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If the purpose of a research is to test a hypothesis of a causal relationship between variables, which of the following research designs is most suita
Question

If the purpose of a research is to test a hypothesis of a causal relationship between variables, which of the following research designs is most suitable for such a research study?

A.

Formulative Research Design

B.

Descriptive Research Design

C.

Experimental Research Design

D.

Diagnostic Research Design

Correct option is C

Experimental Research Design

An Experimental Research Design is the most suitable method for testing a causal relationship between variables. It involves manipulating one or more independent variables and observing their effect on the dependent variable under controlled conditions.

  • The primary goal of experimental research is to establish cause-and-effect relationships between variables.
  • It typically involves the use of randomization, control groups, and treatments to ensure reliable results.
  • Researchers can control extraneous variables, reducing the chances of alternative explanations for the observed effects.
  • Experimental research is commonly used in scientific disciplines, such as psychology, medicine, and social sciences, to validate hypotheses.

Thus, experimental research design is the best approach for hypothesis testing when studying causal relationships.


Information Booster:

  • Experimental research involves independent and dependent variables, with the researcher manipulating the independent variable to observe its impact.
  • Randomization is a key feature, ensuring that subjects are randomly assigned to different groups (e.g., control and experimental).
  • Control groups help in comparing the effects of the manipulated variable against a baseline.
  • This method is widely used in scientific studies, such as clinical trials, behavioral research, and psychology experiments.
  • Two main types of experimental research:
    • Laboratory experiments (highly controlled environment)
    • Field experiments (real-world settings)
  • Statistical tools, such as t-tests, ANOVA, and regression analysis, are commonly used to interpret experimental data.
  • Example: Testing the effect of a new drug (independent variable) on patient recovery (dependent variable) through clinical trials.

Additional Information:

  • Formulative Research Design (Option 1): Used for exploratory studies to gain insights and develop hypotheses, not for testing causal relationships.
  • Descriptive Research Design (Option 2): Focuses on describing characteristics and patterns of variables but does not establish causality.
  • Diagnostic Research Design (Option 4): Aims at identifying causes of a problem but does not manipulate variables to test causal effects.

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