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Not researcher manipulated
Pretesting and Postesting
Measuring of a dependent variable among subjects prior to the experiment and after being exposed.
Does not receive stimulus
Experimental Research Designs
One-Shot Case Study
One Group Pretest-Posttest Design
One Shot Case Study
Researcher measures a single group of subjects on a dependent variable following the administration of an experimental stimulus.
: Show video to one group and give questionnaire.
One Group Pretest Posttest Design
Researcher adds a pretest for the experimental group but lacks a control group
Static Group Comparison
Researcher does not add pretest to the experimental or control group.
Has control and experimental group.
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
Process of transforming raw data into a standardized form.
visible, surface content-
: count the number of times things blow up, people are being shot at to determine violence in a movie.
Underlying meaning of communications,
: overall assessment of how violent the movie was.
Nonrigorous inquires somewhat resembling controlled experiments but lacking key elements such as pre- and posttesting and/or control group.
Time series design
Design that involves measurements made over some period
Nonequivalent Control Groups
Control group that is similar to the experimental group but is not created by the random assignment of subjects
Multiple Time-series Designs
Improved version of the nonequivalent control group design
Qualitative Data Analysis
Nonumerical examination and interpretation of observations
Linking theory and analysis
Search for explanatory patterns
“plausible relationships proposed among the concepts and sets of concepts”
- Strauss and corbin
seek to discover patters such as changes over time or possible causal links among variables.
Six different ways of looking for patterns in a particular research topic
: how often does it occur?
: examine the degree at which it happens
: what types?
: is there any order?
: what could have caused it?
: how does it affect?
initial classification and labeling of concepts
identify the core concepts
: perception of fairness
identify the central concept that organizes the other concepts that have been identified
: Professor-student relationships.
Numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena
To conduct quantitative analysis:
Researcher must engage in a coding process after the data has been collected
Generate codes from your data
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
Dividing the sum of the values by the total number of cases
Most frequently occurring attribute
The middle attribute in the ranked distribution of observed attributes
distribution of values around some central value, such as an average
distance separating the highest from the lowest value
: Indicate that the age range is from 13 to 19
measure of dispersion around the mean
Applied branch of mathematics especially appropriate for a variety of research analyses
: Descriptive and Inferential Statistics
Statistical computations describing either the characteristics of a sample or the relationship among variables in a sample
The body of statistical computations relevant to making inferences from findings based on sample observations to some larger population
Identifying all the reasons for a single outcome.
Identifying some of the reasons for a class of situations.
Expands from specific to general
Reduces from general to specific