Vertaile menetelmiä

	Kuva- ja taulukkoraportointi: Tietojen visualisoinnin standardit	Tilastollisen raportoinnin standardit: analyysien läpinäkyvä raportointi
Tieteenala	Tieteellinen kirjoittaminen	Tieteellinen kirjoittaminen
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	1983	2005
Kehittäjä	Tufte (visual communication theory), ICMJE standards, APA style guide	Statistical and methodological literature; emphasized by Cumming (2013), ICMJE, and replication crisis discussions
Tyyppi	Guideline	Guideline
Alkuperäislähde	American Psychological Association (2020). Publication Manual of the American Psychological Association (7th ed.). Washington, DC: American Psychological Association. ISBN: 978-1-4338-3216-1	Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 25(1), 7–29.
Rinnakkaisnimet	data visualization, table design, figure captions	reporting statistics, statistical transparency, effect size reporting
Liittyvät	4	4
Tiivistelmä	Tables and figures are the primary means of presenting research data in scientific manuscripts. A well-designed table or figure enables readers to grasp complex data patterns instantly; a poorly designed one obscures findings or misleads. The ICMJE Recommendations and APA Publication Manual establish standards for table and figure formatting, captions, legends, and referencing. Tables are best used for precise numerical values and comparisons across rows and columns; figures (graphs, plots, images) are better for illustrating trends, relationships, or distributions. Both must be self-contained (understandable without consulting the text) and referenced clearly in the manuscript.	Transparent reporting of statistical results—including effect sizes, confidence intervals, p-values, and assumptions—is essential for scientific integrity and reproducibility. Many published studies report p-values in isolation without effect sizes or confidence intervals, making it impossible for readers to assess the magnitude of findings. Statistical reporting standards, emphasized by Cumming (2013), the American Statistical Association, and the ICMJE, require effect sizes, confidence intervals, and discussion of uncertainty. This enables readers to judge whether findings are practically significant (not just statistically significant) and to compare effect sizes across studies in meta-analyses. Poor statistical reporting wastes research and prevents proper synthesis of evidence.