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Experimentation. What experiments are not: Two commonsense uses of “experiment”: – any study – to “try something out” – …both of these understandings.

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Presentation on theme: "Experimentation. What experiments are not: Two commonsense uses of “experiment”: – any study – to “try something out” – …both of these understandings."— Presentation transcript:

1 Experimentation

2 What experiments are not: Two commonsense uses of “experiment”: – any study – to “try something out” – …both of these understandings are flawed.

3 What Experiment are: Experiments test causal relationships. A causal relationship has three elements: – Stable temporal ordering – An association between the phenomena studied – No alternative explanations for that association. Among all the methods available to social researchers, only experiments can verify all three of these elements that define a causal relationship.

4 “Real” experiments have three necessary conditions: A hypothesis; The modification of something in a specific situation; The comparison of outcomes with and without the modification.

5 Experimentation requires that “subjects” (“Ss”) be randomly assigned to “treatment” and “control” groups. The meaning of “random assignment” The purpose of random assignment – Attainment of comparable groups – Even distribution of bias Methods of random assignment – Random process, like coin flips – Random number generator – Computer-based assignment

6 Experiment designs vary, but must have 7 essential features to be true experiments: Random assignment A “treatment” or “independent” variable A “dependent” variable Pretesting Post-testing An “experimental” or “treatment” group A “control” group

7 Some examples of experimental and pseudo-experimental design “Pre-experimental designs” (shortcuts) – Case study (no comparison, no pretest) – Static group comparison (no random assignment, no pretest) Classical Experimental Design – With dichotomous independent variable – With continuous independent variable – With more than one independent variable Quasi-experimental Designs – Two-group, post-test only with random assignment – Time series designs with one group or one subject – Latin square – Solomon n-group – Field experiments

8 Issues regarding internal and external validity Internal Validity – Selection Bias – History Effects – Maturation – Testing Effects – Instrument Reliability – Contamination – Experimenter Expectancy External Validity – Realism (is setting or task “real”?) experimental realism mundane realism – Reactivity (are Ss only reacting to experiment?) The Hawthorne effect response to demand characteristics the placebo effect


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