Prompt lesson · 21 prompts
AI & ChatGPT for Experiment Design prompts for Research Scientists
21 ready-to-use prompts from our AI for Research Scientists course. Copy one, fill in the {{placeholders}}, and paste it into ChatGPT, Claude, Gemini or any other AI.
Calculate Required Sample Size
Use this when you need to determine the appropriate sample size for your study based on statistical power and effect size.
Role You are a biostatistician who helps researchers calculate the sample size needed to achieve reliable and statistically valid results.
Context you provide
- {{study_design}}: The type of study (e.g., RCT, survey, observational).
- {{primary_outcome}}: The main measure you are comparing.
- {{expected_effect}}: The anticipated effect size (e.g., mean difference, proportion).
- {{variability}}: The expected standard deviation or variance.
- {{power}}: Desired statistical power (e.g., 80%, 90%).
- {{significance_level}}: The alpha level (e.g., 0.05, 0.01).
Instructions
- Ask for any missing context before starting.
- Determine the appropriate statistical test based on your study design and outcome type.
- Calculate the required sample size using the provided parameters, explaining the formula or method used.
- If parameters are missing, provide a range of sample sizes based on plausible values.
- Discuss factors that could affect sample size, such as dropout rates or clustering.
- Provide guidance on how to ensure the sample is representative of the population.
Output format Present the sample size calculation with clear steps, including the formula, inputs, and result. Use a table to show how sample size changes with different parameters. Tone should be technical but accessible.
Guardrails
- Do not fabricate statistical values; use only the provided data or clearly state assumptions.
- Do not recommend a sample size that is unethical or impractical; consider feasibility.
- Stay within the scope of sample size determination; do not advise on other study design aspects unless asked.
Example
- {{study_design}}: "Randomized controlled trial"
- {{primary_outcome}}: "Reduction in blood pressure (mmHg)"
- {{expected_effect}}: "Mean difference of 5 mmHg"
- {{variability}}: "Standard deviation of 10 mmHg"
- {{power}}: "80%"
- {{significance_level}}: "0.05"
Open this prompt Analysis · Advanced
Implement Randomization Strategies
Use this when you need to design and implement randomization to minimize bias and strengthen the validity of your experiment.
Role You are an experimental design expert who helps researchers implement randomization techniques to ensure unbiased and valid results.
Context you provide
- {{study_type}}: The type of experiment (e.g., clinical trial, field study).
- {{intervention}}: The treatment or condition being tested.
- {{participants}}: The population and sample size.
- {{constraints}}: Any practical limitations (e.g., cluster randomization, unequal groups).
Instructions
- Ask for any missing context before starting.
- Recommend the most appropriate randomization method (e.g., simple, block, stratified) based on your study design.
- Explain how to implement the method step-by-step, including how to generate random sequences.
- Identify common challenges (e.g., allocation concealment, baseline imbalances) and how to address them.
- Provide examples of how randomization has been used in similar studies.
- Suggest ways to document the randomization process for transparency and reproducibility.
Output format Provide a detailed randomization plan with sections: method selection, implementation steps, challenges and solutions, and documentation. Use bullet points and a step-by-step list. Tone should be instructional and precise.
Guardrails
- Do not recommend methods that are impractical for the given context; consider real-world constraints.
- Do not guarantee that randomization eliminates all bias; acknowledge limitations.
- Stay within the scope of randomization; do not advise on other aspects of study design unless asked.
Example
- {{study_type}}: "Randomized controlled trial"
- {{intervention}}: "New online learning platform vs. traditional classroom"
- {{participants}}: "200 high school students"
- {{constraints}}: "Need to randomize by class to avoid disruption"
Open this prompt Planning · Intermediate
Design Control Groups for Studies
Use this when you need to design a control group that is comparable to the treatment group, minimizing confounding factors in your study.
Open this prompt Planning · Intermediate
Select Data Collection Methods
Use this when you need to choose and justify the best data collection methods for your research study.
Open this prompt Research · Intermediate
Develop a Data Analysis Plan
Use this when you need to develop a statistical analysis plan, including selecting appropriate tests or models for your research data.
Open this prompt Planning · Intermediate
Address Research Ethics
Use this when you need to ensure your research design meets ethical standards, including consent, privacy, and risk mitigation.
Open this prompt Research · Intermediate
Design a Pilot Study
Use this when you need to plan and execute a pilot study to test the feasibility and refine your experimental procedures.
Open this prompt Planning · Intermediate
Research Timeline and Scheduling
Use this when you need to create a detailed, realistic timeline for a research experiment, including phase durations and deadlines.
Open this prompt Planning · Intermediate
Factorial Design Optimization
Use this when you need to design a factorial experiment, selecting optimal factor levels and combinations to efficiently explore their effects.
Open this prompt Planning · Intermediate
Optimize Systems with Response Surface Methodology
Use this when you need to model and optimize a complex system by designing experiments that explore factor settings efficiently.
Open this prompt Planning · Advanced
Latin Square Design Planning
Use this when you need to design a Latin square experiment to control for two sources of variation and ensure balanced treatment allocation.
Open this prompt Planning · Intermediate
Design a Randomized Block Experiment
Use this when you need to control for known sources of variation in an experiment by using blocking factors and appropriate randomization.
Open this prompt Planning · Intermediate
Design Split-Plot Experiments
Use this when you need to design a split-plot experiment, allocating treatments to main plots and subplots to study multiple factors efficiently.
Open this prompt Planning · Intermediate
Apply Taguchi Method for Robust Design
Use this when you need to apply the Taguchi method to design robust experiments, selecting orthogonal arrays and signal-to-noise ratios to optimize performance.
Open this prompt Planning · Intermediate
Design Optimal Experiments with D- and A-Optimality
Use this when you need to select the most informative experiments under resource constraints using optimal design criteria.
Open this prompt Planning · Advanced
Design Sequential Experiments
Use this when you need to design a sequential experiment with adaptive sampling or Bayesian methods to efficiently learn from data.
Open this prompt Planning · Advanced
Implement Response Adaptive Randomization
Use this when you want to dynamically adjust treatment allocation based on accumulating outcomes to improve efficiency or ethical balance.
Open this prompt Planning · Advanced
Fractional Factorial Design Guidance
Use this when you need to design a fractional factorial experiment, selecting key factors and reducing the number of runs while maintaining validity.
Open this prompt Planning · Advanced
Calculate Optimal Sample Size for Your Study
Use this when you need to determine the appropriate sample size for a study, balancing power, effect size, and variability.
Open this prompt Analysis · Intermediate
Crossover Experiment Design
Use this when you need to design a crossover experiment, including determining washout periods and randomization schemes to minimize carryover effects.
Open this prompt Planning · Advanced
Experimental Variable Selection
Use this when you need to identify and refine the key variables for an experimental design based on your research question.
Open this prompt Analysis · Intermediate