Prompt lesson · 22 prompts
Experimental Design prompts for Research Associates
22 ready-to-use prompts from our AI for Research Associates course. Copy one, fill in the {{placeholders}}, and paste it into ChatGPT, Claude, Gemini or any other AI.
Bayesian Experimental Design Guide
Use this when you need to design experiments that incorporate prior knowledge, optimize resources, and handle uncertainty.
Role You are a statistical consultant specializing in Bayesian experimental design. Your goal is to help me design robust experiments that leverage prior information, optimize sample sizes, and adapt to new data.
Context you provide
- {{specific context}}: The field or scenario where Bayesian design is applied (e.g., clinical trials, A/B testing).
- {{specific application}}: The particular use case for incorporating prior information (e.g., drug efficacy, user engagement).
- {{specific study}}: The study for which you need sample size and resource optimization.
Instructions
- If any of the above inputs are missing, ask for them before proceeding.
- Explain Bayesian experimental design, contrasting it with traditional frequentist methods, using the provided context.
- Provide concrete examples of how prior information can be incorporated, tailored to the application.
- Discuss how Bayesian approaches optimize sample sizes and resource allocation, referencing the specific study.
- Summarize advantages and limitations, including practical considerations for implementation.
Output format A structured response with sections: 'Key Differences', 'Examples', 'Optimization Strategies', and 'Advantages & Limitations'. Use clear headings and bullet points. Keep tone professional and accessible.
Guardrails
- Do not invent statistical facts; base explanations on established Bayesian principles.
- Flag any assumptions about the context or application.
- Stay within the scope of experimental design; avoid unrelated statistical topics.
Example
- {{specific context}}: clinical trials, {{specific application}}: dose-finding, {{specific study}}: a Phase II trial.
Open this prompt Learning · Intermediate
Control Group Design
Use this when you need to design a control group that ensures experimental integrity and minimizes bias.
Role You are an experimental design consultant. Your goal is to help me create a control group that is representative, unbiased, and ethically sound.
Context you provide
- {{topic}}: The research topic or question.
- {{study_design}}: The overall study design (e.g., RCT, quasi-experimental).
- {{participant_characteristics}}: Key characteristics that should be balanced between groups (e.g., age, gender, severity).
Instructions
- If any of the above inputs are missing, ask for them before proceeding.
- Outline the key factors to consider when planning the control group, such as size, selection criteria, and representativeness.
- Identify common pitfalls in control group design (e.g., selection bias, contamination) and how to avoid them.
- Provide best practices for selecting participants to ensure comparability with the experimental group, using the given characteristics.
- Discuss ethical considerations, including informed consent and equitable treatment.
Output format Present the plan in sections: Key Considerations, Pitfalls to Avoid, Participant Selection, Ethical Considerations, and Recommendations. Use bullet points for readability. Keep the tone professional and practical.
Guardrails
- Do not recommend unethical practices; emphasize participant welfare.
- Flag any assumptions about the study population or setting.
- Stay focused on control group design, not on the entire experimental protocol.
Example Topic: Effect of a new drug on blood pressure; study design: RCT; participant characteristics: age, baseline blood pressure, gender.
Open this prompt Planning · Intermediate
Create Fractional Factorial Designs
Use this when you need to design a fractional factorial experiment to study main effects efficiently, especially with many factors.
Open this prompt Planning · Advanced
Data Collection Method Selection
Use this when you need to choose and justify a data collection method for your research, considering validity and ethics.
Open this prompt Decisions · Intermediate
Design a Pilot Study
Use this when you need to plan a small-scale study to test procedures, estimate sample sizes, or refine methods before a full experiment.
Open this prompt Planning · Intermediate
Design Factorial ANOVA Experiments
Use this when you need to design a factorial ANOVA experiment to analyze the effects of multiple factors on an outcome.
Open this prompt Planning · Intermediate
Design Randomization Procedure
Use this when you need to design or evaluate a randomization procedure for participant assignment in a study.
Open this prompt Planning · Intermediate
Design Randomized Control Trials
Use this when you need to design a randomized control trial, including randomization methods and sample size calculations.
Open this prompt Planning · Advanced
Determine Sample Size for Studies
Use this when you need to calculate the required sample size for a research study to ensure statistical significance.
Open this prompt Analysis · Intermediate
Ethical Research Design Review
Use this when you need to identify and address ethical issues in your research design, ensuring participant protection and compliance.
Open this prompt Analysis · Intermediate
Explore Quasi-Experimental Designs
Use this when you need to understand or choose quasi-experimental designs for evaluating interventions when randomization is not possible.
Open this prompt Learning · Intermediate
Generate and Refine Research Hypotheses
Use this when you need to brainstorm and refine potential hypotheses for your research, considering variables and existing literature.
Open this prompt Creating · Beginner
Generate Latin Square Design
Use this when you need to create a balanced experimental layout with multiple treatments and blocking factors.
Open this prompt Creating · Intermediate
Optimize Factorial Design Combinations
Use this when you need to optimize factor and level combinations in a factorial design to capture significant effects and interactions.
Open this prompt Planning · Intermediate
Plan Response Surface Experiments
Use this when you need to design and analyze response surface methodology experiments to optimize process parameters.
Open this prompt Planning · Advanced
Plan Sequential Experimentation
Use this when you need to design adaptive and efficient experiments that can be adjusted based on interim results.
Open this prompt Planning · Advanced
Plan Split-Plot Experiments
Use this when you need to design experiments that involve both hard-to-change and easy-to-change factors, typical in split-plot designs.
Open this prompt Planning · Advanced
Select Optimal Design Criteria
Use this when you need to choose and apply optimal design criteria like D-optimality or A-optimality for efficient experiments.
Open this prompt Planning · Advanced
Statistical Analysis Plan
Use this when you need to outline the statistical tests and analyses for your research study.
Open this prompt Planning · Intermediate
Summarize Research Literature
Use this when you need to quickly understand key findings, methodologies, or themes from specific papers or a body of literature.
Open this prompt Research · Beginner
Taguchi Method Experiment Design Guide
Use this when you need to design or learn how to apply a Taguchi robust-design experiment in your field.
Open this prompt Learning · Advanced
Variable Identification
Use this when you need to clearly define the independent and dependent variables in your research study.
Open this prompt Analysis · Beginner