1. Simple Experiments

2. Causal Claim Boldest claim a scientist can make Verbs such as “associated with” and “related to” replaced with “causes, influences, affects or makes” Must be based on sound experimental research

3. Experiments: The Basics Very specific meaning Manipulation of at least one variable Measurement of at least one variable Control of possible threatening variables

4. Independent Variables Manipulated At least two levels Assign participants to at least one of the levels (condition) Plotted on the X axis Examples: – Color, parenting type, amount of caffeine, minutes of exercise a day

5. Dependent Variables Measured – Depends on IV Behavioral, physiological, self-reports, attitudes Determines kinds of statistics employed Plotted on the Y axis

6. Control Variables Researchers need to be sure they are manipulating one variable at a time  the IV Must hold all other factors/variables constant Confound variables- may be the cause of the change in the dependent variable. – Influences “internal validity” – Possible explanation other than the IV

7. Comparison Groups Control groups Level of the IV that is intended to represent “no treatment” or a neutral condition AKA “placebo grou”

8. Other Important Factors Random selection Random assignment – Except when “matching “on variable Design

9. Refers to how the subjects are placed with regards to IV conditions/levels Depends on concerns for confound variables such as: – Fatigue – Practice – Variables known to be a potential confound

10. Within-Subjects Design All P’s exposed to all levels of the IV Same P’s in each level Advantage: – Less variability between groups Disadvantage: – Practice effect, fatigue, order effects; demand characteristics Use of counterbalancing  present the levels of the IV to in different orders

11. Counterbalancing Split participants into groups; each group receives one of the condition orders Example with IV that has 3 levels – A  B  CB  C  A – A  C  BC  A  B – B  A  CC  B  A Partial counterbalancing an option when too many levels

12. Between-Subjects Design Different P’s in each of the IV levels Advantage: – No practice effects – No fatigue – No order effect Disadvantage: – Too much variability – Overcome by random selection and assignment – Large sample size

13. Matched-Groups Design Used when researcher concerned about known confounding variable (gender, IQ etc) Used to equate the groups so the effect of the IV is clearer