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# Psych Research Pt 4

### Experiments, Correlations, Parametrics

Question | Answer |
---|---|

Quasi-Experiment | research technique that does NOT have random assignment, but in which the researcher manipulates the IV |

Investigations | research technique that does NOT allow researcher to infer causation; no random assignment |

Experiment | a study that has random assignment and the researcher manipulates the IV |

Theory | explanation for a phenomenon that can be falsified and that involves entities that cannot be directly observed |

Hypothesis | a tentative statement about the relationship between observable variables |

Can't Prove the Null Hypothesis | impossible to prove that the IV has no effect on the DV |

Random Assignment | occurs when every subject has an equally likely chance to be assigned to each IV level/to each treatment order |

Random Selection | occurs when every member of the population to which we would like to generalize the results has an equally likely chance of being chosen to participate in the study |

Internal Validity | the extent to which your research provides a valid test of the relationship between the IV and DV |

External Validity | the extent to which the results of your research can be applied outside the research situation |

Alpha | the probability of making a Type I error given that our experiment found an effect of the IV on the DV |

Beta | the probability of making a Type II error given that our experiment failed to find an effect of the IV on the DV |

Levels of the IV | specific values of the IV that the researcher uses in a study |

Mean v. Median | mean more affected by extreme scores but more consistent and easier to calculate |

Frequency Distribution | a graph showing the # of times each score occurred in a data set |

Normal Distribution | symmetrical, bell-shaped distribution |

Positively Skewed Distribution | distribution w/ a few extreme high scores |

Negatively Skewed Distribution | distribution w/ a few extreme low scores |

Advantage of Experimental Approach | allows researcher to infer a causal relationship between the IV and DV |

How is the logic of experimentation ruined by confounds? | if you have a confound in an experiment, then it is impossible to know whether it was the IV or confound that influenced the DV |

Correlation Co-Efficient | a statistic used to indicate the direction and strength of the inner relationship between two variables measured on an interval/ratio scale |

Possible Values of a Correlation Co-Efficient | -1 (perfect negative) to 1 (perfect positive) |

Positive Relationship of Correlation | as one increases, the other increases |

Negative Relationship of Correlation | as one increases, the other decreases, or vice versa |

Why Correlation Cannot Determine Causation | 1) unclear which variable is cause and which is effect (directionality problem) 2) 3rd variable problem |

Mathematical Limitations of Correlations | 1) poor at capturing non-linear relationships 2) greatly affected by extreme scores 3) can be lowered by range restriction |

How to Find Main Effects in a Table or Graph | Table: average each level of the IVs - if they are the same, then no reliable ME Graph: middle of each line - if they are the same, then no reliable ME |

How to Find Interaction in a Table or Graph | Table: subtract - if they are the same, then no reliable interaction Graph: if lines interact, then reliable interaction |

Parametric Statistical Tests | require assumptions about the distraction of the DV in order to obtain correct p-values; symmetrically distributed |

Advantages of Non-Parametric Statistics | less restrictive and often easier to calculate than parametric tests |

Disadvantages of Non-Parametric Statistics | tend to be overly conservative (type II errors) and no non-parametric test exists for some research designs (ex: factorials) |

Participant Observation | a naturalistic observation in which the researcher becomes a member of the group being observed |