R/data-mammals.R

In OpenIntroStat/openintro-r-package: Data Sets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

#' Sleep in Mammals
#'
#' This data set includes data for 39 species of mammals distributed over 13
#' orders. The data were used for analyzing the relationship between
#' constitutional and ecological factors and sleeping in mammals. Two
#' qualitatively different sleep variables (dreaming and non dreaming) were
#' recorded. Constitutional variables such as life span, body weight, brain
#' weight and gestation time were evaluated. Ecological variables such as
#' severity of predation, safety of sleeping place and overall danger were
#' inferred from field observations in the literature.
#'
#'
#' @name mammals
#' @docType data
#' @format A data frame with 62 observations on the following 11 variables.
#' \describe{
#'   \item{species}{Species of mammals}
#'   \item{body_wt}{Total body weight of the mammal (in kg)}
#'   \item{brain_wt}{Brain weight of the mammal (in kg)}
#'   \item{non_dreaming}{Number of hours of non dreaming sleep}
#'   \item{dreaming}{Number of hours of dreaming sleep}
#'   \item{total_sleep}{Total number of hours of sleep}
#'   \item{life_span}{Life span (in years)}
#'   \item{gestation}{Gestation time (in days)}
#'   \item{predation}{An index of how likely the mammal is to be preyed upon.
#'   1 = least likely to be preyed upon. 5 = most likely to be preyed upon.}
#'   \item{exposure}{An index of the how exposed the mammal is during sleep.
#'   1 = least exposed (e.g., sleeps in a well-protected den). 5 = most exposed.}
#'   \item{danger}{An index of how much danger the mammal
#' faces from other animals. This index is based upon Predation and Exposure. 1
#' = least danger from other animals. 5 = most danger from other animals.}
#' }
#' @references T. Allison and D. Cicchetti, "Sleep in mammals: ecological and
#' constitutional correlates," Arch. Hydrobiol, vol. 75, p. 442, 1975.
#' @source \url{http://www.statsci.org/data/general/sleep.txt}
#' @keywords datasets
#' @examples
#'
#' library(ggplot2)
#'
#' ggplot(mammals, aes(x = log(body_wt), y = log(brain_wt))) +
#'   geom_point() +
#'   geom_smooth(method = "lm") +
#'   labs(x = "Log of body weight", x = "Log of brain weight")
"mammals"