Nordic Informatics Network in the Agricultural Sciences
Design of Data Generation - Experimental Design
Structure
The course will consist of two parts, the statistical
theory of experimental design and the methodological analysis of empirical
research. The parts will be interwoven by the research problems of the
participants in the project works.
In the projects the participants will tackle their
research problem from these both points of view. After clarifying the question
its empirical solution is outlined. Various experimental designs will be
evaluated with respect to their applicability in solving the problem. The aim is
to the matching of the research problem and the experimental design used.
Each day will consist of lectures and seminar-type small
group work. In addition, statistical software exercises take place.
Day 1
- Introduction.
- Aims of the course.
- Introductory presentation of the research problems of
the participants
Day 2
- Introduction to the methodology of empirical research
- Basic statistics: randomization, replication and
blocking
Day 3
-
The art of measurement: validity,
reliability and conceptual efficiency
-
Treatment structure: factorial
designs
Day 4
- The art of experimentation I: clarifying the original
research question
-
Repeated measurements I: analysis of
follow-up designs
Day 5
-
The art of experimentation II:
analysis of the data generation conditions
-
Repeated measurements II: covariance
structures
Day 6
-
Individual research philosophies and
their methods
-
Unbalanced designs I: forms and
reasons of unbalance
Day 7
-
Reasoning in research I: principles
of formal logic and their use in scientific reasoning
-
Unbalanced designs II: implications
to analysis and interpretation
Day 8
Day 9
-
Working in the research community
-
Finalization
of projects
Day 10
-
Presentation of the projects
-
Course evaluation
Author: phd@dina.kvl.dk. Updated:
23 November 2001