Experiments, Correlations, Parametrics
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| Quasi-Experiment | research technique that does NOT have random assignment, but in which the researcher manipulates the IV
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| Investigations | research technique that does NOT allow researcher to infer causation; no random assignment
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| Experiment | a study that has random assignment and the researcher manipulates the IV
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| Theory | explanation for a phenomenon that can be falsified and that involves entities that cannot be directly observed
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| Hypothesis | a tentative statement about the relationship between observable variables
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| Can't Prove the Null Hypothesis | impossible to prove that the IV has no effect on the DV
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| Random Assignment | occurs when every subject has an equally likely chance to be assigned to each IV level/to each treatment order
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| 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
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| Internal Validity | the extent to which your research provides a valid test of the relationship between the IV and DV
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| External Validity | the extent to which the results of your research can be applied outside the research situation
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| Alpha | the probability of making a Type I error given that our experiment found an effect of the IV on the DV
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| Beta | the probability of making a Type II error given that our experiment failed to find an effect of the IV on the DV
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| Levels of the IV | specific values of the IV that the researcher uses in a study
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| Mean v. Median | mean more affected by extreme scores but more consistent and easier to calculate
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| Frequency Distribution | a graph showing the # of times each score occurred in a data set
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| Normal Distribution | symmetrical, bell-shaped distribution
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| Positively Skewed Distribution | distribution w/ a few extreme high scores
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| Negatively Skewed Distribution | distribution w/ a few extreme low scores
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| Advantage of Experimental Approach | allows researcher to infer a causal relationship between the IV and DV
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| 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
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| 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
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| Possible Values of a Correlation Co-Efficient | -1 (perfect negative) to 1 (perfect positive)
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| Positive Relationship of Correlation | as one increases, the other increases
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| Negative Relationship of Correlation | as one increases, the other decreases, or vice versa
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| Why Correlation Cannot Determine Causation | 1) unclear which variable is cause and which is effect (directionality problem)
2) 3rd variable problem
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| Mathematical Limitations of Correlations | 1) poor at capturing non-linear relationships
2) greatly affected by extreme scores
3) can be lowered by range restriction
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| 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
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| 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
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| Parametric Statistical Tests | require assumptions about the distraction of the DV in order to obtain correct p-values; symmetrically distributed
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| Advantages of Non-Parametric Statistics | less restrictive and often easier to calculate than parametric tests
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| 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)
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| Participant Observation | a naturalistic observation in which the researcher becomes a member of the group being observed
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