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Quantitative Research - Coggle Diagram

- - - - Basic minimum of control to make the result of the experiment interpretable
      - Experimental treatment really makes a difference in dependent variable?
      - Researcher confident factor being control
    - - Generalisability of the results
      - The more extensively the results can be generalized, the more useful the research
  - - - Posttest - Measure taken after the experimental treatment
      - Simplest form, efficient design (involves 2 group)
      - Pretest - Measure given to the subject
      - Contains as many group (a control/comparison group).
    - - Given prior to administering the experimental treatment
      - Subject randomly assigned to group
      - Used as a statistical control in the analysis
      - Contain as many group (control group)
    - - Combination 2 design (posttest-only control group design & pretest-posttest control group design)
      - Include 2 control and 2 experimental groups (Receive same experimental treatment)
      - Only 1 group from the control & experimental is pretested
    - - Requires a min of 2 independent variables
      - Minimum design - 2 x 2 factorial
      - Advantages
        
        provide the economy of a single design
        
        Allow to investigate the interactions between the variables
      - Determine by the levels of the independent variables taken in combination
    - - Measure the same subject more than once
  - - - Use of intact groups of subjects
    - - Lack of random assignment
        
        Internal: Different selection of subjects(
        
        External: Intact Group (can't be argued & have the possibility the selection becomes bias)
    - - Posttest-Only, Nonequivalent Control Group Design
        
        Same as experimental design, except no random assignment
      - Pretest-Posttest, Nonequivalent Control Group Design
        
        Subject not randomly assigned
        
        Subject are pretested
- - - - not highly related, dropped from further examination
      - High related, examined in causal-comparative/experimental studies
  - - - Test hypotheses
      - Variables to be correlated
      - Relationship to be investigated should be logical one
      - Correlational "Treasure Hunts" - strongly discouraged
    - - 30 Participants (minimal)
      - Develop valid & reliable measures
    - - Paired scores - correlation
      - Result - correlation coefficient
    - - Correlation Coefficient
        
        range from +1.00 to 0.00 to -1.00
        
        near +1.00 - a high size & a positive direction
        
        near .00 - variables are not related
        
        near -1.00 - a high negative direction
    - - Relationship Studies
        
        Variables related to complex variables
        
        Subsequent examination
        
        Provide control
        
        identified relationship between variable
        
        Removes other influence
      - Prediction Studies
        
        Predictor - variable used to predict (can use more than 1)
        
        Criterion - variable that is predicted
        
        Accurate result - contain several variable for each correlation
- - - - Self report instrument
      - Observation
      - Interview & Observation
    - - Cross-sectional survey
        
        Collected data from selected individuals
        
        Limitation: Don't provide sufficient perspective to make needed decision
      - Longitudinal Survey
        
        collect 2 or more times to measure
        
        Study the dynamics of an issues over time
- - - - Hypothesis Testing - process of decision about the result
      - Null Hypothesis: No difference/relationship between variable
    - - Two-Tailed & One-Tailed Test
      - T-Test: determine two means are significantly different, look at the p-value
      - Simple (One-way) ANOVA
        
        Analysis of variance
        
        Multiple comparison post hoc test
    - - investigate two or more independent variable and the interactions
    - - Appropriate for nominal data
      - compares the proportions, to see if they significantly different
  - - - Scoring Procedures: scored accurately & consistenly, standardiesed instrument & self-develop instruments
      - Tabulation & Coding Procedures
    - - Measure of variability
      - Measures of relative position
      - Measures of central tendency
      - Measure of relationship
    - - Mode
      - Median
      - Mean
    - - The range: difference between the highest & the lowest score
      - Variance: amount of spread among test scores
      - The Standard Deviation (SD): Interval/ratio data
    - - Person
      - Spearman