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The data are gathered from end of semester student evaluations for 463 courses taught by a sample of 94 professors from the University of Texas at Austin. In addition, six students rate the professors' physical appearance. The result is a data frame where each row contains a different course and each column has information on the course and the professor who taught that course.

Usage

evals

Format

A data frame with 463 observations on the following 23 variables.

course_id

Variable identifying the course (out of 463 courses).

prof_id

Variable identifying the professor who taught the course (out of 94 professors).

score

Average professor evaluation score: (1) very unsatisfactory - (5) excellent.

rank

Rank of professor: teaching, tenure track, tenured.

ethnicity

Ethnicity of professor: not minority, minority.

gender

Gender of professor: female, male.

language

Language of school where professor received education: English or non-English.

age

Age of professor.

cls_perc_eval

Percent of students in class who completed evaluation.

cls_did_eval

Number of students in class who completed evaluation.

cls_students

Total number of students in class.

cls_level

Class level: lower, upper.

cls_profs

Number of professors teaching sections in course in sample: single, multiple.

cls_credits

Number of credits of class: one credit (lab, PE, etc.), multi credit.

bty_f1lower

Beauty rating of professor from lower level female: (1) lowest - (10) highest.

bty_f1upper

Beauty rating of professor from upper level female: (1) lowest - (10) highest.

bty_f2upper

Beauty rating of professor from second level female: (1) lowest - (10) highest.

bty_m1lower

Beauty rating of professor from lower level male: (1) lowest - (10) highest.

bty_m1upper

Beauty rating of professor from upper level male: (1) lowest - (10) highest.

bty_m2upper

Beauty rating of professor from second upper level male: (1) lowest - (10) highest.

bty_avg

Average beauty rating of professor.

pic_outfit

Outfit of professor in picture: not formal, formal.

pic_color

Color of professor's picture: color, black & white.

Source

Daniel S. Hamermesh, Amy Parker, Beauty in the classroom: instructors’ pulchritude and putative pedagogical productivity, Economics of Education Review, Volume 24, Issue 4, 2005. doi: 10.1016/j.econedurev.2004.07.013 .

Examples


evals
#> # A tibble: 463 × 23
#>    course_id prof_id score rank    ethnicity gender language   age cls_perc_eval
#>        <int>   <int> <dbl> <fct>   <fct>     <fct>  <fct>    <int>         <dbl>
#>  1         1       1   4.7 tenure… minority  female english     36          55.8
#>  2         2       1   4.1 tenure… minority  female english     36          68.8
#>  3         3       1   3.9 tenure… minority  female english     36          60.8
#>  4         4       1   4.8 tenure… minority  female english     36          62.6
#>  5         5       2   4.6 tenured not mino… male   english     59          85  
#>  6         6       2   4.3 tenured not mino… male   english     59          87.5
#>  7         7       2   2.8 tenured not mino… male   english     59          88.6
#>  8         8       3   4.1 tenured not mino… male   english     51         100  
#>  9         9       3   3.4 tenured not mino… male   english     51          56.9
#> 10        10       4   4.5 tenured not mino… female english     40          87.0
#> # … with 453 more rows, and 14 more variables: cls_did_eval <int>,
#> #   cls_students <int>, cls_level <fct>, cls_profs <fct>, cls_credits <fct>,
#> #   bty_f1lower <int>, bty_f1upper <int>, bty_f2upper <int>, bty_m1lower <int>,
#> #   bty_m1upper <int>, bty_m2upper <int>, bty_avg <dbl>, pic_outfit <fct>,
#> #   pic_color <fct>