diff --git a/module3/exo3/exercice_fr.ipynb b/module3/exo3/exercice_fr.ipynb
index 393c804ea7df15168ed56ff97c5e3ec49a4ff611..ec1dd96a6a1fcc75faa970871fd37cb57cdccf5c 100644
--- a/module3/exo3/exercice_fr.ipynb
+++ b/module3/exo3/exercice_fr.ipynb
@@ -242,7 +242,7 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 58,
"metadata": {},
"outputs": [
{
@@ -295,61 +295,8 @@
]
},
{
- "cell_type": "code",
- "execution_count": 39,
+ "cell_type": "markdown",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "
\n",
- " | Alive | Dead | Sum |
\n",
- "\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",
- "\t| Sum | 443 | 139 | 582 |
\n",
- "\n",
- "
\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": [
"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",
@@ -524,7 +471,9 @@
"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)."
+ "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).\n",
+ "\n",
+ "Représentons ces résultats dans un graphique."
]
},
{
@@ -553,6 +502,285 @@
"barplot(mortality_age,beside=T,xlab=\"Groupe d'âge\", ylab=\"Taux de Mortalité\", legend.text=c(\"Fumeuses\", \"Non fumeuses\"), ylim=c(0,1.1))"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "En étudiant les résultats des tableaux de fréquence nous remarquons que l'effectif des personnes âgées est plus important chez les non fumeuses que les fumeuses : il y a plus de personnes âgées non fumeuses que fumeuses. Cette différence peut expliquer les résultats contradictoires que nous observons.\n",
+ "\n",
+ "## Question 3\n",
+ "### Enoncé\n",
+ "*Afin d'éviter un biais induit par des regroupements en tranches d'âges arbitraires et non régulières, il est envisageable d'essayer de réaliser une régression logistique. Si on introduit une variable Death valant 1 ou 0 pour indiquer si l'individu est décédé durant la période de 20 ans, on peut étudier le modèle Death ~ Age pour étudier la probabilité de décès en fonction de l'âge selon que l'on considère le groupe des fumeuses ou des non fumeuses. Ces régressions vous permettent-elles de conclure sur la nocivité du tabagisme ? Vous pourrez proposer une représentation graphique de ces régressions (en n'omettant pas les régions de confiance).*\n",
+ "\n",
+ "### Introduction de la nouvelle variable"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "| Smoker | Status | Age | Death |
\n",
+ "\n",
+ "\t| Yes | Alive | 21.0 | 0 |
\n",
+ "\t| Yes | Alive | 19.3 | 0 |
\n",
+ "\t| No | Dead | 57.5 | 1 |
\n",
+ "\t| No | Alive | 47.1 | 0 |
\n",
+ "\t| Yes | Alive | 81.4 | 0 |
\n",
+ "\t| No | Alive | 36.8 | 0 |
\n",
+ "\n",
+ "
\n"
+ ],
+ "text/latex": [
+ "\\begin{tabular}{r|llll}\n",
+ " Smoker & Status & Age & Death\\\\\n",
+ "\\hline\n",
+ "\t Yes & Alive & 21.0 & 0 \\\\\n",
+ "\t Yes & Alive & 19.3 & 0 \\\\\n",
+ "\t No & Dead & 57.5 & 1 \\\\\n",
+ "\t No & Alive & 47.1 & 0 \\\\\n",
+ "\t Yes & Alive & 81.4 & 0 \\\\\n",
+ "\t No & Alive & 36.8 & 0 \\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/markdown": [
+ "\n",
+ "Smoker | Status | Age | Death | \n",
+ "|---|---|---|---|---|---|\n",
+ "| Yes | Alive | 21.0 | 0 | \n",
+ "| Yes | Alive | 19.3 | 0 | \n",
+ "| No | Dead | 57.5 | 1 | \n",
+ "| No | Alive | 47.1 | 0 | \n",
+ "| Yes | Alive | 81.4 | 0 | \n",
+ "| No | Alive | 36.8 | 0 | \n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ " Smoker Status Age Death\n",
+ "1 Yes Alive 21.0 0 \n",
+ "2 Yes Alive 19.3 0 \n",
+ "3 No Dead 57.5 1 \n",
+ "4 No Alive 47.1 0 \n",
+ "5 Yes Alive 81.4 0 \n",
+ "6 No Alive 36.8 0 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "data$Death <- ifelse(data$Status=='Dead',1,0)\n",
+ "head(data)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Groupe des fumeuses"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "Call:\n",
+ "glm(formula = Death ~ Age, family = binomial(logit), data = death_smoker)\n",
+ "\n",
+ "Deviance Residuals: \n",
+ " Min 1Q Median 3Q Max \n",
+ "-2.0745 -0.6464 -0.3756 -0.2013 2.6560 \n",
+ "\n",
+ "Coefficients:\n",
+ " Estimate Std. Error z value Pr(>|z|) \n",
+ "(Intercept) -5.508106 0.466221 -11.81 <2e-16 ***\n",
+ "Age 0.088977 0.008721 10.20 <2e-16 ***\n",
+ "---\n",
+ "Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
+ "\n",
+ "(Dispersion parameter for binomial family taken to be 1)\n",
+ "\n",
+ " Null deviance: 639.89 on 581 degrees of freedom\n",
+ "Residual deviance: 480.41 on 580 degrees of freedom\n",
+ "AIC: 484.41\n",
+ "\n",
+ "Number of Fisher Scoring iterations: 5\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "death_smoker <- subset(data,Smoker==\"Yes\")\n",
+ "reg_smoker <- glm(data=death_smoker, Death ~ Age,family=binomial(logit))\n",
+ "summary(reg_smoker)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Groupe des non fumeuses"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "Call:\n",
+ "glm(formula = Death ~ Age, family = binomial(logit), data = death_no_smoker)\n",
+ "\n",
+ "Deviance Residuals: \n",
+ " Min 1Q Median 3Q Max \n",
+ "-2.4019 -0.5179 -0.2003 0.4728 3.0457 \n",
+ "\n",
+ "Coefficients:\n",
+ " Estimate Std. Error z value Pr(>|z|) \n",
+ "(Intercept) -6.795507 0.479430 -14.17 <2e-16 ***\n",
+ "Age 0.107275 0.007806 13.74 <2e-16 ***\n",
+ "---\n",
+ "Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
+ "\n",
+ "(Dispersion parameter for binomial family taken to be 1)\n",
+ "\n",
+ " Null deviance: 911.23 on 731 degrees of freedom\n",
+ "Residual deviance: 519.08 on 730 degrees of freedom\n",
+ "AIC: 523.08\n",
+ "\n",
+ "Number of Fisher Scoring iterations: 6\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "death_no_smoker <- subset(data,Smoker==\"No\")\n",
+ "reg_no_smoker <- glm(data=death_no_smoker, Death ~ Age,family=binomial(logit))\n",
+ "summary(reg_no_smoker)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 64,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "library(ggplot2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {},
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "NULL"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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TSbXeWcqRKFObmdty1sSIwO6rtHeINgBwAA/MrXqe5QTfybe6d09OlGzpye1XPr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\nurqJEydef/31fa8tk3/W27ZtU6lU8s9aEASn0/n000+//vrrD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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "ggplot(death_no_smoker, aes(x = Age, y = Death)) +\n",
+ "geom_point() + # Plot the raw data points\n",
+ "stat_smooth(method = \"glm\", method.args = list(family = \"binomial\"),\n",
+ "formula = y ~ x, # Logistic regression formula\n",
+ "geom = \"smooth\") # Add a smoothed line)\n",
+ "labs(x = \"Age\", y = \"Probability of Death with smoker people\",\n",
+ "title = \"Logistic Regression of Death by Age\") +\n",
+ "theme_minimal()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 71,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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57pdIWTGil3B3W7ujyN1358RastfDWGsndTFzZiBPN42Pr1zG/FPfjgNXvI559P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zwgQtTKVSCQQCl1/YT61W07/HLkyn0+n1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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# création d'un ggplot vide à remplir avec les deux ggplot (fumeuses, non fumeuses)\n",
+ "p <- ggplot() +\n",
+ "labs(x = \"Age\", y = \"Death\",\n",
+ "title = \"Régression logistique Death/Age selon le tabagisme\") +\n",
+ "theme_minimal()\n",
+ "\n",
+ "# ajout des infos sur le tabagisme pour différencier les deux graphiques\n",
+ "death_smoker$tabac <- 'Smoker'\n",
+ "death_no_smoker$tabac <- 'Non-Smoker'\n",
+ "\n",
+ "# ajout des fumeuses\n",
+ "p <- p + geom_point(data = death_smoker, aes(x = Age, y = Death, color = tabac)) +\n",
+ "stat_smooth(data = death_smoker, aes(x = Age, y = Death, color = tabac),\n",
+ "method = \"glm\", method.args = list(family = \"binomial\"),\n",
+ "formula = y ~ x, geom = \"smooth\")\n",
+ "\n",
+ "# ajout des non fumeuses\n",
+ "p <- p + geom_point(data = death_no_smoker, aes(x = Age, y = Death, color = tabac)) +\n",
+ "stat_smooth(data = death_no_smoker, aes(x = Age, y = Death, color = tabac),\n",
+ "method = \"glm\", method.args = list(family = \"binomial\"),\n",
+ "formula = y ~ x, geom = \"smooth\")\n",
+ "\n",
+ "# customisation des légendes\n",
+ "p <- p + scale_color_manual(name = \"Tabagisme\",\n",
+ "values = c(\"Smoker\" = \"red\", \"Non-Smoker\" = \"blue\"),\n",
+ "labels = c(\"Smoker\" = \"Smoker\", \"Non-Smoker\" = \"Non-Smoker\"))\n",
+ "# Print the plot\n",
+ "print(p)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Nous remarquons que le risque est plus important pour les fumeuses que les non fumeuses pour les femmes âgées de moins de 70 ans. Pour les femmes plus âgées la tendance est inversée, néanmoins comme nous avons peu de données pour ces âges les résultats sont à prendre avec des pincettes."
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,