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Bridging Null Hypothesis Testing and Estimation: A Practical Guide to Statistical Conclusion Drawing From Research in Psychology

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This guide demonstrates Bayesian analysis for statistical inference, suggesting intervals and population parameters for significance testing.

The study highlights the limitations of null hypothesis testing, showing how Bayesian analysis offers a robust alternative.
Bayesian methods provide intuitive probabilities for population parameters, unlike traditional frequentist approaches.
The analysis utilizes an illustrative empirical dataset for comparing means of two groups, demonstrating practical applications using R.
Each method's advantages and disadvantages are discussed, emphasizing their relevance in statistical analysis across various contexts.

Kiers et al. (2025) studied this question.

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This guide demonstrates Bayesian analysis for statistical inference, suggesting intervals and population parameters for significance testing.