punto 2.1 y 2.2

A = (24/-8+7)/(9-6*(2))
A= round(A,1)
print (A)
## [1] -1.3
B = 2^3*(-7)+4-((1/3)+(1/2))
B = round(B,1)
print (B)
## [1] -52.8
C = (sqrt(16)+5*4-3^-2)/(3*(4-8)+1)
C = round(C,1)
print (C)
## [1] -2.2
D = 1/2*((5/4-1/2)*13/4-sqrt(7)+8/(2/1-1/5)-3^2)
D = round(D,1)
print (D)
## [1] -2.4
E = 2*sin(pi/3)+5*cos(pi/4)-tan(pi/6)/4
E = round(E,1)
print (E)
## [1] 5.1
F = 4*log2(5)-3*log(7,base=3)+1/3*log(8)^3
F = round(F,1)
print (F)
## [1] 7

punto 2.3

GC = c(14.2, 8.0, 9.2, 12.1, 8.7, 11.6, 11.0, 12.5, 10.0, 9.0, 8.5, 13.1, 12.9, 8.4, 11.2, 9.8, 12.4, 11.0, 13.0, 8.6)
NP = c(11, 10, 6, 9, 10, 12, 14, 10, 8, 9, 11, 12, 11, 11, 15, 13, 12, 12, 8, 13)
ID = c(1:20)

#media
prom_GC = mean(GC)
print(prom_GC)
## [1] 10.76
prom_NP = mean(NP)
print(prom_NP)
## [1] 10.85
#moda
moda_GC = mode(GC)
print (moda_GC)
## [1] "numeric"
moda_NP = mode(NP)
print (moda_NP)
## [1] "numeric"
#mediana
acom_GC = sort(GC)
mediana_GC = median(acom_GC)
print (acom_GC)
##  [1]  8.0  8.4  8.5  8.6  8.7  9.0  9.2  9.8 10.0 11.0 11.0 11.2 11.6 12.1 12.4
## [16] 12.5 12.9 13.0 13.1 14.2
acom_NP = sort(NP)
mediana_NP = median(acom_NP)
print (acom_NP)
##  [1]  6  8  8  9  9 10 10 10 11 11 11 11 12 12 12 12 13 13 14 15
#desviación estandar 
desviacion_GC = sd(GC)
d_1 = round(desviacion_GC, 2)
print (d_1)
## [1] 1.91
desviacion_NP = sd(NP)
d_2 = round(desviacion_NP, 2)
print (d_2)
## [1] 2.18
#varianza 
varianza_GC = var(GC)
v_1 = round(varianza_GC, 2)
print(v_1)
## [1] 3.67
varianza_NP = var(NP)
v_2 = round(varianza_NP, 2)
print(v_2)
## [1] 4.77
#cuartiles
cuartiles_GC = quantile(GC)
print(cuartiles_GC, 2)
##   0%  25%  50%  75% 100% 
##  8.0  8.9 11.0 12.4 14.2
cuartiles_NP = quantile(NP)
print(cuartiles_NP, 2)
##   0%  25%  50%  75% 100% 
##  6.0  9.8 11.0 12.0 15.0
#graficas

barplot(GC, names.arg = ID, col = "blue", xlab = "ID", ylab = "GC", main = "ID vs GC")
mtext("Gráfica", side = 3, line = 3, cex = 1.2, font = 2)

barplot(NP, names.arg = ID, col = "green", xlab = "ID", ylab = "NP", main = "ID vs NP")

mtext("Gráfica", side = 3, line = 3, cex = 1.2, font = 2)

punto 2.4

PHP = c(14.0, 24.7, 16.4, 26.0, 25.7, 24.6)
TMI =c(8.8, 10.2, 8.0, 9.1, 8.2, 9.4)

#media
prom_PHP = mean(PHP)
print(prom_PHP)
## [1] 21.9
prom_TMI = mean(TMI)
print(prom_TMI)
## [1] 8.95
#moda 
moda_PHP = mode(PHP)

moda_TMI = mode(TMI)

#mediana
acom_PHP = sort(PHP)
mediana_PHP = median(acom_PHP)
print(mediana_PHP)
## [1] 24.65
acom_TMI = sort(TMI)
mediana_TMI = median(acom_TMI)
print(mediana_TMI)
## [1] 8.95
#desviación estandar
desviacion_PHP = sd(PHP)
de_1 = round(desviacion_PHP, 2)
print(de_1)
## [1] 5.27
desviacion_TMI = sd(TMI)
de_2 = round(desviacion_TMI, 2)
print(de_2)
## [1] 0.81
INDICA = c("Central", "Norte", "Sur", "Oriente", "Oeste", "Rural")
barplot(PHP, names.arg = INDICA, col = "Red", xlab = "Indicador", ylab = "PHP", main = "Zona vs PHP")
mtext("Gráfica", side = 3, line = 3, cex = 1.2, font = 2)

barplot(TMI, names.arg = INDICA, col = "Orange", xlab = "Indicador", ylab = "TMI", main = "Zona vs TMI")
mtext("Gráfica", side = 3, line = 3, cex = 1.2, font = 2)

Punto 2.5

datos = matrix(c(8, 12, 14, 9, 5, 10), nrow = 2, byrow = FALSE)
rownames(datos) = c("Masculino", "Femenino")
colnames(datos) = c("Casado", "Soltero", "Otro")

tabla = as.data.frame(datos)

rownames(tabla) = c("Masculino", "Femenino")
colnames(tabla) = c("Casado", "Soltero", "Otro")

print(tabla)
##           Casado Soltero Otro
## Masculino      8      14    5
## Femenino      12       9   10
datos = matrix(c(8, 12, 14, 9, 5, 10), nrow = 2, byrow = FALSE)

rownames(datos) <- c("Masculino", "Femenino")
colnames(datos) <- c("Casado", "Soltero", "Otro")

#Crear data frame
df <- as.data.frame(datos)

print(df)
##           Casado Soltero Otro
## Masculino      8      14    5
## Femenino      12       9   10
#Gráfico de barras apiladas
barplot(as.matrix(df), beside = TRUE, legend.text = FALSE, col = c("red", "yellow"),
        main = "Estado Conyugal por Género (Barras Apiladas)", xlab = "Género", ylab = "Frecuencia")

#Gráfico de barras agrupadas
barplot(as.matrix(df), beside = FALSE, col = c("purple", "pink"),
        main = "Estado Conyugal por Género (Barras Agrupadas)", xlab = "Género", ylab = "Frecuencia")