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PSYC 305: FINAL EXAM

Main Effect
Effect independent variable has on the dependent variable across all independent variables
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Simple Main Effect
Analysis examines mean differences at each level of IV
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Independent Groups Design
Participants can be apart of either control or treatment group, not both
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Interaction
If there is an interaction between two IV, the effect of one IV depends on the particular level of other variable.
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Factorial Designs
Designs with more than one independent variable
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Manipulation Checks
Attempt to measure whether IV has the intended effect
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Straightforward Manipulation
Written, verbal, visual instructions
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One tailed Test
Has a predicted direction
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Two tailed test
Has no predicted direction
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Type 1 Error
Incorrect decision to reject the null hypothesis when it is true
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Type II Error
Incorrect decision to accept the null hypothesis when it is false
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ANOVA (Analysis of Variance)
Statistical procedure used to test the degree in which two or more groups vary or differ
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Effect size
Extent to which 2 variables are associated
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External Validity
Degree where results can be generalized
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Internal Validity
Results of the experiment are because of IV, not confounding variables
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Longitudinal Method
Same group @ different times
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Sequential Method
Uses both longitudinal, and cross sectional
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Cross sectional Method
People of different ages measured @ same point
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F Test
Difference among three or more groups to evaluate results of factorial design
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T test
Examine whether two groups are different
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Research hypothesis
Variable under investigation are related to the population
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Null hypothesis
Variable under investigation are not related to the population
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Descriptive Statistics
Describe the sample (mean, std, correlation)
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Inferential Statistics
Designed to determine whether results can be generalized to the population
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Sampling Distribution
Based on assumption that null hypothesis is true
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Interrupted Time Series Design
Examines DV over extended period of time both before and after IV is implemented
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Non Equivalent Control Group Pretest-Posttest Design
Most effective Quasi experiment. Participant-measure-treatment-measure Participant-measure-no treatment-measure
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Non Equivalent Control Group
Separate control group but participants in 2 conditions
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Solomon Four Group Design
Solomon Four Group Design
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Control Series Design
Improves interrupted time series by finding control group
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Floor Effects
Task too difficult that hardly anyone can perform ell
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Ceiling Effects
Tasks too easy that participants reach maximum performance
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Sensitivity
Important in measuring human performance
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Staged Manipulations
Necessary to create some psychological state in the participant or stimulate a situation that occurs in real life
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Program Evaluation
Research on programs that are implemented to achieve positive effect
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Repeated Measure Design
Same individuals participate in all conditions of the study
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Participant Variables
Personal attribute such as gender, age, ethnic group
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Problems with one group pretest posttest design
history maturation testing instrument decay regression toward the mean
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One group pretest posttest design
used to obtain a comparison
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One group posttest only design
lacks control group lack internal validity
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Quasi Experimental Design
used when control features of experiment cannot be achieved No random assignment IV cannot be manipulated
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Stages of Program Evaluation
Needs Assessment Program theory assessment Process Evaluation Outcome Evaluation Efficiency Assessment
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Multiple Baseline Design
Effectiveness of treatment is demonstrated when behavior change occurs after manipulation is introduced
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ABA design
Behavior is observed during baseline-observed during treatment-observed after experimental treatment is removed
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ABAB design
Similar to ABA. Treatment is introduced a second time
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Mixed Factorial Design
2 or more IV At least one repeated measure
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Demand Characteristics
Any feature of an experiment that might inform a participant the purpose of the study
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