Skill UI

Utilize Monte Carlo simulation to model complex marketing scenarios and predict revenue outcomes with quantified probability distributions. This tool is essential for assessing downside risk, understanding potential upside, and validating the probability of hitting specific revenue targets when testing budget shifts, channel mix changes, or new campaign launches.

A comprehensive framework for translating reduced-form causal estimates (e.g., elasticity, treatment effects) into explicit policy statements. It guides researchers on building clear welfare, cost-benefit, or optimal-policy models, defining sufficient statistics, and articulating distributional effects, ensuring policy claims are rigorously grounded in empirical data.

This guide outlines the rigorous standards for presenting tables and figures in Cognitive Psychology manuscripts. It emphasizes moving beyond simple bar charts of means, requiring authors to overlay the model's predicted curve onto observed data, reveal distributions and uncertainty intervals, and accurately report parameter estimates with confidence intervals. The goal is to ensure reproducible, comprehensive, and highly informative scientific communication.

A comprehensive guide to the rigorous theoretical foundations required in advanced econometrics and theoretical statistics. It covers proving identification conditions (parameter uniqueness), deriving limiting distributions (asymptotics), and establishing existence and uniqueness from fundamental axioms. Essential for manuscripts requiring deep methodological proof, particularly for top-tier academic journals.

This guide provides rigorous guidelines for designing and presenting results in Experimental Economics manuscripts. It emphasizes making the treatment comparison and its uncertainty immediately visible through specific figure types (distributions, dynamics plots) and structured tables, ensuring the findings are self-contained and highly credible for academic review.

A comprehensive guide for auditing and improving the scientific rigor of hardware architectural evaluations (e.g., HPCA style). It emphasizes establishing a clear 'fidelity contract' defining tools, scope, and configurations. It requires that all performance claims are backed by credible instruments, mandates capturing full machine state provenance, ensuring honest baseline tuning, and reporting results via per-workload distributions rather than single means.

This guide provides best practices for creating high-impact tables and figures (exhibits) for academic journals, especially in behavioral economics. It emphasizes visualizing the core behavioral comparison—such as treatment effects, dynamic changes over rounds, or underlying distributions—so the main finding is immediately visible before reading any text. Key practices include using confidence intervals over significance stars, ensuring grayscale readability, and providing self-contained captions.

A comprehensive guide detailing the data sharing and transparency requirements for submitting manuscripts to the Journal of Marriage and Family (JMF). It specifically addresses the challenge of restricted-use family datasets, teaching researchers how to document access paths and ensure replication-level detail without direct data redistribution.

This guide outlines the rigorous formal requirements for econometric papers, focusing on achieving the level of mathematical rigor expected by top academic journals. It covers proving identification, verifying primitive assumptions, constructing asymptotic derivations (consistency, rate, distribution), and structuring proofs for maximum verifiability in causal inference and time series analysis.

A guide for advanced data analysis in policy evaluation, extending beyond standard causal estimates. It emphasizes rigorous reporting of cost-benefit ratios, distributional consequences (who gains and who pays), robust heterogeneity testing, and honest uncertainty quantification necessary for high-level policy academic journals. Essential for turning effect sizes into decision-relevant policy narratives.

This comprehensive guide provides best practices and an audit checklist for designing robust, real-world experiments in mobile and wireless communication systems. It emphasizes moving beyond simulations, detailing necessary RF setups, quantifiable energy metrics, and reporting statistical distributions to ensure high academic credibility.

A comprehensive guide for authors submitting papers to mobile and wireless networking conferences (e.g., MobiCom). It emphasizes structuring the paper around measured evidence, ensuring every claim is paired with a precise operating regime and empirical proof. Key sections cover the 'first-page arc,' reporting distributions instead of superlatives, and managing the manuscript's page budget for maximum impact.