Calculate the summary statistics for specified courses including mean, median and quantiles.

generate_course_statistics(courses, grades, course_ids)

Arguments

courses	A dataframe containing component weights for each course
grades	A dataframe containing grades for students
course_ids	A list including all course IDs for which the summary statistics are calculated for.

Value

A dataframe containing the summary statistics for specified courses

Examples

grades <- data.frame(
  course_id = c(511, 511, 511, 511, 522, 522, 522, 522),
  student_id = c("tom", "tiff", "mike", "joel", "tom", "tiff", "mike", "joel"),
  lab1 = c(100, 87.6, 84.4, 100, 0, 0, 0, 0),
  lab2 = c(100, 100, 79.6, 100, 0, 0, 0, 0),
  lab3 = c(79.2, 81.2, 75.2, 99.6, 0, 0, 0, 0),
  lab4 = c(83.6, 89.2, 98.8, 71.2, 0, 0, 0, 0),
  quiz1 = c(75.6, 100, 84.8, 96.8, 0, 0, 0, 0),
  quiz2 = c(75.6, 73.2, 100, 79.2, 0, 0, 0, 0),
  milestone1 = c(0, 0, 0, 0, 100, 100, 92, 98.4),
  milestone2 = c(0, 0, 0, 0, 97.6, 77.2, 75.6, 85.6),
  milestone3 = c(0, 0, 0, 0, 80, 76.8, 97.6, 96.8),
  milestone4 = c(0, 0, 0, 0, 100, 100, 84.4, 100),
  feedback = c(0, 0, 0, 0, 100, 85.6, 98.8, 82.4)
)
courses <- data.frame(
  course_id = c(511, 522),
  lab1 = c(0.15, 0),
  lab2 = c(0.15, 0),
  lab3 = c(0.15, 0),
  lab4 = c(0.15, 0),
  quiz1 = c(0.2, 0),
  quiz2 = c(0.2, 0),
  milestone1 = c(0, 0.1),
  milestone2 = c(0, 0.2),
  milestone3 = c(0, 0.2),
  milestone4 = c(0, 0.3),
  feedback = c(0, 0.2)
)
generate_course_statistics(courses, grades, course_ids = "511")
#>   course_id  mean 1st-quantile median 3rd-quantile
#> 1       511 87.87        86.91     88        88.96
generate_course_statistics(courses, grades, course_ids = c("511", "522"))
#>   course_id  mean 1st-quantile median 3rd-quantile
#> 1       511 87.87        86.91     88        88.96
#> 2       522 91.29        88.67  90.86        93.48