Detailed_Experimental_Design_Presentation.pptx

Experimental design ppt

1. Guide to Experimental Design Eufemio D. Adarayan Jr. Research Enthusiast

2. Presentation Outline

3. Key terms Experiments  are used to study  causal relationships . You manipulate one or more  independent variables  and measure their effect on one or more dependent variables. Experimental design  create a set of procedures to systematically  test a hypothesis . A good experimental design requires a strong understanding of the system you are studying.

4. What is Experimental Design? Experimental design is the process of planning a research study to test hypotheses , determine cause-and-effect relationships , and ensure valid, reliable results. It involves manipulating one or more independent variables to assess their effect on dependent variables.

5. Key Steps in Experimental Design

6. Important!

7. Define Your Variables Identify independent (variables you manipulate), dependent (variables you measure), and controlled variables (constants throughout the experiment).

8. Define Your Variables

9. Define Your Variables

10. Define Your Variables

11. Write Your Hypothesis Formulate a clear, testable statement predicting the outcome of your experiment, based on existing theories or observations.

12. Write Your Hypothesis The next steps will describe how to design a  controlled experiment . In a controlled experiment, you must be able to: Systematically and precisely manipulate the independent variable(s). Precisely measure the dependent variable(s). Control any potential confounding variables.

13. Design Your Experimental Treatments Plan how to manipulate the independent variable(s) across different groups or conditions to observe varying effects.

14. Design Your Experimental Treatments

15. Assign Your Subjects to Treatment Groups Use random assignment to place participants in different groups, ensuring each has an equal chance of being in any condition. This helps eliminate bias and confounding variables. Study size Treatment groups Control Groups Randomization

16. Assign Your Subjects to Treatment Groups Randomization. A n experiment can be completely randomized or randomized within blocks (aka strata): In a  completely randomized design , every subject is assigned to a treatment group at random. In a  randomized block design  (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

17. Assign Your Subjects to Treatment Groups Sometimes randomization isn’t practical or  ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a  quasi-experimental design .

18. Between-subjects vs. within-subjects In a  between-subjects design  (also known as an independent measures design or classic  ANOVA  design), individuals receive only one of the possible levels of an experimental treatment. In medical or social research, you might also use  matched pairs  within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions. In a  within-subjects design  (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured. Counterbalancing  (randomizing or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

19. Assign Your Subjects to Treatment Groups

20. Measure Your Dependent Variable Decide on how to accurately and consistently measure the outcomes of your experiment, considering the tools, techniques, and timing of data collection.

21. Measure Your Dependent Variable How precisely you measure your dependent variable also affects the kinds of  statistical analysis  you can use on your data. Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

22. In conclusion

23. The important thing is not to stop questioning. Curiosity has its own reason for existing. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery every day. Never lose a holy curiosity. -Albert Einstein