),right=FALSE, include.lowest=TRUE)\n", + "no_smoker_age_prop <- table(no_smoker_age_group,no_smoker_age$Status)\n", + "addmargins(no_smoker_age_prop)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + " \n", + "no_smoker_age_group Alive Dead\n", + " [18,34) 0.97260274 0.02739726\n", + " [34,54) 0.90452261 0.09547739\n", + " [54,64) 0.67226891 0.32773109\n", + " [64,100] 0.14871795 0.85128205" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mortality_no_smoker <-prop.table(no_smoker_age_prop,margin=1)\n", + "mortality_no_smoker" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comparons maintenant les taux de mortalité des fumeuses et non fumeuses selon leur groupe d'âge." + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "$Fumeuses\n", + " \n", + "smoker_age_group Alive Dead\n", + " [18,34) 0.97206704 0.02793296\n", + " [34,54) 0.82845188 0.17154812\n", + " [54,64) 0.55652174 0.44347826\n", + " [64,100] 0.14285714 0.85714286\n", + "\n", + "$`Non fumeuses`\n", + " \n", + "no_smoker_age_group Alive Dead\n", + " [18,34) 0.97260274 0.02739726\n", + " [34,54) 0.90452261 0.09547739\n", + " [54,64) 0.67226891 0.32773109\n", + " [64,100] 0.14871795 0.85128205\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mortality_smoking_age <- list(mortality_smoker,mortality_no_smoker)\n", + "names(mortality_smoking_age) <-c (\"Fumeuses\",\"Non fumeuses\")\n", + "mortality_smoking_age" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous remarquons que le taux de mortalité est supérieur pour les fumeuses que pour les non fumeuses pour chaque groupe d'âge. Ces résultats sont surprenants car ils sont en contradiction avec ceux de la première question (sans prendre en compte les groupes d'âge)." + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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523K3O/WUNI7REhpUlIOXdE3z1pbiCk9oiQ0iSkfpfG3t9s5hNSO0RIaRLSDZEH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\n", + "text/plain": [ + "plot without title" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "plot(data=mortality_smoking)" + "smoker_mortality <- c(mortality_smoker[1,2],mortality_smoker[2,2],mortality_smoker[3,2],mortality_smoker[4,2])\n", + "no_smoker_mortality <- c(mortality_no_smoker[1,2],mortality_no_smoker[2,2],mortality_no_smoker[3,2],mortality_no_smoker[4,2])\n", + "group_age <- c(\"[18-34)\",\"[34-54)\",\" [54-64)\",\"[>64]\")\n", + "mortality_age <- c(smoker_mortality,no_smoker_mortality)\n", + "mortality_age <- matrix(mortality_age,nc=4,nr=2,byrow=T)\n", + "colnames(mortality_age)=group_age\n", + "barplot(mortality_age,beside=T,xlab=\"Groupe d'âge\", ylab=\"Taux de Mortalité\", legend.text=c(\"Fumeuses\", \"Non fumeuses\"), ylim=c(0,1.1))" ] }, {