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    • Identify The Research Objective
    • Identify Independent and Dependent Variables
    • Define and Group The Population
    • Conduct Pre-Tests
    • Conduct The Research
    • Conduct Post-Tests
    • Analyse The Collected Data

    Identify the variables which you need to analyze for a cause-and-effect relationship. Deliberate which particular relationship study will help you make effective decisions and frame this research objective in one of the following manners: 1. Determination of the impact of X on Y 2. Studying how the usage/application of X causes Y

    Establish clarity as to what would be your controlling/independent variable and what variable would change and would be observed by the researcher. In the above samples, for research purposes, X is an independent variable & Y is a dependent variable.

    Define the targeted audience for the true experimental design. It is out of this target audience that a sample needs to be selected for accurate research to be carried out. It is imperative that the target population gets defined in as much detail as possible. To narrow the field of view, a random selection of individuals from the population is car...

    Before commencing with the actual study, pre-tests are to be carried out wherever necessary. These pre-tests take an assessment of the condition of the respondent so that an effective comparison between the pre and post-tests reveals the change brought about by the research.

    Implement your experimental procedure with the experimental group created in the previous step in the true experimental design. Provide the necessary instructions and solve any doubts or queries that the participants might have. Monitor their practices and track their progress. Ensure that the intervention is being properly complied with, otherwise...

    Gauge the impact that the intervention has had on the experimental group and compare it with the pre-tests. This is particularly important since the pre-test serves as a starting point from where all the changes that have been measured in the post-test, are the effect of the experimental intervention. So for example: If the pre-test in the above ex...

    Use appropriate statistical tools to derive inferences from the data observed and collected. Correlational data analysis tools and tests of significance are highly effective relationship-based studies and so are highly applicable for true experimental research. This step also includes differentiating between the pre and the post-tests for scoping i...

    • True Experimental Design. In the world of experiments, the True Experimental Design is like the superstar quarterback everyone talks about. Born out of the early 20th-century work of statisticians like Ronald A. Fisher, this design is all about control, precision, and reliability.
    • Quasi-Experimental Design. So, let's talk about the Quasi-Experimental Design. Think of this one as the cool cousin of True Experimental Design. It wants to be just like its famous relative, but it's a bit more laid-back and flexible.
    • Pre-Experimental Design. Now, let's talk about the Pre-Experimental Design. Imagine it as the beginner's skateboard you get before you try out for all the cool tricks.
    • Factorial Design. Now, buckle up, because we're moving into the world of Factorial Design, the multi-tasker of the experimental universe. Imagine juggling not just one, but multiple balls in the air—that's what researchers do in a factorial design.
  2. True Experimental Design. Martyn Shuttleworth 418.4K reads. True experimental design is regarded as the most accurate form of experimental research, in that it tries to prove or disprove a hypothesis mathematically, with statistical analysis.

  3. True experiments work best with relatively large sample sizes, and random assignment, a key criterion for a true experimental design, is hard (and unethical) to execute in practice when you have people in dire need of an intervention.

  4. True experimental design is best suited for explanatory research questions. True experiments require random assignment of participants to control and experimental groups. Pretest/post-test research design involves two points of measurement—one pre-intervention and one post-intervention.