taller 331

**Punto 2

# Secuencia de artículos defectuosos y no defectuosos
secuencia <- c("N", "D", "D", "N", "N", "D", "N", "N", "N", "D", "N", "D", "D", "N", "D", "N", "N", "N", "D",
               "D", "N", "N", "D", "D", "N", "N", "N", "N", "N", "D", "D", "D", "N", "D", "D", "D", "N", "D",
               "N", "D", "N", "D", "D", "N", "N", "D", "D", "D", "D", "N")

# Realizar prueba de chi-cuadrado
resultado <- chisq.test(table(secuencia))
resultado

## 
##  Chi-squared test for given probabilities
## 
## data:  table(secuencia)
## X-squared = 0, df = 1, p-value = 1

**Punto 3

# Crear una matriz con los datos
datos <- matrix(c(470, 191, 42, 445, 171, 28, 257, 139, 17), nrow = 3, byrow = TRUE,
                dimnames = list(c("dia", "tarde", "noche"), c("alta", "moderada", "baja")))

# Realizar prueba de chi-cuadrado
resultado <- chisq.test(datos)
resultado

## 
##  Pearson's Chi-squared test
## 
## data:  datos
## X-squared = 9.4939, df = 4, p-value = 0.04987

**Punto 4

# Datos de notas
notas <- c(3.4, 2.8, 4.2, 2.1, 2.8, 2.4, 3.5, 4.2, 3.1, 4.1, 2.4, 3.4, 4.1, 4.0, 2.4, 4.1, 3.4, 4.4, 3.8,
           3.7, 2.2, 3.6, 2.3, 3.7, 2.8, 4.1, 2.3, 4.6, 4.6, 5.2, 2.4, 2.4, 2.7, 3.8, 4.6, 4.4, 4.2, 4.4,
           2.4, 3.3, 3.8, 2.9, 3.1, 2.7, 3.6, 3.8, 4.4, 3.9, 2.8, 3.7)

# Realizar prueba de Shapiro-Wilk
resultado <- shapiro.test(notas)
resultado

## 
##  Shapiro-Wilk normality test
## 
## data:  notas
## W = 0.95071, p-value = 0.03649

# Prueba t de una muestra
t.test(notas, mu = 3.3, alternative = "greater")

## 
##  One Sample t-test
## 
## data:  notas
## t = 1.416, df = 49, p-value = 0.08155
## alternative hypothesis: true mean is greater than 3.3
## 95 percent confidence interval:
##  3.270562      Inf
## sample estimates:
## mean of x 
##      3.46

**Punto 5

# Crear una matriz con los datos
datos_tv <- matrix(c(29, 19, 15, 27), nrow = 2, byrow = TRUE, dimnames = list(c("Más de 25 horas", "Menos de 25 horas"), c("Masculino", "Femenino")))

# Realizar prueba de chi-cuadrado
resultado <- chisq.test(datos_tv)
resultado

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  datos_tv
## X-squared = 4.5262, df = 1, p-value = 0.03338