comm research

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  1. texts
    any kind of communication that can be documented
  2. Cohen's Kappa
    • K = #agree/#possible - 1/n
    • _______________________

  3. minimum acceptable inter-relater reliability
  4. what causes low inter-relater reliability?
    • 1. definition problems
    • 2. coding rules
    • 3. coder drift
  5. 6 types of texts
    • 1. public/private
    • 2. mediated/non-mediated
    • 3. scripted/unscripted
  6. Scott's pi
    •    2M
    •  _______

    N1 + N2
  7. How do we increase inter-rater reliability?
    • 1. good definitions
    • 2. clearly defined coding rules
    • 3. test inter-relater reliability often
  8. 3 criteria for good coding system
    • 1. mutually exclusive
    • 2. exhaustive
    • 3. equivalent
  9. strengths of content analysis
    • - less biased & more comprehensive than surveys
    • -unobtrusive
    • -less expensive to make errors
  10. weaknesses of content analysis
    • -limited to recorded information
    • -validity problems
    • -coding can be too simplistic
    • -assuming there is a uniform relationship between symbols and meaning
  11. How are experiments unique?
    only method that implies causality
  12. What are the requirements for inferring causality?
    • 1. IV + DV are correlated
    • 2. IV comes before DV
    • 3. Rule out alternative explanations
  13. strengths of experiments
    • - ability to isolate the experimental variable and effect over time
    • -experiments don't involve large number of subjects and can be replicated many times
  14. weaknesses of experiments
    • -artificiality
    • -little likelihood situations will occur in real life
  15. Double - Blind
    neither experimenter nor anyone who comes in contact with the participants has knowledge of whether they are in control group or experimental group
  16. Control group
    subject to exact same conditions as experimental group, except without the IV
  17. random group assignment
    • each participant has an equally likely chance of being in control or experimental group
    • gives assurance that each group is equivalent
  18. matching
    rather than random assignment, experimenters predict what variables might affect the DV and account for those in the group assignment
  19. pretesting/posttesting
    • testing the DV before and after IV is administered
    • gives researchers a baseline to compare effects of IV
  20. manipulation check
    asks participants after the study if the independent variable actually meant what it was intended to
  21. experimenter effect
    experimenter unconsciously treats subjects differently if they know the purpose of the study, affecting how participants behave
  22. observer bias
    if researchers/observers know which subjects are in experimental/control group, what they see may be biased
  23. researcher attribute effect
    traits of the researcher affect behavior/data of subjects
  24. Hawthorne effect
    participant's responses are influenced because they are aware of being observed
  25. Testing effect
    participants are primed by the test to respond in a certain way
  26. maturation effect
    subjects naturally change over time during the study regardless of the independent variable
  27. experimental mortality effect
    participants drop out before the study is complete
  28. selection bias effect
    when subjects are allowed to choose their groups, the groups will not be the same to begin with
  29. intersubject bias
    participants influence one another's behaviors
  30. compensatory rivalry
    one group compensates for missing experimental condition by working harder
  31. demoralization
    sense of not progressing causes control group to give up
  32. History effect
    a historical effect occurring outside the study affects the outcomes
  33. instrumentation
    unreliable scale yields unreliable results
  34. statistical regression
    outliers/extremes will naturally test closer to mean on posttest
  35. Maxi-con-mini
    • maxi: maximize IV
    • con: control for third/extraneous variables
    • mini: minimize error variance
  36. How do researchers minimize the weaknesses of experiments?
    • - make conditions the same for control & experimental group
    • -double-blindness
    • -random selection
    • -manipulation check
  37. Solomon 4
    • 2 control and 2 experimental groups
    • 1 experimental and 1 control are pretested
  38. alpha level
    significance of the probability that the stats are due to sampling error, measures statistical significance
  39. mean
  40. standard deviation
    measures dispersion of statistics, higher =more dispersed data
  41. correlation
    the extent to which two variables are related, the extent of agreement/consistency, shows reliability of results
  42. t-test
    examines the difference between two groups, will two groups with same IV vary on DV?
Card Set:
comm research
2012-12-13 05:01:52
communication research

final exam
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