A generated data set containing data on 1200 imaginary individual K-12 students in Wisconsin. They are nested within 6 schools in 3 districts. In adapting this from the source, Sam switched the school and district variables (there had been multiple districts per school) and made other minor changes, including dropping columns that I didn't understand or that didn't seem relevant (e.g., variables like "luck" that were used to calculate the reading and math scores).
wiscA data frame with 2700 rows and 26 variables:
numeric: student's unique ID #
numeric: grade level
numeric: district code
numeric: school code
numeric: is the student white?
numeric: is the student black?
numeric: is the student Hispanic?
numeric: is the student Native-American Indian?
numeric: is the student Asian?
numeric: is the student economically-disadvantaged?
numeric: is the student female?
numeric: is the student an English Language Learner?
numeric: does the student have a learning disability?
numeric: school year
numeric: days attended
numeric: student's reading standardized test score
numeric: student's math standardized test score
factor: student's proficiency level
factor: student's single-category race
...