Paper
Kaitlyn Good
Chapter 13 notes
4-26-13
To Be Important, a Study Must be Replicable * Good researchers will always ask if the study is replicable * Must be replicable to be important * Two strategies used to determine if it is replicable * Use inferential stats * Conduct same study again * Inferential Statistics: Estimating Whether a Study is Replicable * Inferential stats * Use theories of probability to decide if the result is statistically significant * Compare probability estimate, which predicts likelihood that the result was sampled from a population in which there is no difference, no correlation or no relationship * Leads researchers to infer that if they were to repeat the study exactly they would get similar results * Replication Studies: Making Replication an Empirical Question * Direct Replication * Researchers repeat an original study as closely as they can, to see if the original effect shows up in the newly collected data * Direct replication can never replicate the first study exactly * If any threats were present in the original study they will be seen in the direct replication * Conceptual Replication * Researchers study the same research question but use different procedures * Variables in the study are the same but the procedures are different * Replication-Plus Extension * Researchers replicate their original study but add variables to test additional questions * Introduce new situational variable * Ex: first replication of the finding that driving while talking on a cell phone worsens people’s driving performance then compared the effect of driving drunk to the effect of driving while on a cell phone * Replication, Importance and the “Weight of the Evidence” * Even statistically significant studies should be tested through replication studies *
Chapter 13 notes
4-26-13
To Be Important, a Study Must be Replicable * Good researchers will always ask if the study is replicable * Must be replicable to be important * Two strategies used to determine if it is replicable * Use inferential stats * Conduct same study again * Inferential Statistics: Estimating Whether a Study is Replicable * Inferential stats * Use theories of probability to decide if the result is statistically significant * Compare probability estimate, which predicts likelihood that the result was sampled from a population in which there is no difference, no correlation or no relationship * Leads researchers to infer that if they were to repeat the study exactly they would get similar results * Replication Studies: Making Replication an Empirical Question * Direct Replication * Researchers repeat an original study as closely as they can, to see if the original effect shows up in the newly collected data * Direct replication can never replicate the first study exactly * If any threats were present in the original study they will be seen in the direct replication * Conceptual Replication * Researchers study the same research question but use different procedures * Variables in the study are the same but the procedures are different * Replication-Plus Extension * Researchers replicate their original study but add variables to test additional questions * Introduce new situational variable * Ex: first replication of the finding that driving while talking on a cell phone worsens people’s driving performance then compared the effect of driving drunk to the effect of driving while on a cell phone * Replication, Importance and the “Weight of the Evidence” * Even statistically significant studies should be tested through replication studies *