What is Experiment? Its 9 characteristics & Types

What is an Experiment?

An experiment is a scientific method used to establish causal relationships between variables. It involves the manipulation of an independent variable (IV) to observe its effect on a dependent variable (DV) while controlling extraneous factors. Experiments are widely used in psychology, natural sciences, and social sciences to test hypotheses under controlled conditions.

Definition of Experiment:
According to Kerlinger (1973), “An experiment is a systematic and scientific approach in which one or more independent variables are manipulated under controlled conditions to observe their effect on dependent variables.”

According to American Psychological Association (2018) Experiment is a series of observations conducted under controlled conditions to study a relationship with the purpose of drawing causal inferences about that relationship.

An experiment involves the manipulation of an independent variable, the measurement of a dependent variable, and the exposure of various participants to one or more of the conditions being studied.

Random selection of participants and their random assignment to conditions also are necessary in experiments. —experimental adj.

Properties of an Experiment

1. Manipulation – The researcher manipulates one or more independent variables.
2. Control – Extraneous variables are controlled to avoid confounding results.
3. Randomization – Participants are randomly assigned to different conditions to minimize bias.
4. Observation/Measurement – The effect of the IV on the DV is systematically observed and measured.
5. Replication – The experiment can be repeated to verify results.

Characteristics of an Experiment

An experiment is a structured investigation designed to establish cause-and-effect relationships between variables. It follows a scientific method where researchers systematically manipulate one or more independent variables (IVs) and observe the effect on a dependent variable (DV) while controlling for external influences. The following are the key characteristics of an experiment:

1. Manipulation of Variables

One of the fundamental features of an experiment is the deliberate manipulation of one or more independent variables (IVs) to examine their impact on the dependent variable (DV).

Example: In a study on the effects of sleep on memory, the researcher manipulates the amount of sleep (IV) and observes its impact on memory performance (DV).

Importance:

• Allows researchers to determine causal relationships between variables.
• Helps in understanding how one factor influences another.

2. Control Over Extraneous Variables

A well-designed experiment ensures that only the intended independent variable affects the dependent variable by controlling extraneous variables (i.e., unwanted influences that could affect results).

• Example: In an experiment on learning, researchers control environmental factors like noise and light so they don’t interfere with the study outcomes.

Importance:

• Increases internal validity, ensuring that observed changes in the dependent variable are due to the independent variable and not other factors.
• Reduces bias and confounding effects.

3. Randomization

To ensure fairness and eliminate selection bias, researchers use random assignment to allocate participants into different experimental conditions.

Example: In a drug trial, participants are randomly assigned to either the treatment group (receives the drug) or control group (receives a placebo).

Importance:

• Helps in creating equivalent groups, reducing the impact of individual differences.
• Ensures that the results are generalizable and not influenced by systematic bias.

4. Presence of Experimental and Control Groups

An experiment typically involves at least two groups:

• Experimental Group – Participants who receive the treatment or manipulation.
• Control Group – Participants who do not receive the treatment; they serve as a baseline for comparison.Example: In a study on the effect of caffeine on attention, one group drinks caffeinated coffee (experimental group), while another drinks decaffeinated coffee (control group).

Importance:

• Helps compare before and after effects of the independent variable.
• Ensures that the results are due to the experiment and not external influences.

5. Replicability (Reproducibility)

A good experiment should be repeatable by other researchers under the same conditions to check for consistency in results.

Example: If a psychologist conducts an experiment on stress and finds significant results, another psychologist should be able to replicate the experiment and obtain similar results.

Importance:

• Ensures scientific reliability.
• Strengthens the validity of research findings.

6. Hypothesis Testing

Experiments are hypothesis-driven and aim to either support or reject a proposed research hypothesis.

• Null Hypothesis (H₀): No effect or difference exists.
• Alternative Hypothesis (H₁): There is an effect or difference.

Example: A researcher tests whether music affects concentration.

• • H₀: Music has no effect on concentration.
  • H₁: Music improves concentration.

Importance:

• Helps in making data-driven conclusions.
• Forms the basis for statistical analysis and interpretation.

7. Measurement of Dependent Variable

An experiment involves systematic observation and measurement of the dependent variable to determine changes caused by the independent variable.

Example: In a study on the impact of exercise on mental health, mental health scores (DV) are measured before and after an exercise program.

Importance:

• Ensures that results are quantifiable and analyzable.
• Helps researchers draw objective conclusions.

8. Ethical Considerations

Researchers conducting experiments must follow ethical guidelines to ensure participant safety and rights. These include:

• Informed Consent: Participants must willingly agree to take part in the study.
• Confidentiality: Participant data should remain private.
• Right to Withdraw: Participants can leave the study at any time.
• Avoiding Harm: No physical or psychological harm should occur.

Example: In Milgram’s obedience study (1963), ethical concerns arose due to psychological distress experienced by participants. Today, stricter ethical guidelines exist.

Importance:

• Ensures respect, dignity, and well-being of participants.
• Increases public trust in scientific research.

9. Use of Statistical Analysis

Experimental results are analyzed using statistical methods to determine whether findings are significant.

• Descriptive statistics: Mean, median, standard deviation.
• Inferential statistics: t-tests, ANOVA, regression analysis.

Example: In a study on stress-reduction techniques, a t-test might be used to compare the stress levels of two groups before and after an intervention.

Importance:

• Helps in interpreting data objectively.
• Ensures that findings are not due to chance.

Experiments play a crucial role in scientific research by establishing causal relationships through manipulation, control, and systematic observation. Their reliability depends on randomization, control of extraneous variables, replicability, and ethical considerations. Understanding these characteristics ensures that experimental research maintains validity, reliability, and scientific credibility.

Types of Experiments

Experiments can be broadly classified into the following categories:

1. Laboratory Experiment

• Conducted in a highly controlled environment.
• Example: Milgram’s (1963) obedience study.
• Advantage: High internal validity.
• Disadvantage: Low external validity (may not generalize to real-life settings).

2. Field Experiment

• Conducted in a natural setting (e.g., school, workplace).
• Example: Piliavin et al. (1969) study on bystander behavior in a subway.
• Advantage: Higher ecological validity than lab experiments.
• Disadvantage: Less control over extraneous variables.

3. Natural (or Quasi) Experiment

• The researcher does not manipulate the IV; it occurs naturally.
• Example: Studying the psychological effects of a natural disaster.
• Advantage: Ethical alternative when manipulation is not possible.
• Disadvantage: Lack of control over variables.

4. Quasi-Experiment

• Participants are not randomly assigned; groups exist naturally.
• Example: Comparing cognitive abilities in different age groups.
• Advantage: Useful in studying real-world groups.
• Disadvantage: Possible confounding variables due to lack of randomization.

Conclusion

Experiments are essential in scientific research for testing hypotheses and establishing cause-and-effect relationships. By controlling extraneous variables and manipulating key factors, experiments provide reliable and valid results that contribute to scientific knowledge. However, the choice of experimental type depends on feasibility, ethical considerations, and the research question.

References:

• Kerlinger, F. N. (1973). Foundations of Behavioral Research. Holt, Rinehart, and Winston.
• Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67(4), 371–378.
• Piliavin, I. M., Rodin, J., & Piliavin, J. A. (1969). Good Samaritanism: An underground phenomenon? Journal of Personality and Social Psychology, 13(4), 289–299.
• Smith, P., & Mackie, D. (2007). Social Psychology. Psychology Press