Experimental design principles

1. Formulate the research question

2. Define Hypotheses

3. Identify of variables to measure

   • Independent variables (the factor being manipulated)
   • Dependent variables (the observed outcome or response)
   • Control variables are factors held constant to prevent confounding effects
   • You may want to build a causal graph

4. Power Analysis and Sample Size calculations

   Conduct a power analysis to determine the sample size needed for the experiment to detect a meaningful effect. This helps ensure that the study has sufficient statistical power.

5. Design Test and Control Groups

6. Randomization and/or Blocking

   • Randomly assign participants to different experimental conditions. Randomization helps ensure that the groups are comparable at the start of the experiment, reducing the impact of confounding variables.
   • Implement blocking (grouping participants based on certain characteristics) and randomization within blocks to enhance the precision of estimates and control for potential confounding variables.

7. Blinding

   • Single-blind studies conceal information from participants
   • Double-blind studies extend this to both participants and experimenters.

8. Statistical Analysis

   Choose appropriate statistical methods to analyze the data. This may include t-tests, analysis of variance (ANOVA), regression analysis, and other inferential statistics.

9. Documentation and Logging

   Maintain detailed records of the experimental procedure, including any modifications made during the course of the study. Log relevant data point for post-experiment analysis

10. Ethical Considerations

    Adhere to ethical guidelines in the treatment of human or animal subjects. Obtain informed consent, minimize harm, and provide debriefing when necessary

Types of Experimental Designs

1.) Completely Randomized Design (CRD)

2.) Randomized Block Design (RBD)

• Blocking: Experimental units are grouped into blocks based on some known characteristic that is expected to affect the response variable. The blocks are formed in such a way that units within a block are more similar to each other than to units in other blocks.
• Random assignment within blocks: After forming blocks, experimental units within each block are randomly assigned to different treatment groups

3.) Factorial Design