Fibtelereg dataset
fibteleregA data frame with 147 observations on the following 18 variables. The first ten variables
are segmentation variables. The rest of the variables refer to five variables 1)
Image = Image, 2) Exp.spec = Specific Expectation, 3) Exp.gen = Generic Expectation,
4)Qual.spec = Specific Quality, 5) Qual.gen = Generic Quality, 6) Value = Value, 7)
Satis = Satisfaction.
Variables description
Image: Generic students perception of ICT schools: (internationally recognized,
ranges of courses, leader in research).
Exp.spec: Specific Expectation on specific skills (technic or applied skills).
Exp.gen: Generic Expectation on generic skills (abilities in problem solving,
communication skills).
Qual.spec: Perception about the achieved quality on the specific skills in the school.
Qual.gen: Perception about achieved quality on the generic skills in
the school (abilities in solving problem, communication skills).
Value: The advantage or profit that the alumni may draw from the school
degree (well paid job, motivated job, prospectives in improvement and promotion).
Satis: Degree of alumni satisfaction about the formation in school respect to
their actual work conditions.
Segmentation Variables description
Careera factor with levels EI ETS TEL
Gendera factor with levels female male
Agea factor with levels 25-26years 27-28years 29-30years 31years+
Studyinga factor with levels no.stud yes.stud
Contract a factor with levels fix.cont other.cont temp.cont
Salarya factor with levels 18k >45k 25k 35k 45k
Firmtypea factor with levels priva publi
Accgradea factor with levels 7-8accnote accnote<7 accnote>8
Gradea factor with levels <6.5note >7.5note 6.5-7note 7-7.5note
Startworka factor with levels after.grad befor.grad
Lamberti, G. (2014) Modeling with Heterogeneity. PhD Dissertation.