1. The Scientific Method Observation Theory Hypothesis Test Making it public Peer review Replication

2. Experimental Research Why do experiments? The problem of causation

3. Showing Causality Experiment Experimental group and control group Random assignment to groups Independent variable Dependent variable Differences?

4. Variables Independent What you think CAUSES the Dependent Variable to change Independent bc RESEARCHER controls it Dependent What you think will BE CHANGED by changes in the Independent Variable Dependent bc IV controls it

5. Variables Arrow of causality IV  DV

6. Another Variable Confounding variables The ones that confuse things The ones that MIGHT interfere in the causal relationship between IV and DV, OR might just look like they do Also known as intervening variables

7. Experimental and Control Groups The experimental group gets the level of the INDEPENDENT VARIABLE that you think will CAUSE a CHANGE The control group gets the USUAL level of the IV, where you would expect NO CHANGE

8. Experimental and Control Groups Examples EG gets new medication, CG gets placebo EG gets new medication, CG gets standard current medication EG gets new therapy, CG gets old therapy EG gets new therapy, CG gets wait list EG gets new sales pitch, CG gets old one EG gets new interview, CG gets old one

9. EG and CG, cont. How do you know it’s the level of the IV that made the difference? Try to make EG and CG as similar as possible. Random assignment. Assignment with matching. (what are the sources of confounding effects in these designs?? Interaction between the matched pairs).

10. Sampling We can’t measure or test everybody. Take a sample. A RANDOM sample is more likely to accurately reflect the population, and less likely to bias the results. A bigger sample is better … to a point. Our sample may not be an accurate representation of the population anyway. Stats can help.

11. Statistics Results from control group Results from experimental group How to know if the difference is chance or a “real” difference? Math can help.

12. Researcher Bias Hypothesis – we all like to be right (and some of us get paid to be right). Double-blind

13. Quasi-Experimental Designs When you cannot randomly assign participants to EG and CG, but you CAN control the IV. Ex. Do boys respond better than girls to a new strategy for teaching math? (4 groups; B CG, B EG, G CG, G EG) Can suggest a causal relationship.

14. Quasi-Experimental Designs Ex-post-facto designs: you cannot control the IV Ex; do smokers or non-smokers have more fires in their homes? CANNOT ESTABLISH A CAUSAL RELATIONSHIP

15. For next class Bring a MAGAZINE of ANY kind

16. Designing an Experiment Group of two - Exercise; 3.3%

17. An Exercise on Variables Group of 3 or 4 people Likely to work together all semester Know each other well enough to make groups on your own, or shall I assign?