# epi.descriptives: Descriptive statistics In epiR: Tools for the Analysis of Epidemiological Data

 epi.descriptives R Documentation

## Descriptive statistics

### Description

Computes descriptive statistics for a numeric vector or a table of frequencies for a factor.

### Usage

``````epi.descriptives(dat, conf.level = 0.95)
``````

### Arguments

 `dat` either a numeric vector or a factor. `conf.level` magnitude of the returned confidence intervals. Must be a single number between 0 and 1.

### Value

If `dat` is numeric a list containing the following:

 `arithmetic` `n` number of observations, `mean` arithmetic mean, `sd` arithmetic standard deviation, `q25` 25th quantile, `q50` 50th quantile, `q75` 75th quantile, `lower` lower bound of the confidence interval, `upper` upper bound of the confidence interval, `min` minimum value, `max` maximum value, and `na` number of missing values. `geometric` `n` number of observations, `mean` geometric mean, `sd` geometric standard deviation, `q25` 25th quantile, `q50` 50th quantile, `q75` 75th quantile, `lower` lower bound of the confidence interval, `upper` upper bound of the confidence interval, `min` minimum value, `max` maximum value, and `na` number of missing values. `symmetry` `skewness` and `kurtosis`.

If `dat` is a factor a data frame listing:

 `level` The levels of the factor `n` The frequency of the respective factor level, including the column totals.

### Examples

``````## EXAMPLE 1:
## Generate some data:
id <- 1:100
n <- rnorm(100, mean = 0, sd = 1)
dat.df01 <- data.frame(id, n)

missing <- dat.df01\$id %in% sample(dat.df01\$id, size = 20)
dat.df01\$n[missing] <- NA

epi.descriptives(dat.df01\$n, conf.level = 0.95)

## EXAMPLE 2:
## Generate some data:
n <- 1000; p.exp <- 0.50; p.dis <- 0.75
strata <- c(rep("A", times = n / 2), rep("B", times = n / 2))
exp <- rbinom(n = n, size = 1, prob = p.exp)
dis <- rbinom(n = n, size = 1, prob = p.dis)
dat.df02 <- data.frame(strata, exp, dis)

dat.df02\$strata <- factor(dat.df02\$strata)
dat.df02\$exp <- factor(dat.df02\$exp, levels = c("1", "0"))