From 16461232e0874ba33ff80c4033e4247d8ce4623f Mon Sep 17 00:00:00 2001
From: 433835ee939dd34ba5afd7c0a68da139
 <433835ee939dd34ba5afd7c0a68da139@app-learninglab.inria.fr>
Date: Thu, 4 Sep 2025 14:02:23 +0000
Subject: [PATCH] Upload exo 1 module 4

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 module4/module4_exo1.Rmd | 56 ++++++++++++++++++++++++++++++++++++++++
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 create mode 100644 module4/module4_exo1.Rmd

diff --git a/module4/module4_exo1.Rmd b/module4/module4_exo1.Rmd
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+---
+title: "module4_exo1"
+author: "Dusfour-Castan Pauline @433835ee939dd34ba5afd7c0a68da139"
+output: pdf_document
+date: "2025-09-04"
+---
+
+
+# Informations sur la version de R et les packages utlisés
+
+
+```{r}
+library(ggplot2)
+library(readr)
+sessionInfo()
+```
+
+
+# Importation des données et analyses
+
+```{r}
+data = read_csv("~/data_shuttle.csv")
+data
+```
+
+
+```{r}
+plot(data=data, Malfunction/Count ~ Temperature, ylim=c(0,1))
+```
+
+
+## Régression Logistique
+
+```{r}
+logistic_reg = glm(data=data, Malfunction/Count ~ Temperature, weights=Count,
+                   family=binomial(link='logit'))
+summary(logistic_reg)
+```
+
+
+## Prédire la probabilité de défaillance
+
+```{r}
+tempv = seq(from=30, to=90, by = .5)
+rmv <- predict(logistic_reg, list(Temperature=tempv), type="response")
+plot(tempv, rmv, type="l", ylim=c(0,1))
+points(data=data, Malfunction/Count ~ Temperature)
+```
+
+
+```{r, fig.height=3.3}
+ggplot(data, aes(y=Malfunction/Count, x=Temperature)) + 
+  geom_point(alpha=.2, size = 2, color="blue") +
+  geom_smooth(method = "glm", method.args = list(family = "binomial"), fullrange=T) +
+  xlim(30,90) + ylim(0,1) + theme_bw()
+```
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