library(rio)
library(DescTools)
library(e1071)
data=import("state_democracy_final.xlsx")
names(data)
## [1] "Country" "Year"
## [3] "Rank" "Total"
## [5] "C1: Security Apparatus" "C2: Factionalized Elites"
## [7] "C3: Group Grievance" "E1: Economy"
## [9] "E2: Economic Inequality" "E3: Human Flight and Brain Drain"
## [11] "P1: State Legitimacy" "P2: Public Services"
## [13] "P3: Human Rights" "S1: Demographic Pressures"
## [15] "S2: Refugees and IDPs" "X1: External Intervention"
## [17] "Democracy_Score" "Type"
str(data)
## 'data.frame': 164 obs. of 18 variables:
## $ Country : chr "AFGHANISTAN" "ALBANIA" "ALGERIA" "ANGOLA" ...
## $ Year : num 2021 2021 2021 2021 2021 ...
## $ Rank : chr "9th" "119th" "74th" "34th" ...
## $ Total : num 102.1 59 73.6 89 50.1 ...
## $ C1: Security Apparatus : num 10 4.8 6 7.2 4.9 5.7 2.7 1.6 6.4 5.9 ...
## $ C2: Factionalized Elites : num 8.6 6.2 7.5 7.2 2.8 7 1.7 3.2 7.9 7.6 ...
## $ C3: Group Grievance : num 7.2 4.1 7.2 8.1 3.8 5.3 3.1 3.9 6.1 9.6 ...
## $ E1: Economy : num 9.2 6.4 6.8 8.4 7.1 6.6 1.6 1.8 4.7 4.1 ...
## $ E2: Economic Inequality : num 8.1 2.9 5.6 8.9 4.9 3.6 1.8 2.3 5.1 5.3 ...
## $ E3: Human Flight and Brain Drain: num 7 8.3 5.5 6 3 6.8 0.5 1.6 4.3 3 ...
## $ P1: State Legitimacy : num 8.7 5.5 7.8 8.2 4 6.9 0.5 0.6 9.1 8 ...
## $ P2: Public Services : num 9.8 4.4 5.6 9.3 4.8 3.9 2.8 2.3 5.5 3.5 ...
## $ P3: Human Rights : num 7.4 3.6 6.3 6.2 3.3 6 1.7 0.5 7.7 8.6 ...
## $ S1: Demographic Pressures : num 9 4.1 4.8 9 5.3 4.4 2.9 3.4 4.2 4.1 ...
## $ S2: Refugees and IDPs : num 8.8 2.6 6.8 5.9 1.9 6.6 2 4.4 6.9 1.7 ...
## $ X1: External Intervention : num 8.3 6.1 3.7 4.6 4.3 7 0.5 0.5 7.2 5.3 ...
## $ Democracy_Score : num 2.85 6.08 3.77 3.66 6.95 5.35 8.96 8.16 2.68 2.49 ...
## $ Type : chr "Authoritarian regime" "Flawed democracy" "Authoritarian regime" "Authoritarian regime" ...
#Ejercicios
Mean(data$`P3: Human Rights`)
## [1] 5.436585
Mean(data$`P1: State Legitimacy`)
## [1] 5.805488
sd(data$`P1: State Legitimacy`)
## [1] 2.851246
sd(data$`P3: Human Rights`)
## [1] 2.617099
var(data$`P1: State Legitimacy`)
## [1] 8.129602
var(data$`P3: Human Rights`)
## [1] 6.849205
boxplot(data$`P3: Human Rights`~data$`P1: State Legitimacy`)
boxplot(data$`P1: State Legitimacy`)
#Respuesta: De acuerdo con los resultados obtenidos, se observa que la desviación estándar de la variable Derechos Humanos resulta 2.62 aproximadamente y su varianza resulta 6.85. Por otro lado, se observa que la desviación estándar de la variable de Legitimidad estatal es 2.85 aproximadamente y su varianza resulta 8.3 aproximadamente. Por lo tanto, se concluye que los puntajes que presentaron los países estudiados respecto a derechos humanos están menos dispersos respecto a la media que en el caso de los puntajes sobre la legitimidad estatal, pues 2.62 es menos que 2.85.
skewness(data$`P3: Human Rights`) #Asimetría
## [1] -0.3428334
kurtosis(data$`P3: Human Rights`) #Curtosis
## [1] -0.9942446
skewness(data$`P1: State Legitimacy`) #Asimetría
## [1] -0.5017317
kurtosis(data$`P1: State Legitimacy`) #Curtosis
## [1] -0.9074828
#A partir de los datos obtenidos, se observa que la asimetría de las variables Legitimidad del Estado y Derechos Humanos son negativas: sesgadas a la izquierda. Por lo tanto, hay una mayor cantidad de países que presentan riesgos en torno a la legitmidad y respeto por los derechos humanos. Hay ciertos países que presentan bajos niveles de riesgo en estas dos categorías. Ello implica que la media se vea alterada y no sea representativa.
#En ambos casos la curtosis en ambos casos es negativa. Ello implica que la distribución será de tipo platicúrtica. Por lo tanto, los indicadores de riesgo para la fortaleza del Estados respecto a estas dos variables son dispersos, no están concentrados alrededor de la moda.
# **Ejercicio 3**
#Trabajamos con la variable Democracy score
table(data$Democracy_Score) #frecuencias
##
## 1.08 1.13 1.32 1.43 1.55 1.72 1.77 1.92 1.94 1.95 2.08 2.12 2.14 2.15 2.2 2.27
## 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1
## 2.49 2.54 2.59 2.63 2.68 2.7 2.71 2.76 2.77 2.8 2.84 2.85 2.93 2.94 3 3.04
## 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## 3.08 3.09 3.1 3.11 3.14 3.16 3.24 3.29 3.31 3.38 3.51 3.54 3.6 3.62 3.66 3.73
## 2 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1
## 3.77 3.8 3.83 3.92 3.93 4.1 4.16 4.21 4.22 4.31 4.48 4.49 4.58 4.84 4.86 4.94
## 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1
## 4.97 5.04 5.05 5.08 5.1 5.22 5.31 5.32 5.35 5.36 5.67 5.7 5.71 5.72 5.74 5.77
## 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## 5.78 5.81 5.89 5.9 5.99 6.01 6.03 6.04 6.07 6.08 6.1 6.13 6.14 6.18 6.22 6.3
## 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2
## 6.32 6.4 6.48 6.5 6.52 6.53 6.56 6.59 6.61 6.71 6.82 6.85 6.92 6.95 6.97 7.04
## 1 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1
## 7.05 7.06 7.13 7.16 7.18 7.19 7.24 7.39 7.51 7.54 7.56 7.62 7.65 7.67 7.68 7.74
## 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1
## 7.84 7.9 7.92 7.99 8.01 8.12 8.13 8.14 8.16 8.28 8.54 8.61 8.67 8.68 8.83 8.96
## 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2
## 9.05 9.15 9.2 9.24 9.25 9.26 9.37 9.81
## 1 1 1 1 1 1 1 1
class(data$Democracy_Score) #Exploramos el formato de la variable
## [1] "numeric"
Mode(data$Democracy_Score) #este comando nos permitirá calcular la moda
## [1] 1.95 3.08 3.10 3.62 4.86 6.30 6.50 6.56 7.13 7.84 8.16 8.96
## attr(,"freq")
## [1] 2
mean(data$Democracy_Score)
## [1] 5.354451
prop.table(table(data$Democracy_Score))*100 #frecuencia relativa
##
## 1.08 1.13 1.32 1.43 1.55 1.72 1.77 1.92
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 1.94 1.95 2.08 2.12 2.14 2.15 2.2 2.27
## 0.6097561 1.2195122 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 2.49 2.54 2.59 2.63 2.68 2.7 2.71 2.76
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 2.77 2.8 2.84 2.85 2.93 2.94 3 3.04
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 3.08 3.09 3.1 3.11 3.14 3.16 3.24 3.29
## 1.2195122 0.6097561 1.2195122 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 3.31 3.38 3.51 3.54 3.6 3.62 3.66 3.73
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 1.2195122 0.6097561 0.6097561
## 3.77 3.8 3.83 3.92 3.93 4.1 4.16 4.21
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 4.22 4.31 4.48 4.49 4.58 4.84 4.86 4.94
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 1.2195122 0.6097561
## 4.97 5.04 5.05 5.08 5.1 5.22 5.31 5.32
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 5.35 5.36 5.67 5.7 5.71 5.72 5.74 5.77
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 5.78 5.81 5.89 5.9 5.99 6.01 6.03 6.04
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 6.07 6.08 6.1 6.13 6.14 6.18 6.22 6.3
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 1.2195122
## 6.32 6.4 6.48 6.5 6.52 6.53 6.56 6.59
## 0.6097561 0.6097561 0.6097561 1.2195122 0.6097561 0.6097561 1.2195122 0.6097561
## 6.61 6.71 6.82 6.85 6.92 6.95 6.97 7.04
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 7.05 7.06 7.13 7.16 7.18 7.19 7.24 7.39
## 0.6097561 0.6097561 1.2195122 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 7.51 7.54 7.56 7.62 7.65 7.67 7.68 7.74
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 7.84 7.9 7.92 7.99 8.01 8.12 8.13 8.14
## 1.2195122 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
## 8.16 8.28 8.54 8.61 8.67 8.68 8.83 8.96
## 1.2195122 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 1.2195122
## 9.05 9.15 9.2 9.24 9.25 9.26 9.37 9.81
## 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561 0.6097561
hist(data$Democracy_Score, col="black")
