Introduction to Experimental Research

Definition: Experimental research is a type of research that allows researchers to infer causation between two variables, specifically that variable A causes variable B.
- Key Features:
  - Random assignment
  - Experimenter control

Ability to Infer Causation: Unlike correlational research, experimental research can determine causal relationships due to its structure and features.

Random Assignment:
- Definition: Random assignment refers to the process of randomly assigning participants to either the experimental group or the control group.
- Purpose: This process ensures that the groups are roughly equal at the beginning of the experiment, minimizing the impact of pre-existing differences.
- Method of Implementation: Researchers might use random methods such as flipping a coin to assign participants.
- Importance of Random Assignment:
  - Prevents self-selection bias, whereby participants choose groups based on their preferences (e.g., nature lovers choosing the experimental group).
  - Enhances the generalizability of results by ensuring a diverse participant pool across both conditions.

Research Hypothesis: Exposure to nature may reduce stress levels.
Experimental Setup:
- Experimental Condition: Participants walk through a forest for exposure to nature.
- Control Condition: Participants sit in an empty room to minimize external stimuli (neutral situation).
Measurement of Stress:
- Stress can be measured through various methods such as surveys and physiological measures like blood samples to assess stress hormones.

Definition: Experimenter control involves the manipulation of one variable by the experimenter to determine its effect on another variable.
Causal Inference: By controlling the exposure to nature, researchers can effectively determine how this exposure influences stress levels.
- This mechanism is what allows us to conclude causation rather than just correlation.

Independent Variable (IV):
- Definition: The independent variable is the presumed cause that the researcher manipulates during the experiment.
- Example: In the nature study, the independent variable is whether participants are exposed to nature or not.
Dependent Variable (DV):
- Definition: The dependent variable is the presumed effect, which the researcher measures in response to the manipulation of the independent variable.
- Example: In the nature study, the dependent variable is the measured level of stress after exposure.
- Contextualization: The change in the dependent variable depends on the manipulation of the independent variable, establishing a direct link between the two.
Confounding Variables:
- Definition: Confounding variables are uncontrolled variables that can affect the results of the experiment and provide alternative explanations for observed effects.
- Examples:
  - Background factors of participants (e.g., personality traits or mood at the time of the study).
  - External factors that are not controlled by the researchers (e.g., environmental influences that are unrelated to the experimental conditions).
- Implications of Confounding Variables: Any significant confounding variable can skew results, making it difficult to interpret the observational outcomes.

Understanding the inherent features of experimental research, the conflicting variables involved, and the methodology of random assignment and control is crucial for establishing causal relationships in psychological studies. This ensures that findings are valid, reliable, and generalizable across different populations.