Lect# Lectures Supporting readings Student presentations
Getting organized 20 min. Examples of causal modeling. Causality and its perils. Pascal; Asch; Schechter; (medical example). Cook & Campbell, Ch. 1

Concepts and indicators. Dependent/outcome/explicandum variable. Focusing on variations of two concepts. Using (Venn) diagrams for specifying concepts. Types of variables.

de Vaus, Ch. 3-4.
Hand in a 1-page paper about your research topic
Elaboration: specification, clarification, explanation. How to construct representations of theory. Rosenberg, Ch. 6, de Vaus, Ch. 12; (tba)
12*3min presentations: what are your x and y; background, intervening, and consequent variables. 2 slides allowed!

Elementary probability, levels of significance, null hypothesis and randomization. Indexes. A brief look at a statistical program (SPSS).

Fisher, Ch. 2; Indexes: de Vaus, Ch. 15; probablity: Mosteller et al.

12*3min: a new version of last week's presentation, with a strategy for detecting spurious relationships. 2 new slides allowed!
The main types of experimental design (simple experiment, block design, factorial design, latin squares). Survey analysis/statistical analysis and its causal status. Between-subjects, within-subjects. (If there is time, a cursory look at time-series and event histories) Maclin & Solso, Ch. 4, Ch. 6.
12*3min: what's your null hypothesis. How can you know whether it has to be rejected? 1 new slide allowed
Checking your research causal models. Intro to alternative designs. -
12*3min: specify your methodology using last week's results. 2 new slides allowed

Guest lecturer: Antti Oulasvirta. He talks about quasi-experimental research.


de Vaus, Ch 16-17. tba**
3*15min: about your own research
Initial analysis. Clarification. The main familiers of statistical techniques. Things that show up along the way. Small samples. Validity: main threats. Cook & Campbell,pp. 50-58, 70-79.
Cntd. Complications good to know. **
Wrap up 45 min. What is causality and how do we understand it? Positivism? What kinds of uses does this methodology have in design research and practice-based research? Qualitative data in quantitative analysis: the limits of causal methodology through an example from ergonomics. Ethics. Small N and Big Conclusions, and other complications, depending on how much time we have.Questions 45 min.

Ethics: Milgram.

Discussion in the classroom.

4*15min, about own research

One week after the class, you need to hand in the final slide show of your research topic, with research ethics thought of.