R/data-ask.R

In openintro: Data Sets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

#' How important is it to ask pointed questions?
#'
#' In this experiment, each individual was asked to be a seller of an iPod (a
#' product commonly used to store music on before smart phones...).  They
#' participant received $10 + 5% of the sale price for participating.  The
#' iPod they were selling had frozen twice in the past inexplicably but
#' otherwise worked fine. The prospective buyer starts off and then asks one of
#' three final questions, depending on the seller's treatment group.
#'
#' The three possible questions:
#' - General: What can you tell me about it?
#' - Positive Assumption: It doesn't have any problems, does it?
#' - Negative Assumption: What problems does it have?
#'
#' The outcome variable is whether or not the participant discloses or hides
#' the problem with the iPod.
#'
#'
#' @name ask
#' @docType data
#' @format A data frame with 219 observations on the following 3 variables.
#' \describe{
#'   \item{question_class}{The type of question:
#'   `general`, `pos_assumption`, and `neg_assumption`.}
#'   \item{question}{The question corresponding to the
#'   `question.class`}
#'   \item{response}{The classified response from the seller,
#'   either `disclose` or `hide`.}
#'   }
#' @source Minson JA, Ruedy NE, Schweitzer ME. There *is* such a thing as
#' a stupid question: Question disclosure in strategic communication.
#' @keywords datasets
#' @examples
#'
#' library(dplyr)
#' library(ggplot2)
#'
#' # Distribution of responses based on question type
#' ask %>%
#'   count(question_class, response)
#'
#' # Visualize relative frequencies of responses based on question type
#' ggplot(ask, aes(x = question_class, fill = response)) +
#'   geom_bar(position = "fill")
#'
#' # Perform chi-square test
#' (test <- chisq.test(table(ask$question_class, ask$response)))
#'
#' # Check the test's assumption around sufficient expected observations
#' # per table cell.
#' test$expected
"ask"