Results Interpretation

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Standardizes the communication of statistical results by providing rigorous guidelines for data interpretation and reporting. This skill ensures that research findings are presented with the necessary nuance, focusing on practical importance through effect sizes and the precision of estimates with confidence intervals. It helps researchers avoid common pitfalls like p-hacking or misinterpreting p-values as the probability of a hypothesis being true, resulting in more robust, publication-ready results and discussion sections.

Características Principales

• Prioritization of effect sizes and 95% confidence intervals
• Guidance on avoiding common p-value misinterpretations
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• Nuanced interpretation of practical vs. statistical significance
• Procedures for multiple comparison adjustments and exploratory analysis
• Standardized reporting of descriptive statistics and test statistics

Casos de Uso

• Writing results and discussion sections for academic research papers
• Ensuring statistical reporting meets rigorous peer-review standards
• Evaluating the practical significance of experimental findings