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  1. Independent Variable
    • Experimental stimulus
    • Cause
    • Researcher manipulated
  2. Dependent Variable
    • Not researcher manipulated
    • Effect
  3. Pretesting and Postesting
    Measuring of a dependent variable among subjects prior to the experiment and after being exposed.
  4. Experimental Group
    Receive stimulus
  5. Control Group
    Does not receive stimulus
  6. Experimental Research Designs
    • One-Shot Case Study
    • One Group Pretest-Posttest Design
    • Static-Group Comparison
  7. One Shot Case Study
    • Researcher measures a single group of subjects on a dependent variable following the administration of an experimental stimulus.
    • Ex: Show video to one group and give questionnaire.
  8. One Group Pretest Posttest Design
    Researcher adds a pretest for the experimental group but lacks a control group
  9. Static Group Comparison
    • Researcher does not add pretest to the experimental or control group.
    • Has control and experimental group.
  10. Guidelines for asking questions
    • Choose appropriate question forms: open closed
    • Make items clear
    • Avoid Double-Barreled Questions
    • Respondents must be competent to answer
    • Respondents must be willing to answer
    • Questions should be relevant
    • Short items are best
    • Avoid negative items
    • Avoid Biased items and terms
  11. Coding
    Process of transforming raw data into a standardized form.
  12. Manifest Content
    • visible, surface content-
    • Ex: count the number of times things blow up, people are being shot at to determine violence in a movie.
  13. Latent Content
    • Underlying meaning of communications,
    • Ex: overall assessment of how violent the movie was.
  14. Quasi-Experimental Design
    Nonrigorous inquires somewhat resembling controlled experiments but lacking key elements such as pre- and posttesting and/or control group.
  15. Time series design
    Design that involves measurements made over some period
  16. Nonequivalent Control Groups
    Control group that is similar to the experimental group but is not created by the random assignment of subjects
  17. Multiple Time-series Designs
    Improved version of the nonequivalent control group design
  18. Qualitative Data Analysis
    Nonumerical examination and interpretation of observations
  19. Linking theory and analysis
    • Search for explanatory patterns
    • “plausible relationships proposed among the concepts and sets of concepts”
    • - Strauss and corbin
  20. Discovering Patterns
    seek to discover patters such as changes over time or possible causal links among variables.
  21. Six different ways of looking for patterns in a particular research topic
    • Frequencies: how often does it occur?
    • Magnitudes: examine the degree at which it happens
    • Structures: what types?
    • Processes: is there any order?
    • Causes: what could have caused it?
    • Consequences: how does it affect?
  22. Open Coding
    initial classification and labeling of concepts
  23. Axial Coding
    • identify the core concepts
    • Ex: perception of fairness
  24. Selective Coding
    • identify the central concept that organizes the other concepts that have been identified
    • ex: Professor-student relationships.
  25. Quantitative Analysis
    Numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena
  26. To conduct quantitative analysis:
    • Researcher must engage in a coding process after the data has been collected
    • Generate codes from your data
  27. Developing Code Categories
    • Begin with well developed coding scheme: Researcher may use existing coding scheme
    • Generate codes from your data: researcher creates his/her own codes
  28. Central Tendency
  29. Mean
    Dividing the sum of the values by the total number of cases
  30. Mode
    Most frequently occurring attribute
  31. Median
    The middle attribute in the ranked distribution of observed attributes
  32. Dispersion
    distribution of values around some central value, such as an average
  33. Range
    • distance separating the highest from the lowest value
    • Example: Indicate that the age range is from 13 to 19
  34. Standard Deviation
    measure of dispersion around the mean
  35. Statistical Analysis
    • Applied branch of mathematics especially appropriate for a variety of research analyses
    • Two types: Descriptive and Inferential Statistics
  36. Descriptive Statistics
    Statistical computations describing either the characteristics of a sample or the relationship among variables in a sample
  37. Inferential Statistics
    The body of statistical computations relevant to making inferences from findings based on sample observations to some larger population
  38. Idiographic Reasoning
    Identifying all the reasons for a single outcome.
  39. Nomothetic Reasoning
    Identifying some of the reasons for a class of situations.
  40. Induction
    Expands from specific to general
  41. Deduction
    Reduces from general to specific
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