01-table.Rmd

---
title: "Tablas de Contingencia"
author: "Curso de Estadística Descriptiva"
date: "24/12/2018"
output: html_document
---

# Tablas de contingencia

```{r}
datos = factor(c("H", "M", "M", "M", "H", "H", "M", "M"))
table(datos)
table(datos)["M"]
sum(table(datos))
```

# Frecuencias relativas

$$f_i = \frac{n_i}{n}$$

```{r}
prop.table(table(datos))
100*prop.table(table(datos))
table(datos)/length(datos)
names(which(table(datos)==3))

moda <- function(d){
  names(which(table(d)==max(table(d))))
}

m_t = moda(datos)
```

La moda del data frame es: `r m_t`.

# Paquete `gmodels`
```{r}
library(gmodels)
sex = factor(c("H", "M", "M", "M", "H", "H", "M", "M"))
ans = factor(c("S", "N", "S", "S", "S", "N", "N", "S"))
CrossTable(sex, ans, prop.chisq = FALSE)
```

# Sumas por filas y columnas
```{r}
tt <- table(sex, ans)
tt# Frec. absolutas
prop.table(tt)#Frec. Rel. Global
prop.table(tt, margin = 1)#Frec. Rel. Por sexo
prop.table(tt, margin = 2)#Frec. Rel. Por respuesta

colSums(tt)
rowSums(tt)
colSums(prop.table(tt))
rowSums(prop.table(tt))

apply(tt, FUN = sum, MARGIN = 1)
apply(tt, FUN = sqrt, MARGIN = c(1,2))
```