R/College_grades.R

#' Grades at a small college
#' 
#' These are the actual grades for 400+ individual students in the courses they took
#' at a small, liberal-arts college in the midwest US. All the students graduated in 2006. 
#' Each row corresponds to a single student in a single course. The data have been de-identified by translating the student ID, the instructor 
#' ID, and the name of the department. Typically a graduating student has taken about 32 courses.
#' As another form of de-identification, only half of the courses each student, selected randomly,
#' are included. Only courses with 10 or more students enrolled were included.
#' 
#' @docType data
#' @name College_grades
#' @usage data(College_grades)
#'
#' @keywords datasets
#' 
#' @source The data were helpfully provided by the registrar of the college with the proviso 
#' that the de-identification steps outlined above be performed. 
#'
#' @format
#'   A data frame with 6146 Grades for 443 students.
#'   \itemize{
#'     \item{\code{grade}} {The letter grade for the student in this course: A is the highest.}
#'     \item{\code{sessionID}} {An identifier for the course taken. Courses 
#'     offered multiple times in one semester or across semesters have individual IDs.}
#'     \item{\code{sid}} {The student ID}
#'     \item{\code{dept}} {The department in which the course was offered. 100 is entry-level, 
#'     200 sophomore-level, 300 junior-level, 400 senior-level.}
#'     \item{\code{enroll}} {Student enrollment in the course. This includes students who are not 
#'     part of this sample.}
#'     \item{\code{iid}} {Instructor ID}
#'     \item{\code{gradepoint}} {A translation of the letter grade into a numerical scale. 4 is high.
#'     Some letter grades are not counted in a student's gradepoint average. These have \code{NA} for
#'     the gradepoint.}
#'   }
#' 
#' @examples
#' \dontrun{
#' GPA <- lm(gradepoint ~ sid - 1, data = College_grades)
#' }
"College_grades"

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mosaicModel documentation built on May 2, 2019, 7:59 a.m.