Hypothesis generation (dataset)

--- allowed-tools: Task, Read, Write, Bash, Grep, Glob argument-hint: [dataset] [domain] description: Generate research hypotheses and experimental designs based on data patterns --- # Hypothesis Generation Command Generate research hypotheses and experimental designs for dataset $1 in domain $2 using the hypothesis-generator subagent. ## Context - Dataset location: @data_storage/$1 - Analysis domain: $2 (user-behavior, business-impact, technical-performance, custom) - Current working directory: !pwd - Output directory: ./hypothesis_reports/ - Available research methodologies and experimental designs - Statistical analysis capabilities ## Your Task Use the hypothesis-generator subagent to create rigorous, testable hypotheses: ### 1. Pattern Analysis - Identify significant correlations and relationships - Detect temporal patterns and trends - Discover clusters and segments in the data - Recognize anomalies and unusual patterns ### 2. Hypothesis Formulation - Create clear, testable hypotheses - Define null and alternative hypotheses - Specify variables and their relationships - Establish measurable outcomes and success criteria ### 3. Experimental Design - Select appropriate research methodologies - Design experimental approaches to test hypotheses - Determine sample size and power requirements - Plan data collection and measurement procedures ### 4. Validation Strategy - Define statistical testing approaches - Establish success criteria and metrics - Plan for replication and verification - Consider alternative explanations and approaches ## Analysis Domains ### User Behavior - Engagement Patterns: User interaction and engagement hypotheses - Conversion Optimization: Conversion rate and funnel analysis hypotheses - Retention and Churn: User retention and churn prediction hypotheses - Segmentation: User behavior segmentation hypotheses - Journey Analysis: User journey and path analysis hypotheses ### Business Impact - Revenue Optimization: Revenue generation and growth hypotheses - Cost Reduction: Cost efficiency and optimization hypotheses - Market Expansion: Market growth and expansion hypotheses - Customer Satisfaction: Customer experience and satisfaction hypotheses - Operational Efficiency: Process improvement and efficiency hypotheses ### Technical Performance - System Optimization: Performance and scalability hypotheses - Reliability: System stability and reliability hypotheses - Security: Security vulnerability and protection hypotheses - User Experience: Technical UX and performance hypotheses - Integration: System integration and compatibility hypotheses ### Custom - Domain-Specific: Custom domain-specific hypotheses - Research-Oriented: Academic and research hypotheses - Experimental: Novel experimental hypotheses - Predictive: Predictive modeling hypotheses ## Hypothesis Types ### Descriptive Hypotheses Describe patterns and relationships in the data without inferring causation. Example: "There is a positive correlation between user engagement time and conversion rates." ### Explanatory Hypotheses Explain underlying mechanisms and causal relationships. Example: "Increased user engagement time leads to higher conversion rates due to improved product understanding." ### Predictive Hypotheses Forecast future outcomes based on current patterns. Example: "Users with engagement time > 5 minutes are 3x more likely to convert within 30 days." ### Prescriptive Hypotheses Recommend optimal actions and interventions. Example: "Implementing personalized recommendations will increase user engagement by 25%." ## Research Methodologies ### Experimental Designs - A/B Testing: Randomized controlled experiments - Multivariate Testing: Multiple variable experiments - Longitudinal Studies: Time-series analysis - Cross-sectional Studies: Point-in-time analysis - Quasi-experiments: Non-randomized designs - Case Studies: In-depth analysis of specific cases ### Statistical Approaches - Hypothesis Testing: Statistical significance testing - Confidence Intervals: Estimation of effect sizes - Bayesian Methods: Bayesian hypothesis testing - Power Analysis: Statistical power calculation - Effect Size Measurement: Quantifying relationship strength ### Validation Methods - Cross-validation: Model validation techniques - Bootstrapping: Resampling validation - Sensitivity Analysis: Testing robustness - Replication Studies: Independent verification - Meta-analysis: Synthesis of multiple studies ## Expected Output ### Hypothesis Documentation - hypothesis_reports/$1_$2_hypotheses.md - Hypothesis documentation - hypothesis_reports/$1_$2_experimental_design.md - Experimental design - hypothesis_reports/$1_$2_validation_plan.md - Validation strategy - hypothesis_reports/$1_$2_research_proposal.md - Research proposal ### Hypothesis Structur