Psychology 242 exam 2

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Psychology 242 exam 2
2010-10-24 19:15:27
UIC Psychology

Psychology and Research Methods
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  1. Describing Relationships
  2. Quantitative variable relationships
    • linear: positive, negative, no correlation
    • non-linear: curved
  3. Quantifying the relationship
    • correlation coefficient: pearson's r represents the strength
    • interval & ratio scales
    • correlations are rarely bigge than .30
    • measurement error tends to produce weaker correlations: one way to think about strength is the mean difference
  4. Describing relations involving one categorical variable
    • groups differ in mean score?
    • direction?
    • size of the difference?
  5. Significance test
    If probability is low the relation is real
  6. Correlation & Causation
  7. One variable cause another
    • making infeerences about causality: one variable causes another to occur
    • directionality problem
  8. 3rd variable problem
    • 3rd variable cause both variables to be correlated
    • very common
    • there can be more than one
    • indirect & direct
    • negative & positive
  9. Controlled Experiments
  10. DV & IV
    • IV has levels
    • they both have operational definitions: not a causal statement
    • random assignment: different types of people are equally distributed to each condition
    • manipulation of the IV: eliminates the 3rd variable problem
  11. Confounds & more
  12. Internal & external validity
    • internal: confirm in the experiment
    • external: confirm outside the experiment
  13. Experimental control
    • maximizes internal validity
    • sometimes limits external validity
    • external validity matters, but without internal validity we dont know what's causing what in either the lab or the real world
  14. Increasing external validity in experiment
    • replicate with many samples
    • when studying abstract variables, ues many concrete instances as feasible
    • create a naturalistic atmosphere, both physically and/or psychologically with deceltion
  15. Interpreting "null" results
    • was your manipulation of your IV powerful enough?
    • was your DV sensitive enough to detect differences in the score?: Ceiling effect & floor effect
    • did you have enough people in your groups to detect a difference?
    • was there a lot of random errorm in the measure of your DV?
  16. Units of observation
    • smallest level of data on all variables
    • each unit if observation can be any defiable unit for which the variable differs from one unit to the next
  17. Within-subject manipulation
  18. Between subjects
    different people are assigned to different conditions (or levels) of the IV
  19. Within subjects
    (repeated measure) the same people are exposed to all levels or conditions of the IV
  20. Benefits of within-subjects design
    • no random sampling error; only measurement
    • mortality not a confound
    • requires half as many subjects
    • greater statistical power to eliminate chance as an explanation
  21. Weaknesses of within-subject designs
    • order effects
    • history effects: event ex. 9/11
    • maturation effects
    • carryover effects: something about the first condition caries over into the second condition
  22. Carryover Effects
    • fatigue effects: people get tired or bored during the study; performance effects
    • practice effects: more engaging; having pratice
    • testing effects: familiarity; study
    • contamination effects: what happens in the 1st condition spills over and "contaminates" the 2nd
  23. Counterbalancing
    • order effects becaome confounds, if one condition always comes first
    • confound is eliminated if each condition comes in each order
    • large order effects can still weaken the observed effect of the IV
    • complete: every subject gets every order
    • incomplete: different subjects get different orders
  24. Factorial Design
    • more than one independent variable
    • each level of the first IV is paired with each level if the second IV
    • ex. 2x2= 4 conditions
    • 2 experiments in 1
    • matrix table
    • interaction: the difference between the IV's