Skill UI

This comprehensive checklist guides researchers through finalizing scientific figures and tables for submission to PNAS. It enforces rigorous standards covering optimal column sizing, minimum font size, displaying underlying data (points and 'n'), colorblind accessibility, and maintaining data integrity. Use this guide before submission to ensure your visualizations meet high journal standards.

This guide ensures authors meet the rigorous standards for submitting figures and tables to PNAS Nexus. It covers critical aspects including managing the page budget (graphical-element count), optimizing sizing for print legibility, visualizing raw data points (vs. means), ensuring colorblind-safe palettes, and maintaining complete data integrity by retaining raw, unprocessed source images.

A comprehensive guide for designing and presenting empirical evidence (tables and figures) in Production and Operations Management (POM) manuscripts. It helps authors manage the limited 'exhibit budget' across the main paper and the online e-companion, ensuring that all visuals are decision-legible, operationally relevant, and adhere to journal standards.

This skill guides the creation of rigorous, self-contained tables and figures (exhibits) for academic journals like Public Opinion Quarterly (POQ). It ensures that all visual data accurately report design-based uncertainty, weighting adjustments, and the base N, meeting the high standards required for empirical survey research.

This guide details best practices for creating high-impact tables and figures for psychological science manuscripts, adhering to APA 7th edition guidelines. It emphasizes showing effect sizes, uncertainty (like confidence intervals), and embedding visuals directly within the main text near their first discussion, moving beyond traditional end-of-document placement. It covers data visualization principles and manuscript triage.

Provides comprehensive guidelines for designing tables and figures (exhibits) for academic manuscripts. The focus is on creating self-contained, highly accessible visualizations that effectively communicate quantitative effect magnitude and uncertainty to both specialized scholars and public practitioners, optimizing impact for publication.

Provides detailed guidelines for constructing high-quality tables and figures for Quantitative Economics (QE) manuscripts. It emphasizes adhering to strict academic standards, such as replacing significance asterisks with standard errors and confidence bands, placing exhibits in-text, and ensuring all visuals are self-contained, professionally formatted, and journal-compliant.

This guide provides detailed best practices for presenting empirical results, specifically tailored for top-tier economics journals like the QJE. It emphasizes shifting from 'table-heavy' to 'figure-forward' visualization, covering techniques for event-study plots, RDD discontinuity plots, and ensuring all exhibits are self-contained, readable, and follow strict academic formatting standards.

This guide provides best practices for building self-explanatory, high-impact exhibits for interdisciplinary academic manuscripts. It covers the structured design of complex visualizations, including regression tables, bibliometric maps, event-study plots, and qualitative data structures. The goal is to ensure every figure and table carries the core innovation mechanism and is immediately interpretable by diverse readers (e.g., policymakers, managers, and economists).

This guide outlines the standards for creating publication-quality tables and figures for economics journals, particularly adhering to the rigorous 'REStat' house style. It ensures that the main findings are legible in a single, self-contained exhibit, emphasizing standard errors, clear notes, and load-bearing visualizations.

This guide provides comprehensive best practices for structuring tables and figures (exhibits) in empirical finance papers. It addresses the strict 60-page journal limit, advising authors on how to present core findings, identify mechanisms, and display robustness evidence while maintaining readability. Learn how to move mechanical grids to appendices, focus the main body, and ensure every visual element is self-contained and highly interpretable for top-tier referees.

Provides comprehensive guidelines for designing high-impact scientific figures for major academic journals. It covers technical aspects like optimal sizing, font legibility, and colorblind safety, while also enforcing strict data visualization practices (e.g., using dot plots over bars, defining 'n', ensuring data integrity). Use this as a final quality check before submission to guarantee scientific rigor and maximize publication chances.