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The data were gathered from end of semester student evaluations for a large
sample of professors from the University of Texas at Austin (variables beginning
with cls
). In addition, six students rated the professors' physical
appearance (variables beginning with bty
). (This is a slightly modified
version of the original data set that was released as part of the replication
data for Data Analysis Using Regression and Multilevel/Hierarchical Models
(Gelman and Hill, 2007).
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A data frame with 463 rows and 21 variables:
Average professor evaluation score: (1) very unsatisfactory - (5) excellent
Rank of professor: teaching, tenure track, tenure
Ethnicity of professor: not minority, minority
Gender of professor: female, male
Language of school where professor received education: english or non-english
Age of professor
Percent of students in class who completed evaluation
Number of students in class who completed evaluation
Total number of students in class
Class level: lower, upper
Number of professors teaching sections in course in sample: single, multiple
Number of credits of class: one credit (lab, PE, etc.), multi credit
Beauty rating of professor from lower level female: (1) lowest - (10) highest
Beauty rating of professor from upper level female: (1) lowest - (10) highest
Beauty rating of professor from second upper level female: (1) lowest - (10) highest
Beauty rating of professor from lower level male: (1) lowest - (10) highest
Beauty rating of professor from upper level male: (1) lowest - (10) highest
Beauty rating of professor from second upper level male: (1) lowest - (10) highest
Average beauty rating of professor
Outfit of professor in picture: not formal, formal
Color of professor's picture: color, black & white
These data appear in Hamermesh DS, and Parker A. 2005. Beauty in the classroom: instructors pulchritude and putative pedagogical productivity. Economics of Education Review 24(4):369-376. This is a slightly modified version of the original data set that was released as part of the replication data for Gelman, Andrew, and Jennifer Hill. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, 2006.
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