R Dataset / Package lme4 / InstEval
On this Rdata statistics page, you will find information about the InstEval data set which pertains to University Lecture/Instructor Evaluations by Students at ETH. The InstEval data set is found in the lme4 R package. You can load the InstEval data set in R by issuing the following command at the console data("InstEval"). This will load the data into a variable called InstEval. If R says the InstEval data set is not found, you can try installing the package by issuing this command install.packages("lme4") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the InstEval R data set. The size of this file is about 2,311,569 bytes.
University Lecture/Instructor Evaluations by Students at ETH
Description
University lecture evaluations by students at ETH Zurich, anonymized for privacy protection. This is an interesting “medium” sized example of a partially nested mixed effect model.
Format
A data frame with 73421 observations on the following 7 variables.
s

a factor with levels
1:2972
denoting individual students. d

a factor with 1128 levels from
1:2160
, denoting individual professors or lecturers.
studage

an ordered factor with levels
2
<4
<6
<8
, denoting student's “age” measured in the semester number the student has been enrolled. lectage

an ordered factor with 6 levels,
1
<2
< ... <6
, measuring how many semesters back the lecture rated had taken place. service

a binary factor with levels
0
and1
; a lecture is a “service”, if held for a different department than the lecturer's main one. dept

a factor with 14 levels from
1:15
, using a random code for the department of the lecture. y

a numeric vector of ratings of lectures by the students, using the discrete scale
1:5
, with meanings of ‘poor’ to ‘very good’.
Each observation is one student's rating for a specific lecture (of one lecturer, during one semester in the past).
Details
The main goal of the survey is to find “the best liked prof”, according to the lectures given. Statistical analysis of such data has been the basis for a (student) jury selecting the final winners.
The present data set has been anonymized and slightly simplified on purpose.
Examples
str(InstEval)head(InstEval, 16) xtabs(~ service + dept, InstEval)
Dataset imported from https://www.rproject.org.