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Simple Experiments

Simple Experiments. 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. Experiments: The Basics. Very specific meaning

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Simple Experiments

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  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. Design • 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C BCA • ACB CAB • BAC C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

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