R/shiny_dnorm.R

In ABACUS: Apps Based Activities for Communicating and Understanding Statistics

#' Shiny App to Explore Properties of the Normal Distribution
#'
#' @name shiny_dnorm
#' @aliases shiny_dnorm
#' @description An interactive Shiny app to demonstrate properties of the Normal distribution.
#' @usage shiny_dnorm()
#'
#' @details The interactive Shiny app demonstrates the properties of Normal distribution.
#'     The app considers parameters (mean and standard deviation) of the Normal distribution and captures its
#'     properties using different graphical outputs.
#'     The user changes the population parameter values, sample characteristics, distribution function and
#'     simulation features and explores the influence of these changes on the hypothesis testing.
#'
#'     The left panel includes the user inputs for \strong{Simulation Features}, \strong{Population Parameters},
#'     \strong{Sample Characteristics}, and \strong{Distribution Function}.
#'     To use the app at first instance, just click the \code{Update} button.
#'     To alter the input values, edit the text box or move the point on the slider and
#'     explore the changes in different tabs (see below).
#'
#'     To obtain identical outcomes in a separate run of the app,
#'     set a common seed value at the bottom of the left panel and click \code{Update}.
#'     All subsequent updates will produce identical results provided other inputs are identical.
#'     The seed value is ignored when the option \code{check the box to update instantly} is selected.
#'
#' @return The outcomes are presented in several tabs.
#'     \item{Sample}{contains the histogram of sampling units randomly drawn from the given population.
#'     Increasing the sample size and the number of bins creates the shape of the Normal distribution.
#'     It also creates the normal density plot based on empirical data and
#'     theoretical normal distribution given the parameter values}
#'     \item{Distribution}{contains the plot for the probability density function of the Normal distribution
#'     with given parameter values.
#'     The user can also explore centring and scaling effect on the probability density function.}
#'     \item{Probability & Quantile}{contains the plots for the probability density function and
#'     cumulative probability density function. The user can explore the relationship between the
#'     cumulative probability and quantile corresponding to tails of the distribution.}
#'
#' @seealso Function in base R for normal distribution including
#'          \code{\link{dnorm}}, \code{\link{pnorm}}, \code{\link{qnorm}}, \code{\link{rnorm}}.
#'
#' @note \url{https://shiny.abdn.ac.uk/Stats/apps/}
#'
#' @author Mintu Nath
#'
#' @seealso Function in base R for normal distribution, including
#'          \code{\link{dnorm}}, \code{\link{pnorm}},
#'          \code{\link{qnorm}}, \code{\link{rnorm}}
#'
#' @examples
#' if(interactive()){
#'     library(ggplot2)
#'     library(shiny)
#'     library(ABACUS)
#'     # Run shiny app
#'     shiny_dnorm()
#' }
#'
#' @import shiny
#' @import ggplot2
#' @export


# Function

shiny_dnorm <- function() {

  shiny::runApp(appDir = system.file("app_dnorm", package = "ABACUS"), launch.browser = TRUE)
  Sys.setenv("shiny_dnorm" = "")

}