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12 Cards in this Set
- Front
- Back
Independent Groups
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Groups that are independent of each other. usually aimed at finding out the effects of a single variable to the group. Each group is tested in a different condition.
ex. testing levels of testosterone in males and females. |
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Independent groups: cause and effect
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if and only if appropriate study is conducted
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Independent groups: goal
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show that the IV causes a change in DV
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Independent groups: true experiment
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IV must be under the control of the researcher
ex. taking rats and causing aggression. |
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Quasi-experimental design
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no cause and effect: IV "chosen" by participant.
ex. males & females |
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Steps in conducting experiment
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6 steps
1. formulate hypothesis 2. select appropriate IV & DV 3. consider and control extraneous variables 4. manipulate IV & DV: carry out experiment and collect data 5. Analyze variation in DV - appropriate statistical technique 6. Draw inferences about relationship between IV & DV - use inferential stats to make statements about the population based on sample findings. |
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Controlled experiments in the laboratory
Advantages vs. Disadvantages |
Advantages
1. Better control over IV 2. Better control over extraneous variables 3. More precise measures of DV 4. Improved internal validity Disadvantages 1. Some phenomena can’t be studied in the lab 2. Ethical problems 3. Practical disadvantages (costly, time consuming) 4. May lack external validity |
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Experiments in the field
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Improved external validity
May lack internal validity (lack of control) |
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Completely randomized groups designs
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One IV
Participants randomly assigned to different levels of one IV. ensures initial equivalence between groups. Scores are assumed to be independent of each other. Different levels of one IV; no control |
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Simplest completely randomized design
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2 group design.
independently assigned to either a control group or experimental: 2 levels of 1 IV answer the question: did the manipulation of the IV affect the DV? |
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Randomized factorial groups designs
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more external validity
more than one IV (factor) allow us to assess the relationship between IV's (interaction effect) as well as the effect of multiple factors (main effect). Answers the question: did the IV affect the DV? |
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what happens to the complexity of a factorial design when the number of levels of each variable and the number of IVs increases?
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complexity increases.
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