Research Methods and Experimental Design

Unit 1: Research Methods

1.1 Experiments

Hypothesis

• Hypothesis: A testable statement based on the aims of an investigation.
• Alternative Hypothesis: Predicts a difference in the DV (Dependent Variable) due to changes in the IV (Independent Variable).
  • Directional Hypothesis (one-tailed): Predicts the direction (increase/decrease) of the relationship between variables.
  • Non-directional Hypothesis (two-tailed): States that a relationship exists without specifying the direction of the difference.
• Null Hypothesis: Suggests that any observed difference or correlation is due to chance, with no real pattern arising from the variables being studied.

Sampling Methods

1. Opportunity Sampling

   • Definition: Participants are chosen based on their availability.
   • Example: Selecting university students present at the research location.
   • Strengths:
     • Quick and easy method.
     • Can yield a larger sample size.
   • Weaknesses:
     • Often non-representative due to limited variety.
     • Potential for bias.

2. Volunteer Sampling

   • Definition: Participants are invited to participate, often responding to advertisements.
   • Example: Recruitment through flyers or online ads.
   • Strengths:
     • Easy recruitment as participants self-select.
     • Likely to have committed participants.
   • Weaknesses:
     • Non-representative due to similarity among respondents.
     • Risk of low response rates.

3. Random Sampling

   • Definition: All members of a population are assigned numbers, and participants are selected randomly.
   • Example: Pulling numbers from a hat or using a random number generator.
   • Strengths:
     • More likely to be representative.
     • Quick to administer.
   • Weaknesses:
     • Random sampling might inadvertently yield unequal representation (e.g., many participants from one demographic).

Experimental Variables

• Experiment: An investigation to determine relationships between variables.
• Independent Variable (IV): The factor manipulated to create different conditions in the experiment.
• Dependent Variable (DV): The factor measured in the experiment.
• Operationalization: The clear description of a variable for accurate manipulation and measurement.

Controlling Variables

• Controls: Techniques to ensure potential confounding variables remain constant.
• Standardization: Keeping procedures identical for all participants.
• Confounding Variables: Uncontrolled variables that may systematically affect the DV, obscuring the relationship with the IV.
• Participant Variables: Individual differences (age, personality, intelligence) that could influence results.
• Situational Variables: Environmental factors that can act as confounding variables (e.g., light, noise).

Experimental Conditions

• Experimental Group/Condition: Represents one or more levels of the IV.
• Control Group/Condition: A level of IV where the IV is absent, used for comparison.

Types of Experiments

• Lab Experiments:

  • Strengths: Good control of variables, causal relationships can be determined, standardized procedures enhance reliability.
  • Weaknesses: Artificial settings may affect behavior, leading to demand characteristics.

• Field Experiments:

  • Strengths: More natural behaviors due to real settings, reduced demand characteristics.
  • Weaknesses: Harder to control variables, raising issues of reliability and replication.

Experimental Design

1. Independent Measures: Different groups for each IV level; reduces order effects but may suffer from individual differences.
2. Repeated Measures: Same participants used in all conditions; risks order effects (practice/fatigue).
   • Counterbalancing: Balances order effects by varying the sequence of conditions.
3. Matched Pairs: Participants paired based on relevant characteristics; helps control individual differences but may be difficult to execute properly.

Validity

• Validity: The extent to which the researcher is measuring what they claim to.
  • Ecological Validity: Generalizability of findings to real-world situations.
  • Objectivity vs. Subjectivity: Depend on personal bias in data interpretation.
  • Demand Characteristics: Factors that influence behavior by revealing study aims.

Reliability

• Reliability: Consistency of results across multiple trials.
  • Inter-rater Reliability: Consistency between different researchers interpreting data similarly.
  • Test-retest Reliability: Consistency of results when the same test is repeated under similar conditions.

Ethical Considerations

• Ethical Guidelines: Considerations aimed at protecting participants' welfare.
  • Protection from Harm: Participants should not face undue risks.
  • Informed Consent: Participants must understand the study to agree.
  • Right to Withdraw: Participants can leave the study any time.
  • Confidentiality and Privacy: Safeguarding personal information and emotional space.
• Debriefing: Providing explanations of the study's aims and outcomes after completion.

Ethical Guidelines Specific to Animals

• Minimizing Harm: Ensuring ethical treatment of animals used in research.
  • Replacement, Reduction, and Refinement: Methods to lessen animal use and suffering during experiments.