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Prerequisites
Taught by
Language of instruction
Duration
Identical courses
Cannot be taken as part of an examination contractAims
The course aims at making students aware of the fact that different research questions requires different data and different techniques to be answered. Moreover, it underlines what are the assumptions, strengths and weaknesses of each analytical approach to the solution of a research problem. The students will first gains an understanding of how a research question can be formally translated into hypotheses that can be formally tested and how to organize the empirical material to answer the question. They will learn about the nature of data and the way to handle them in an adequate, effective and efficient way.
At the end of the course, the students are expected to be able to analyse a research problem and to suggest the appropriate analytical strategy to tackle it. Whence the title of the course: From Problem to Analysis. The course thus supply a reference scheme in which the students can also organize the knowledge concerning other models that they will acquire in further courses.
Previous knowledge
To attend the course, the students are expected to have a working knowledge of the basic mathematical concepts and procedure.
Students should also be acquainted to a statistical package, with a preference for SPSS. The exercises will be illustrated with this software.
Is included in these courses of study
- Doctoral Programme in Business Economics (Leuven)
- Master of Statistics and Data Science (on campus) (Leuven) (Statistics and Data Science for Social, Behavioral and Educational Sciences) 120 ects.
- Master of Statistics and Data Science (Abridged Programme - Quantitative Analysis in the Social Sciences) (No new enrollments as from 2023-2024) (Leuven) (Quantitative Analysis in the Social Sciences) 60 ects.
- Master of Sociology (Leuven) 60 ects.
Activities
6 ects. From Problem to Analysis (B-KUL-G0W09a)
Content
Part I. The nature of data and measurement
Measurement will cover the first part of the course, considering measurement models as a constitutional part of the conceptualization process. Continuous, ordinal, discrete variables as well as single or multiple items measurement will be addressed, namely handling Classical Test Theory (factor and reliability analysis).
Part II. From Theory to Methodology
Different types of problems and research situations are illustrated, supplying a classification of classical techniques of multivariate analysis. Thus, the connection between a problem and a technique is analysed.
Part III. The analytical strategy
The course presents a discussion of the classical techniques of multivariate analysis, of which students gain an overview in an expert-like way. Students will also have an active acquaintance with the classical techniques as well as with the underlying assumptions of the models.
Course material
A list with compulsory and suggested study materials will be supplied a few weeks before the starting of the course.
Language of instruction: more information
The course will be held in English.
Format: more information
The main components of the course are the following (all lectures will be recoded and uploaded to Toledo):
Readings: for each topic, a list of readings and additional material is supplied; the students are expected to be familiar with the material before attending the lectures; the list is made available in advance, with sufficient time to allow student to a comfortable preparation of the lectures.
Basic concepts: description of the basic concepts related to the topic, online and in presence
Exercise: an exercise with detailed instruction is supplied and explained to the students; the exercise is supplied in written form; students have a week time to carry out the exercise
Q&A sessions: students can submit their questions via mail/social media/platform within the week; for each topic a session of Q&A takes place, online and in presence
Evaluation: Each week assignment + Final assignment, discussed with the student individually.
This course is taught in block teaching: approximately 1 month of classes, from September 24 to October 31, with lectures twice a week. Following this, a final assignment is expected to be completed, which will be discussed during the January exam period.
Evaluation
Evaluation: From Problem to Analysis (B-KUL-G2W09a)
Explanation
Features of evaluation
The evaluation is based upon on the evaluation of the final assignement that will be discussed orally. The request for the final assignment is to apply all the notions learned in class to answer a research question defined by the student. The notions learned in class do not concern only statistical models, but also the application of the correct logic to a research problem, the evaluation of the quality of measurement, the sensitivity to the limitations of the models applied.
The oral discussion could contemplate also theoretical questions.
Evaluation criteria
The course is evaluated by the teacher, as announced via Toledo and the examination regulations. The result is calculated and expressed as an integer out of 20.
The grade is based on the written final assignment (80%) and the oral evaluation (20%).
Students are fully responsible for submitting papers and assignments free of fraud and plagiarism (www.kuleuven.be/english/education/plagiarism/) and are requested to observe the Faculty’s relevant regulations. Plagiarism will be sanctioned with the sanctions mentioned in the University’s Regulations on Education and Examinations (http://www.kuleuven.be/education/regulations/).
For students with the status of working student, the above evaluation characteristics can be deviated from, in consultation with and after approval by the lecturer.
Second examination opportunity
Students who do not pass in January are given the opportunity to resubmit a paper in September. Identical evaluation criteria are used.