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Research Methods. Learning How We Know What We Know. Why Scientific Method is Important. Avoids pitfalls in human logic: Human intuition Hindsight bias Overconfidence Confirmation bias False consensus effect Promotes critical thinking & healthy skepticism

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research methods

Research Methods

Learning How We Know What We Know

why scientific method is important
Why Scientific Method is Important
  • Avoids pitfalls in human logic:
    • Human intuition
    • Hindsight bias
    • Overconfidence
    • Confirmation bias
    • False consensus effect
  • Promotes critical thinking & healthy skepticism
  • Allows for stronger, more reliable conclusions to be drawn
descriptive methods
Descriptive Methods
  • Goal: Describe behavior, and that’s it.
  • Two main types of descriptive methods:
    • Naturalistic Observation
      • Researchers do not intrude on the natural behaviors
      • Avoids Hawthorne Effect
      • Examples: Jane Goodall (chimpanzees); Dian Fossey (mountain gorillas)
      • Cannot draw conclusions about behavior
      • Cannot generalize to others
descriptive methods1
Descriptive Methods
  • Two main types of descriptive methods:
    • Case Studies
      • In-depth study of one person/group
      • Necessary for some types of research:
        • Child abuse, crime, physical injuries, mental illness, etc.
      • Examples: Genie, brain injury cases
      • Cannot generalize to others
      • Numerous case studies culled together can draw limited conclusions
inferential methods
Inferential methods
  • Infer conclusions about variables
  • Stronger than descriptive studies
  • Main types of inferential methods:
    • Correlations
      • Show relationships between variables
        • Direct (positive) correlation: variables vary together
        • Inverse (negative) correlation: variables vary separately
      • CORRELATION DOES NOT MEAN CAUSATION!
inferential methods1
Inferential methods
  • Correlations (continued)
    • Correlation Coefficients: number indicating the strength and direction of a relationship
    • Range from -1 to +1
      • -1 indicates the strongest inverse relationship
      • +1 indicates the strongest direct relationship
      • 0 indicates no relationship
inferential methods2
Inferential Methods
  • Correlations (continued)
    • How are correlations obtained?
      • Surveys: essential elements
        • Representative sample
          • Obtained through random sampling
        • Questions/Statements
          • Multiple Choice
          • Yes/No
          • Rank Order
          • Likert Scale
inferential methods3
Inferential Methods
  • Correlations (continued)
    • How are correlations obtained?
      • Longitudinal studies
        • Same group over long period of time
      • Cross-Sectional studies
        • Several cohort groups at the same time
slide12

Problems with Interpreting Correlations

Directionality:

Third Variable:

inferential methods4
Inferential Methods
  • Main types of inferential methods:
    • Experimentation
      • Can determine cause & effect relationships
      • Strongest methodology available
      • One factor is manipulated
      • Another factor is measured
      • Control of all variables is important!
        • Confounding variables must be controlled!
inferential methods5
Inferential Methods
  • Steps in the experimental process:
    • Form a hypothesis
      • Two main types of hypotheses:
        • Null hypothesis states that no relationship exists between/among the variables
          • Scientific notation: H0
        • Alternative hypothesis states the predicted relationship between/among variables
          • Scientific notation: HA
        • Experiments test the null hypothesis, not the alternative
inferential methods6
Inferential Methods
  • Steps in the experimental process:
    • Create an operational definition of variables in the hypothesis
      • Written in behavioral terms
      • Not designed to be “all-inclusive”
      • Identifies independent and dependent variables
inferential methods7
Inferential Methods
  • Independent & Dependent Variables
    • DV: the variable that is measured by the researchers
      • AKA: the “effect” in the study
      • Easier to identify, because it’s what the researchers are hoping will happen in the study
    • IV: the variable that is changed/manipulated by the researchers
      • AKA: the “cause” in the study
      • It’s what the researchers hope is causing the DV
      • Must be something researchers can change
        • Age, gender, IQ, etc., are not IVs – they are “variables of interest”
inferential methods8
Inferential Methods
  • Identify the following IVs & DVs:
    • Exposing children to public television improves reading skills.
    • Rewarding comments will make people work harder on an assembly line.
    • A young monkey will prefer to spend time with a pretend mother monkey covered in cloth who provides no milk over a pretend mother monkey covered in wire who provides milk.
    • People who have psychotherapy are less likely to have psychological problems in the future.
    • Being polite to others tends to make people more cooperative.
    • Extroverted people are more fun at parties.
inferential methods9
Inferential Methods
  • Steps in the experimental process:
    • Determine the population of participants
      • Acquire a representative sample from the population by random sampling.
      • Divide sample into two main groups through random selection:
        • Experimental group receives the independent variable.
        • Control group does not receive the independent variable.
inferential methods10
Inferential Methods
  • Steps in the experimental process:
    • Ways to group participants:
      • Within-subjects design
        • AKA: pre/post design
        • Ps are compared to each other
        • Is less susceptible to individual differences
        • Is more susceptible to “practice effects”
inferential methods11
Inferential Methods
  • Steps in the experimental process:
    • Ways to group participants:
      • Between-subjects design
        • Ps are divided into two groups and compared to each other
        • Is more efficient
        • Avoids “practice effects”
        • Is more susceptible to individual differences
          • Way to address problem: Matched-subjects design
          • Match Ps according to a predetermined variable (age, gender, IQ, etc.) and make sure each group shares same individual characteristic.
inferential methods12
Inferential Methods
  • Steps in the experimental process:
    • Ways to control variables:
      • Placebo-control groups
      • Blind studies
        • Single-blind: Ps don’t know which group they are in.
        • Double-blind: Ps and people conducting the study don’t know which group the Ps are in.
        • Helps control expectation effects, demand characteristics, and researcher bias
      • Control environmental conditions
inferential methods13
Inferential Methods
  • Steps in the experimental process:
    • Conduct the study
    • Conduct statistical analysis
      • Descriptive statistics
        • Measures of central tendency: mode, median, mean, range, standard deviation
      • Inferential statistics
        • Determine statistical significance
          • p = .05 – There is a 95% likelihood that the results of the study are NOT due to chance.
ethics
Ethics
  • Ethics guidelines keep research from harming participants.
    • Main principles:
      • The benefits of the study must outweigh the harm to the participants.
      • Informed consent must be obtained.
        • Must know they are in a research study
        • Must be allowed to back out of the study at any time without penalty
      • Participants must be debriefed about the true intentions of the study afterward.
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