| 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. | ** | ||
10 |
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.