database=read_excel("C:/Users/HP/Downloads/basepays.xls")
knitr::kable(head(database, 10), caption = "Aperçu des premières lignes de la base")| Pays | partPNBmond | PIBhab | PNBhab | Espér de vie | Taux Mort I | Pourc pop ur | Pourc analph | T Racc E Po | Nbre Téléph | Nbre Ordin | Nbre Voitur | Nbre Intern | nbrjourhab | celectrhab | tauxfertil | nbrlithop | nbrmedec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Albanie | 0.0096956 | 896.1765 | 810,00 | 72,00 | 25,00 | 40,00 | 16,50 | 76,00 | 31,00 | 3,00 | 27,00 | 0.23999999999999999 | 35.517452 | 851.39227 | 2.5 | 3.2 | 1.4 |
| Algérie | 0.1637053 | 1578.2333 | 1550,00 | 71,00 | 35,00 | 59,00 | 35,00 | 90,00 | 53,00 | 4,20 | 25,00 | 0.01 | 37.663101 | 565.86261 | 3.5 | 2.1 | 0.8 |
| Angola | 0.0165888 | 602.5806 | 380,00 | 47,00 | 124,00 | 33,00 | 41,00 | 32,00 | 6,00 | 0.80000000000000004 | 18,00 | 0 | 11.310478 | 63.90368 | 6.7 | 1.3 | 0.0 |
| Argentine | 1.0346809 | 8145.6557 | 8030,00 | 73,00 | 19,00 | 89,00 | 3,00 | 65,00 | 203,00 | 44,30 | 137,00 | 16,00 | 122.657578 | 1633.77441 | 2.6 | 3.3 | 2.7 |
| Arménie | 0.0061539 | 500.0000 | 460,00 | 74,00 | 15,00 | 69,00 | 2,00 | 99,00 | 157,00 | 4,20 | 0 | 1,85 | 22.606000 | 1140.78186 | 1.3 | 7.6 | 3.0 |
| Australie | 1.3806166 | 19038.0000 | 20640,00 | 79,00 | 5,00 | 85,00 | 3,00 | 99,00 | 512,00 | 411,60 | 488,00 | 400,00 | 293.250336 | 8307.00098 | 1.8 | 8.5 | 2.5 |
| Autriche | 0.7650952 | 26155.3086 | 26830,00 | 78,00 | 5,00 | 65,00 | 2,00 | 100,00 | 491,00 | 233,40 | 481,00 | 164,00 | 295.570160 | 6050.90576 | 1.3 | 9.2 | 2.8 |
| Azerbeidjan | 0.0135189 | 490.7500 | 480,00 | 71,00 | 17,00 | 57,00 | 3,00 | 97,00 | 89,00 | 7,00 | 36,00 | 0.23000000000000001 | 27.325000 | 1630.51794 | 2.0 | 9.7 | 3.8 |
| Bangladesh | 0.1573507 | 334.3931 | 350,00 | 59,00 | 73,00 | 23,00 | 60,00 | 84,00 | 3,00 | 3,00 | 1,00 | 0 | 9.179866 | 76.42000 | 3.1 | 0.3 | 0.2 |
| Bélarus | 0.0782828 | 2211.2745 | 2180,00 | 68,00 | 11,00 | 71,00 | 0.5 | 100,00 | 241,00 | 25,00 | 2,00 | 0.77000000000000002 | 174.266000 | 2606.54468 | 1.3 | 12.2 | 4.3 |
## [1] 132 18
## Pays partPNBmond PIBhab PNBhab
## Length:132 Min. : 0.000676 Min. : 104.2 Length:132
## Class :character 1st Qu.: 0.015790 1st Qu.: 396.1 Class :character
## Mode :character Median : 0.062789 Median : 1575.6 Mode :character
## Mean : 0.756402 Mean : 5864.9
## 3rd Qu.: 0.368381 3rd Qu.: 5305.3
## Max. :28.188596 Max. :37131.0
##
## Espér de vie Taux Mort I Pourc pop ur Pourc analph
## Length:132 Length:132 Length:132 Length:132
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## T Racc E Po Nbre Téléph Nbre Ordin Nbre Voitur
## Length:132 Length:132 Length:132 Length:132
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## Nbre Intern nbrjourhab celectrhab tauxfertil
## Length:132 Min. : 0.0835 Min. : 21.37 Min. :1.100
## Class :character 1st Qu.: 7.7619 1st Qu.: 420.25 1st Qu.:1.800
## Mode :character Median : 34.2571 Median : 1632.15 Median :2.850
## Mean : 99.8412 Mean : 2944.61 Mean :3.345
## 3rd Qu.:150.3765 3rd Qu.: 4124.21 3rd Qu.:4.825
## Max. :792.2675 Max. :23499.47 Max. :7.300
## NA's :24
## nbrlithop nbrmedec
## Min. : 0.100 Min. :0.000
## 1st Qu.: 1.300 1st Qu.:0.200
## Median : 2.300 Median :1.100
## Mean : 3.939 Mean :1.462
## 3rd Qu.: 5.650 3rd Qu.:2.575
## Max. :20.800 Max. :5.500
## NA's :5 NA's :2
datanum=database[,sapply(database,is.numeric)]
corelation=cor(datanum,use ="complete.obs",method = "pearson")
pairs(datanum)## $chisq
## [1] 571.8326
##
## $p.value
## [1] 1.326434e-107
##
## $df
## [1] 21
La p-value est très largement inférieure à 0.05, donc on rejette H0.
Cela signifie qu’il existe des corrélations significatives entre les variables.
Conclusion : On peux continuer avec une analyse factorielle, car elle est pertinente pour ces données.
## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = corelation)
## Overall MSA = 0.83
## MSA for each item =
## partPNBmond PIBhab nbrjourhab celectrhab tauxfertil nbrlithop
## 0.78 0.82 0.82 0.85 0.82 0.88
## nbrmedec
## 0.77
KMO global = 0.83 Très bonne adéquation
Les MSA individuels vont de 0.77 à 0.88. Tous sont au-dessus du seuil minimal de 0.60 donc aucune variable n’a besoin d’être exclue.