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rsprinse Research Methods 212 Inglés 49 fichas

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  1. 1A well-designed experiment:Varies at least one independent variable, assigned participants to conditions, and controls extraneous variables.
  2. 2Environmental manipulationsModifications to the research setting
  3. 3Instructional manipulationsVarying the instructions or information.
  4. 4Invasive manipulationsCreate physical changes in someone through simulation, drugs or surgery.
  5. 5Control variablesHeld constant to separate causes or eliminate alternatives.
  6. 6Internal validityEnsuring that the proposed causal variable is responsible for the change in the effect variable.
  7. 7ConfoundsAn alternative explanation for the research findings.
  8. 8Design confoundsA second variable that varies systematically with the IV and is an alternative explanation for the results.
  9. 9Between groups DesignDifferent groups are exposed to different levels of the IV. Randomly assigned or matched. Selection effects.
  10. 10Pretest only designParticipants are only tested on the DV once.
  11. 11Pretest/posttest designParticipants are tested on the DV twice, before and after the different IV.
  12. 12Within subjects DesignWhere all participants are exposed to the IV. Order effects.
  13. 13Concurrent-measures designParticipants are exposed to all levels at the same time and asked to choose one. (two IVs, one DV)
  14. 14Repeated-measures designParticipants are exposed to the IV, then DV, and repeated.
  15. 15Manipulation checksConstruct validity. A question/questions to ensure the experiment is successful.
  16. 16Pilot testA trial run to test effectiveness.
  17. 17Experimenter's DilemmaThe more controlled the experiment (and better the internal validity) the less generalizable (and worse the external validity).
  18. 18Selection effectsWhen one kind of participant is systematically different in one group. Between-groups. Random assignment. Matched.
  19. 19Order effectsWhen being exposed to one variable changes the outcome of the others. Within-subjects. Carryover, practice, fatigue, sensitization.
  20. 20CounterbalancingPresenting the levels of the IV in different orders.
  21. 21Partial counterbalancingWhen some, but not all, possible combinations of order are presented. Latin square.
  22. 22MaturationWhen an observed change could have emerged spontaneously. Use two groups?
  23. 23History threatWhen change occurs because of an event outside the experiment. This must vary systematically.
  24. 24Regression threatRegression towards the mean. Extreme findings will become normal.
  25. 25AttritionIn a repeated-measures experiment where participants systematically drop out. Their pretest scores might be removed.
  26. 26Testing threatA repeated measures experiment where scores change because the participants took the test more than once.
  27. 27Instrumental threatWhen the measuring instrument changes because its been used before.
  28. 28Observer biasWhen an observer's expectations change the result of the study. It can happen whenever behaviour is the DV. Double-blind.
  29. 29Placebo effectWhen participants feel like they are getting better because they believe they are getting treatment. Double-blind placebo control group.
  30. 30Ceiling effectNull findings. When something is too easy and all scores fall on the high end.
  31. 31Floor effectNull findings. When testing is too easy and the results fall on one end.
  32. 32Confounds in reverseWhen confounds eliminate the effect of the IV. Nervousness with GPA.
  33. 33Within-group variabilityNull findings. Noise or error variance creates overlap and makes it hard to find differences. Measurement error, individual differences, and situation noise.
  34. 34Measurement errorIs part of the DV (plus true score). Create reliable, precise measurements, and more instances of it.
  35. 35Individual differencesBaseline mood could be difference or experimenter. use a within-groups design or a matched-groups. Add more participants.
  36. 36Situation noiseWhere the participant gets distracted. Control the setting.
  37. 37Inferential statisticsDetermine if the difference in group means are significant.
  38. 38Systematic variabilityTreatment and confound variance. Has to do with group membership. If everyone varies systematically because of a confound you are in for a bad time.
  39. 39Unsystematic variabilityIndependent of group membership, so within groups. Situation noise, measurement error and individual differences can make it hard to detect.
  40. 40PowerThe probability that the study will show a statistically significant effect from the actual population.
  41. 41Effect sizeSize of the relationship using eta squared or omega squared figure out the proportion of variability. Cohen's d determines the size of difference between means
  42. 42t testA statistical test used to evaluate the size and significance of the difference between means. Error variance?
  43. 43Rejecting the null hypothesisThe conclusion that the IV did have an effect.
  44. 44Failing to reject the null hypothesisWhere researchers conclude the IV had no effect. Could be explained by error variance, and so this does not give us information.
  45. 45Directional hypothesisOne mean is expected to be greater than the other (one tailed)
  46. 46Nondirectional hypothesisWhere the mean is just expected to differ (two-tailed)
  47. 47Type 1 ErrorWhere the researcher wrongly concluded the null hypothesis is false (false alarm). More important. Alpha.
  48. 48Type 2 ErrorWhen the researcher fails to reject the null hypothesis (miss). Beta. Power is used to prevent this and detect IV.
  49. 49P ValueThe probability that the relationship is not by chance.

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Descripción
Simple experiments, confounds/obscuring variables, inferential statistics
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rsprinse
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