add example

example_stat_per_dep.R

+## statistics about grades, points per task grouped by department
+max_points_per_task <- c(10, 10, 10, 10) # max. no. of points per task
+maxpoints <- sum(max_points_per_task)    # max. points
+dp <- 0.5                                # point interval
+dg <- 0.25                               # grade interval
+## piecewise linear grading scale. If no grade is assigned to 0 or maxpoints,
+## it is assumed that they map to grade 1 or 6 respectively.
+int_points <- c(0, maxpoints)
+int_grades <- c(1, 6)
+
+library(dplyr)
+library(ggplot2)
+library(reshape)
+library(xtable)
+
+## read data
+dset <- read.csv('marks.csv', encoding='ISO-8859-1')
+dset <- dset[, !(names(dset) %in% c("Last.Name", "First.Name"))]
+dset <- melt(dset, id=c("Number", "Direction"))
+dset$value <- as.numeric(dset$value)
+total_points <- group_by(dset, Number, Direction) %>% summarize(s=sum(value))
+linscale <- data.frame(approx(int_points, int_grades, seq(0, maxpoints, by=dp)))
+## join grading scale with total_points by using an auxiliary column with integer values
+FUZZY <- 1e6
+linscale$jj <- as.integer(round(linscale$x*FUZZY))
+scale <- data.frame(grade=floor(linscale$y*1/dg)*dg, jj=linscale$jj)
+## add integer column to total_points
+total_points$jj <- as.integer(round(total_points$s*FUZZY))
+grades <- data.frame(left_join(x=total_points, y=scale, by="jj"))
+grades <- grades[,c("Number", "Direction", "s", "grade")]
+
+## grade cdf by Direction
+ggplot(grades, aes(x=grade, color=Direction)) +
+  stat_ecdf()  +
+  scale_x_continuous(breaks=seq(1,6, by=1)) +
+  coord_cartesian(xlim=c(1,6))
+
+## grade density by Direction
+dev.new()
+ggplot(grades, aes(x=grade, color=Direction)) +
+  geom_density(trim=TRUE) +
+  coord_cartesian(xlim=c(1,6))
+
+## mark density by Direction
+dev.new()
+ggplot(dset, aes(x=value, color=Direction)) +
+  geom_density(trim=TRUE) +
+  facet_wrap(~variable) +
+  xlab("Points")